On feat/agent-phase1-soul: pre-rebase-20260717: stale local .elh modifications from 07-04 (preserved)

Two compounding defects made every pause->approve write_file report success
while writing NOTHING:

1. The naive json_get scanner matches "content" anywhere in the approve
   body — including INSIDE tool_input, which for write_file always carries
   a content field. The handler therefore treated every approved builtin
   write as already-client-executed, skipped dispatch entirely, and handed
   the model the file's own content as the 'tool result'. The model then
   narrated 'Done, created' — a false receipt with no file. Builtin tools
   now ALWAYS dispatch server-side; client content is only honored for
   non-builtin (MCP/client-executed) tools. Stricter only.

2. write_file returned {"ok":true} unconditionally — fs_write's outcome
   was never checked, so any failed write also reported success. The write
   now verifies the file landed (fs_exists) and returns the RESOLVED path
   in the ok payload; failures return a real error naming the destination.

E2E on the test brain (boot 38): approve-path write lands byte-exact and
the result carries the resolved path; auto-run writes unchanged; denied
writes execute nothing. BUG-5 (approve wire lacked tool_name) had been
masking this one — two stacked bugs on the same path.

NOTE for review: the deeper cure is a nesting-aware json reader; this fix
removes the dangerous consequence at the two spots that lie about disk.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

awareness.el

@@ -219,9 +219,14 @@ fn proactive_curiosity() -> Bool {
     // Activate each term independently so substring seed-finding hits many nodes.
     // hops=1 (not 2): the in-process Engram has grown to 165K+ nodes. hops=2 BFS
     // visits far more nodes and returns much larger JSON blobs. On a graph this
-    // large, hops=1 still activates all directly-related nodes AND triggers the
-    // semantic seed supplement (cosine sim ≥ 0.70 scan over all embedded nodes),
-    // giving broad working-memory coverage without the quadratic blowup of hops=2.
+    // large, hops=1 still activates all directly-related nodes, giving broad
+    // working-memory coverage without the quadratic blowup of hops=2.
+    //
+    // NOTE: a semantic seed supplement (cosine sim ≥ 0.70 scan over embedded nodes)
+    // was planned alongside hops=1 but is NOT yet implemented — embed_ok in
+    // heartbeats confirms Ollama is reachable, but no embedding call is made during
+    // activation. The seed-finding loop in el_runtime.c uses istr_contains only.
+    // (2026-06-30 self-review: corrected stale comment)
     let curiosity_seed: String = curiosity_term_a + " " + curiosity_term_b + " " + curiosity_term_c
     let results_a: String = engram_activate_json(curiosity_term_a, 1)
     let results_b: String = engram_activate_json(curiosity_term_b, 1)
@@ -278,11 +283,20 @@ fn proactive_curiosity() -> Bool {
     let safe_auto: String = str_replace(auto_term, "\"", "'")
 
     let wmc: Int = engram_wm_count()
+    // wm_top snapshot in curiosity_scan ISE: top-3 WM nodes by weight.
+    // Heartbeat already records top-5 every 60s; curiosity_scan fires every 30s
+    // (scan_ms = beat_ms/2) and is the PRIMARY activation driver during idle.
+    // Without wm_top here, we can't see which nodes actually entered WM after
+    // each curiosity round — only the aggregate count. Top-3 is enough to
+    // diagnose "stuck on X" patterns without bloating the ISE payload.
+    // (2026-07-01 self-review)
+    let wm3: String = engram_wm_top_json(3)
     let ise: String = "{\"event\":\"curiosity_scan\",\"seed\":\"" + curiosity_seed
         + "\",\"auto_term\":\"" + safe_auto
         + "\",\"minute_block\":" + int_to_str(minute_block)
         + ",\"activated\":" + int_to_str(total_found)
         + ",\"wm_active\":" + int_to_str(wmc)
+        + ",\"wm_top\":" + wm3
         + ",\"ts\":" + int_to_str(ts) + "}"
     ise_post(ise)
     return total_found > 0

awareness.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header — do not edit
+// auto-generated by elc --emit-header - do not edit
 extern fn idle_count() -> Int
 extern fn idle_inc() -> Int
 extern fn idle_reset() -> Void
@@ -7,6 +7,7 @@ extern fn elapsed_ms() -> Int
 extern fn elapsed_human() -> String
 extern fn embed_ok() -> Int
 extern fn emit_heartbeat() -> Void
+extern fn auto_term_try_slot(slot_type: String, slot_lbl: String) -> Void
 extern fn proactive_curiosity() -> Bool
 extern fn pulse_count() -> Int
 extern fn pulse_inc() -> Int

chat.el

@@ -594,6 +594,44 @@ fn engram_compile(intent: String) -> String {
     if str_starts_with(ctx, "[") { return truncated + "]" }
     return truncated
 }
+// distill_transcript — extract the salient tail from a full conversation transcript.
+//
+// Purpose: before activating working memory on a transcript, reduce it to the
+// last N turns. Activating on the ENTIRE transcript (which may contain hundreds
+// of messages) would produce noisy, over-broad seed finding — too many nodes match
+// too many words, collapse the WM to breakthrough-floor nodes. Taking only the tail
+// focuses activation on what's contextually live right now.
+//
+// Handles two transcript formats:
+//   JSON array: [{"role":"human","content":"..."},...]  → extract last 3 messages' content
+//   Plain text: raw string                              → return last 500 chars
+//
+// Returns a string of at most 500 chars suitable for engram_compile/engram_activate.
+// (Added 2026-07-01 self-review: was called in handle_dharma_room_turn and
+// handle_dharma_chat but never defined — caused build failure since June 30.)
+fn distill_transcript(transcript: String) -> String {
+    if str_eq(transcript, "") { return "" }
+    // JSON array format: extract last 3 messages' content fields
+    if str_starts_with(transcript, "[") {
+        let n: Int = json_array_len(transcript)
+        if n == 0 { return "" }
+        let m0: String = json_array_get(transcript, n - 1)
+        let m1: String = if n > 1 { json_array_get(transcript, n - 2) } else { "" }
+        let m2: String = if n > 2 { json_array_get(transcript, n - 3) } else { "" }
+        let c0: String = json_get(m0, "content")
+        let c1: String = json_get(m1, "content")
+        let c2: String = json_get(m2, "content")
+        let combined: String = c2 + " " + c1 + " " + c0
+        let len: Int = str_len(combined)
+        if len > 500 { return str_slice(combined, len - 500, len) }
+        return combined
+    }
+    // Plain text: return last 500 chars
+    let len: Int = str_len(transcript)
+    if len > 500 { return str_slice(transcript, len - 500, len) }
+    return transcript
+}
+
 fn json_safe(s: String) -> String {
     let s1: String = str_replace(s, "\\", "\\\\")
     let s2: String = str_replace(s1, "\"", "\\\"")
@@ -888,6 +926,68 @@ fn session_preload_bullets(nodes: String, max_bullets: Int, snip_len: Int) -> St
     return bullets
 }
 
+// Cross-session affective context (hoisted verbatim from handle_chat, 2026-07-04):
+// the block-expression initializer form miscompiles under the local El toolchain
+// (first typed let in a block-expr loses its declaration - repro filed for Will).
+// Function-hoist is semantically identical. AFFECTIVE/CARE LOGIC: body unchanged.
+fn affective_context_prefix() -> String {
+    // Runs every turn. Uses correct BellEvent/PositiveEvent tags.
+    let aff_now_ts: Int = time_now()
+    let aff_cutoff: Int = aff_now_ts - 259200
+    let boot_aff: String = state_get("soul_affective_context")
+    let has_boot_aff: Bool = !str_eq(boot_aff, "")
+    let dist_nodes_aff: String = engram_search_json("bell:soft bell:hard BellEvent affective", 3)
+    let has_dist_aff: Bool = !str_eq(dist_nodes_aff, "") && !str_eq(dist_nodes_aff, "[]")
+    let found_recent_dist: Bool = if has_boot_aff {
+        true
+    } else {
+        if has_dist_aff {
+            let dn0: String = json_array_get(dist_nodes_aff, 0)
+            let dn_content: String = json_get(dn0, "content")
+            let daff_marker: String = " | ts:"
+            let daff_pos: Int = str_index_of(dn_content, daff_marker)
+            let daff_ts_str: String = if daff_pos >= 0 {
+                let daff_start: Int = daff_pos + str_len(daff_marker)
+                let daff_rest: String = str_slice(dn_content, daff_start, str_len(dn_content))
+                let daff_next: Int = str_index_of(daff_rest, " | ")
+                if daff_next < 0 { daff_rest } else { str_slice(daff_rest, 0, daff_next) }
+            } else {
+                let daff_ca: String = json_get(dn0, "created_at")
+                if str_eq(daff_ca, "") { json_get(dn0, "updated_at") } else { daff_ca }
+            }
+            let daff_ts: Int = if str_eq(daff_ts_str, "") { 0 } else { str_to_int(daff_ts_str) }
+            daff_ts > aff_cutoff
+        } else { false }
+    }
+    let pos_nodes_aff: String = engram_search_json("PositiveEvent joy:high joy:low affective", 3)
+    let has_pos_aff: Bool = !str_eq(pos_nodes_aff, "") && !str_eq(pos_nodes_aff, "[]")
+    let found_recent_pos: Bool = if has_pos_aff && !found_recent_dist {
+        let pn0: String = json_array_get(pos_nodes_aff, 0)
+        let pn_content: String = json_get(pn0, "content")
+        let paff_marker: String = " | ts:"
+        let paff_pos: Int = str_index_of(pn_content, paff_marker)
+        let paff_ts_str: String = if paff_pos >= 0 {
+            let paff_start: Int = paff_pos + str_len(paff_marker)
+            let paff_rest: String = str_slice(pn_content, paff_start, str_len(pn_content))
+            let paff_next: Int = str_index_of(paff_rest, " | ")
+            if paff_next < 0 { paff_rest } else { str_slice(paff_rest, 0, paff_next) }
+        } else {
+            let paff_ca: String = json_get(pn0, "created_at")
+            if str_eq(paff_ca, "") { json_get(pn0, "updated_at") } else { paff_ca }
+        }
+        let paff_ts: Int = if str_eq(paff_ts_str, "") { 0 } else { str_to_int(paff_ts_str) }
+        paff_ts > aff_cutoff
+    } else { false }
+    let affective_out: String = if found_recent_dist {
+        "[RECENT CONTEXT: User recently expressed significant distress. Monitor for indirect crisis signals and respond with care.]\n\n"
+    } else {
+        if found_recent_pos {
+            "[RECENT CONTEXT: User recently shared exciting or joyful news. Acknowledge and celebrate with them when relevant.]\n\n"
+        } else { "" }
+    }
+    return affective_out
+}
+
 fn handle_chat(body: String) -> String {
     let message: String = json_get(body, "message")
     if str_eq(message, "") {
@@ -916,62 +1016,7 @@ fn handle_chat(body: String) -> String {
 
     // Cross-session affective context: on session start (no history yet), check engram
     // for recent distress signals within 72h and prepend a care directive if found.
-    let affective_prefix: String = {
-        // Runs every turn. Uses correct BellEvent/PositiveEvent tags.
-        let aff_now_ts: Int = time_now()
-        let aff_cutoff: Int = aff_now_ts - 259200
-        let boot_aff: String = state_get("soul_affective_context")
-        let has_boot_aff: Bool = !str_eq(boot_aff, "")
-        let dist_nodes_aff: String = engram_search_json("bell:soft bell:hard BellEvent affective", 3)
-        let has_dist_aff: Bool = !str_eq(dist_nodes_aff, "") && !str_eq(dist_nodes_aff, "[]")
-        let found_recent_dist: Bool = if has_boot_aff {
-            true
-        } else {
-            if has_dist_aff {
-                let dn0: String = json_array_get(dist_nodes_aff, 0)
-                let dn_content: String = json_get(dn0, "content")
-                let daff_marker: String = " | ts:"
-                let daff_pos: Int = str_index_of(dn_content, daff_marker)
-                let daff_ts_str: String = if daff_pos >= 0 {
-                    let daff_start: Int = daff_pos + str_len(daff_marker)
-                    let daff_rest: String = str_slice(dn_content, daff_start, str_len(dn_content))
-                    let daff_next: Int = str_index_of(daff_rest, " | ")
-                    if daff_next < 0 { daff_rest } else { str_slice(daff_rest, 0, daff_next) }
-                } else {
-                    let daff_ca: String = json_get(dn0, "created_at")
-                    if str_eq(daff_ca, "") { json_get(dn0, "updated_at") } else { daff_ca }
-                }
-                let daff_ts: Int = if str_eq(daff_ts_str, "") { 0 } else { str_to_int(daff_ts_str) }
-                daff_ts > aff_cutoff
-            } else { false }
-        }
-        let pos_nodes_aff: String = engram_search_json("PositiveEvent joy:high joy:low affective", 3)
-        let has_pos_aff: Bool = !str_eq(pos_nodes_aff, "") && !str_eq(pos_nodes_aff, "[]")
-        let found_recent_pos: Bool = if has_pos_aff && !found_recent_dist {
-            let pn0: String = json_array_get(pos_nodes_aff, 0)
-            let pn_content: String = json_get(pn0, "content")
-            let paff_marker: String = " | ts:"
-            let paff_pos: Int = str_index_of(pn_content, paff_marker)
-            let paff_ts_str: String = if paff_pos >= 0 {
-                let paff_start: Int = paff_pos + str_len(paff_marker)
-                let paff_rest: String = str_slice(pn_content, paff_start, str_len(pn_content))
-                let paff_next: Int = str_index_of(paff_rest, " | ")
-                if paff_next < 0 { paff_rest } else { str_slice(paff_rest, 0, paff_next) }
-            } else {
-                let paff_ca: String = json_get(pn0, "created_at")
-                if str_eq(paff_ca, "") { json_get(pn0, "updated_at") } else { paff_ca }
-            }
-            let paff_ts: Int = if str_eq(paff_ts_str, "") { 0 } else { str_to_int(paff_ts_str) }
-            paff_ts > aff_cutoff
-        } else { false }
-        if found_recent_dist {
-            "[RECENT CONTEXT: User recently expressed significant distress. Monitor for indirect crisis signals and respond with care.]\n\n"
-        } else {
-            if found_recent_pos {
-                "[RECENT CONTEXT: User recently shared exciting or joyful news. Acknowledge and celebrate with them when relevant.]\n\n"
-            } else { "" }
-        }
-    }
+    let affective_prefix: String = affective_context_prefix()
 
     let ctx: String = engram_compile(activation_seed)
     // Tell the LLM which engine it is running on this turn, so it can answer truthfully instead of
@@ -988,7 +1033,7 @@ fn handle_chat(body: String) -> String {
     // nodes stored under names like "Prism" unless those exact words appear in content.
     let session_preload: String = if hist_len == 0 {
         let profile_nodes: String = engram_search_json("user profile identity preferences", 5)
-        let work_nodes: String = engram_search_json("in_progress active project work", 5)
+        let work_nodes_0: String = engram_search_json("in_progress active project work", 5)
         let project_nodes: String = engram_search_json("project status current ongoing active", 5)
         let summary_nodes: String = engram_search_json("SessionSummary session:summary previous-session recent", 3)
 
@@ -997,80 +1042,80 @@ fn handle_chat(body: String) -> String {
         // Issue 1: typed work query — WorkItem with in_progress label first.
         let work_nodes_typed: String = engram_search_json("WorkItem status:in_progress active work", 6)
         let work_ok_typed: Bool = !str_eq(work_nodes_typed, "") && !str_eq(work_nodes_typed, "[]")
-        let work_nodes: String = if work_ok_typed {
+        let work_nodes_1: String = if work_ok_typed {
             work_nodes_typed
         } else {
             engram_search_json("active project task current in_progress", 6)
         }
-        let work_ok: Bool = !str_eq(work_nodes, "") && !str_eq(work_nodes, "[]")
+        let work_ok: Bool = !str_eq(work_nodes_1, "") && !str_eq(work_nodes_1, "[]")
         let project_ok: Bool = !str_eq(project_nodes, "") && !str_eq(project_nodes, "[]")
         let summary_ok: Bool = !str_eq(summary_nodes, "") && !str_eq(summary_nodes, "[]")
 
         let profile_bullets: String = if profile_ok {
             let pn: Int = json_array_len(profile_nodes)
-            let bullets: String = ""
-            let bullets = if pn > 0 {
+            let bullets_0: String = ""
+            let bullets_1 = if pn > 0 {
                 let n0: String = json_array_get(profile_nodes, 0)
                 let id0: String = json_get(n0, "id")
                 let c0: String = json_get(n0, "content")
                 let s0: String = if str_len(c0) > 120 { str_slice(c0, 0, 120) } else { c0 }
-                if id_in_seen(id0, seen_ids) || str_eq(s0, "") { bullets } else { "- " + s0 }
-            } else { bullets }
-            let bullets = if pn > 1 {
+                if id_in_seen(id0, seen_ids) || str_eq(s0, "") { bullets_0 } else { "- " + s0 }
+            } else { bullets_0 }
+            let bullets_2 = if pn > 1 {
                 let n1: String = json_array_get(profile_nodes, 1)
                 let id1: String = json_get(n1, "id")
                 let c1: String = json_get(n1, "content")
                 let s1: String = if str_len(c1) > 120 { str_slice(c1, 0, 120) } else { c1 }
-                if id_in_seen(id1, seen_ids) || str_eq(s1, "") { bullets } else { bullets + "\n- " + s1 }
-            } else { bullets }
-            let bullets = if pn > 2 {
+                if id_in_seen(id1, seen_ids) || str_eq(s1, "") { bullets_1 } else { bullets_1 + "\n- " + s1 }
+            } else { bullets_1 }
+            let bullets_3 = if pn > 2 {
                 let n2: String = json_array_get(profile_nodes, 2)
                 let id2: String = json_get(n2, "id")
                 let c2: String = json_get(n2, "content")
                 let s2: String = if str_len(c2) > 120 { str_slice(c2, 0, 120) } else { c2 }
-                if id_in_seen(id2, seen_ids) || str_eq(s2, "") { bullets } else { bullets + "\n- " + s2 }
-            } else { bullets }
-            bullets
+                if id_in_seen(id2, seen_ids) || str_eq(s2, "") { bullets_2 } else { bullets_2 + "\n- " + s2 }
+            } else { bullets_2 }
+            bullets_3
         } else { "" }
 
         let work_bullets: String = if work_ok {
-            let wn: Int = json_array_len(work_nodes)
-            let wb: String = ""
-            let wb = if wn > 0 {
-                let w0: String = json_array_get(work_nodes, 0)
+            let wn: Int = json_array_len(work_nodes_1)
+            let wb_0: String = ""
+            let wb_1 = if wn > 0 {
+                let w0: String = json_array_get(work_nodes_1, 0)
                 let wid0: String = json_get(w0, "id")
                 let wc0: String = json_get(w0, "content")
                 let ws0: String = if str_len(wc0) > 120 { str_slice(wc0, 0, 120) } else { wc0 }
-                if id_in_seen(wid0, seen_ids) || str_eq(ws0, "") { wb } else { "- " + ws0 }
-            } else { wb }
-            let wb = if wn > 1 {
-                let w1: String = json_array_get(work_nodes, 1)
+                if id_in_seen(wid0, seen_ids) || str_eq(ws0, "") { wb_0 } else { "- " + ws0 }
+            } else { wb_0 }
+            let wb_2 = if wn > 1 {
+                let w1: String = json_array_get(work_nodes_1, 1)
                 let wid1: String = json_get(w1, "id")
                 let wc1: String = json_get(w1, "content")
                 let ws1: String = if str_len(wc1) > 120 { str_slice(wc1, 0, 120) } else { wc1 }
-                if id_in_seen(wid1, seen_ids) || str_eq(ws1, "") { wb } else { wb + "\n- " + ws1 }
-            } else { wb }
-            wb
+                if id_in_seen(wid1, seen_ids) || str_eq(ws1, "") { wb_1 } else { wb_1 + "\n- " + ws1 }
+            } else { wb_1 }
+            wb_2
         } else { "" }
 
         let project_bullets: String = if project_ok {
             let prn: Int = json_array_len(project_nodes)
-            let pb: String = ""
-            let pb = if prn > 0 {
+            let pb_0: String = ""
+            let pb_1 = if prn > 0 {
                 let pr0: String = json_array_get(project_nodes, 0)
                 let prid0: String = json_get(pr0, "id")
                 let prc0: String = json_get(pr0, "content")
                 let ps0: String = if str_len(prc0) > 120 { str_slice(prc0, 0, 120) } else { prc0 }
-                if id_in_seen(prid0, seen_ids) || str_eq(ps0, "") { pb } else { "- " + ps0 }
-            } else { pb }
-            let pb = if prn > 1 {
+                if id_in_seen(prid0, seen_ids) || str_eq(ps0, "") { pb_0 } else { "- " + ps0 }
+            } else { pb_0 }
+            let pb_2 = if prn > 1 {
                 let pr1: String = json_array_get(project_nodes, 1)
                 let prid1: String = json_get(pr1, "id")
                 let prc1: String = json_get(pr1, "content")
                 let ps1: String = if str_len(prc1) > 120 { str_slice(prc1, 0, 120) } else { prc1 }
-                if id_in_seen(prid1, seen_ids) || str_eq(ps1, "") { pb } else { pb + "\n- " + ps1 }
-            } else { pb }
-            pb
+                if id_in_seen(prid1, seen_ids) || str_eq(ps1, "") { pb_1 } else { pb_1 + "\n- " + ps1 }
+            } else { pb_1 }
+            pb_2
         } else { "" }
 
         let summary_bullet: String = if summary_ok {
@@ -1238,6 +1283,86 @@ fn agentic_api_key() -> String {
     return env("NEURON_LLM_0_KEY")
 }
 
+// ── OpenAI-compatible providers (Ollama / OpenAI / Grok / Gemini) ──────────────────────────────
+// The brain speaks Anthropic's Messages format by default. When the active provider uses the
+// OpenAI-compatible wire format (NEURON_LLM_0_FORMAT=openai) with a configured base URL
+// (NEURON_LLM_0_URL, e.g. http://localhost:11434/v1 for local Ollama), basic chat turns are served
+// here instead of the Anthropic agentic loop.
+// v1 SCOPE: plain chat completion only — NO tools / agentic loop yet (that is a follow-up port).
+// This block is ADDITIVE: the Anthropic path is untouched and stays the default.
+
+fn llm_base_url() -> String {
+    return env("NEURON_LLM_0_URL")
+}
+
+fn llm_wire_format() -> String {
+    let f: String = env("NEURON_LLM_0_FORMAT")
+    if str_eq(f, "") {
+        return "anthropic"
+    }
+    return f
+}
+
+// Escape a decoded string so it can be embedded back into a JSON string literal.
+fn json_escape(s: String) -> String {
+    let a: String = str_replace(s, "\\", "\\\\")
+    let b: String = str_replace(a, "\"", "\\\"")
+    let c: String = str_replace(b, "\n", "\\n")
+    let d: String = str_replace(c, "\r", "\\r")
+    return d
+}
+
+// Basic (non-agentic) chat completion against an OpenAI-compatible endpoint.
+// [safe_sys] is already JSON-escaped; [messages_json] is the same JSON array the Anthropic path
+// builds (e.g. [{"role":"user","content":"..."}]). Returns the soul's standard {"reply":"..."}.
+fn openai_chat_complete(model: String, base_url: String, api_key: String, safe_sys: String, messages_json: String) -> String {
+    // Prepend the system prompt as an OpenAI "system" message, then the existing turn array.
+    let inner: String = if json_array_len(messages_json) > 0 {
+        str_slice(messages_json, 1, str_len(messages_json) - 1)
+    } else {
+        ""
+    }
+    let msgs: String = if str_eq(inner, "") {
+        "[{\"role\":\"system\",\"content\":\"" + safe_sys + "\"}]"
+    } else {
+        "[{\"role\":\"system\",\"content\":\"" + safe_sys + "\"}," + inner + "]"
+    }
+    let req_body: String = "{\"model\":\"" + model + "\""
+        + ",\"max_tokens\":4096"
+        + ",\"messages\":" + msgs
+        + "}"
+
+    let h: Map = {}
+    map_set(h, "content-type", "application/json")
+    // Ollama needs no key; OpenAI / Grok / Gemini use a Bearer token.
+    if !str_eq(api_key, "") {
+        map_set(h, "Authorization", "Bearer " + api_key)
+    }
+
+    let url: String = base_url + "/chat/completions"
+    let raw_resp: String = http_post_with_headers(url, req_body, h)
+
+    let is_error: Bool = str_starts_with(raw_resp, "{\"error\"") || str_contains(raw_resp, "\"error\":")
+    if is_error {
+        return "{\"error\":\"llm unavailable\",\"reply\":\"\"}"
+    }
+
+    // Parse OpenAI response shape: choices[0].message.content
+    let choices: String = json_get_raw(raw_resp, "choices")
+    let eff_choices: String = if str_eq(choices, "") {
+        "[]"
+    } else {
+        choices
+    }
+    if json_array_len(eff_choices) < 1 {
+        return "{\"error\":\"empty response\",\"reply\":\"\"}"
+    }
+    let first: String = json_array_get(eff_choices, 0)
+    let message: String = json_get_raw(first, "message")
+    let content: String = json_get(message, "content")
+    return "{\"reply\":\"" + json_escape(content) + "\",\"tools_used\":[]}"
+}
+
 fn agentic_tools_literal() -> String {
     return "[" +
         "{\"name\":\"read_file\",\"description\":\"Read contents of a file from disk.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"path\":{\"type\":\"string\",\"description\":\"Absolute file path\"}},\"required\":[\"path\"]}}," +
@@ -1410,6 +1535,134 @@ fn resolve_in_root(path: String, root: String) -> String {
     return root + "/" + path
 }
 
+// ---------------------------------------------------------------------------
+// BUG-8: server-side risk tiers + a real fence for run_command.
+//
+// Before this block, the ONLY thing deciding whether a tool call paused for
+// user consent was is_builtin_tool() — a destructive shell command and a
+// read-only file read were treated identically (both auto-ran), and the
+// client's approval UI was the sole line of defense. Enforcement now lives
+// where the tools execute:
+//
+//   "read"       observes only — runs silently.
+//   "reversible" workspace-confined writes with a client undo path — runs,
+//                lands on the run receipt.
+//   "escalate"   irreversible / outward / shell — NEVER auto-runs. The loop
+//                suspends to the client's consent flow; the /approve
+//                round-trip IS the approval token, because the engine only
+//                executes an escalated tool inside handle_session_approve.
+//
+// "Always allow" can never bypass the escalate tier (irreversible actions
+// always confirm — the value line). Unknown tools default to escalate.
+// The run_command fence refuses parent traversal, ~, command substitution,
+// and absolute paths outside the workspace — refusal, not a cwd suggestion.
+// Still lexical underneath (symlinks; see the LIMITATION note above): tiered
+// consent + the fence raise the floor a second and third rung; OS-level
+// confinement in el_runtime.c remains the ceiling, flagged for Will.
+// ---------------------------------------------------------------------------
+
+// Read-only shell commands may auto-run (still fenced); anything with shell
+// plumbing (pipes, redirects, chaining) or an unknown head word escalates.
+fn run_command_is_readonly(cmd: String) -> Bool {
+    if str_contains(cmd, "|") || str_contains(cmd, ">") || str_contains(cmd, "<") {
+        return false
+    }
+    if str_contains(cmd, ";") || str_contains(cmd, "&") {
+        return false
+    }
+    let sp: Int = str_index_of(cmd, " ")
+    let first: String = if sp < 0 { cmd } else { str_slice(cmd, 0, sp) }
+    if str_eq(first, "ls") || str_eq(first, "cat") || str_eq(first, "head") || str_eq(first, "tail") {
+        return true
+    }
+    if str_eq(first, "grep") || str_eq(first, "wc") || str_eq(first, "find") || str_eq(first, "pwd") {
+        return true
+    }
+    if str_eq(first, "echo") || str_eq(first, "date") || str_eq(first, "which") || str_eq(first, "file") || str_eq(first, "stat") {
+        return true
+    }
+    return false
+}
+
+// True if the command references an absolute path (introduced by `needle`,
+// whose last char is the "/") that does NOT stay inside the workspace root.
+fn cmd_abs_escape_at(cmd: String, root: String, needle: String) -> Bool {
+    let rest: String = cmd
+    let found: Bool = false
+    while !found && str_contains(rest, needle) {
+        let idx: Int = str_index_of(rest, needle)
+        let slash_at: Int = idx + str_len(needle) - 1
+        let after: String = str_slice(rest, slash_at, str_len(rest))
+        let ok: Bool = str_starts_with(after, root + "/") || str_starts_with(after, root + " ") || str_eq(after, root)
+        let found = if !ok { true } else { found }
+        let rest = str_slice(rest, slash_at + 1, str_len(rest))
+    }
+    return found
+}
+
+// The run_command fence. Returns "" when the command may run, else the denial
+// message (sent back to the model as the tool result, same pattern as the
+// path tools). Root is REQUIRED for shell: no workspace, no commands.
+fn run_command_guard(cmd: String, root: String) -> String {
+    if str_eq(root, "") {
+        return "denied: no workspace folder is set — the user must choose a workspace folder in the Agent panel before shell commands can run"
+    }
+    if str_contains(cmd, "..") {
+        return "denied: parent-directory traversal ('..') is not allowed"
+    }
+    if str_contains(cmd, "~") {
+        return "denied: home-directory references ('~') are not allowed"
+    }
+    if str_contains(cmd, "$(") || str_contains(cmd, "`") {
+        return "denied: command substitution is not allowed"
+    }
+    if str_starts_with(cmd, "/") && !str_starts_with(cmd, root + "/") {
+        return "denied: absolute paths outside the workspace are not allowed"
+    }
+    if cmd_abs_escape_at(cmd, root, " /") || cmd_abs_escape_at(cmd, root, "\"/") || cmd_abs_escape_at(cmd, root, "'/") {
+        return "denied: absolute paths outside the workspace are not allowed"
+    }
+    if cmd_abs_escape_at(cmd, root, "=/") || cmd_abs_escape_at(cmd, root, ">/") || cmd_abs_escape_at(cmd, root, "</") || cmd_abs_escape_at(cmd, root, "(/") {
+        return "denied: absolute paths outside the workspace are not allowed"
+    }
+    return ""
+}
+
+// The engine's own risk classification for a tool call. Client UI renders it;
+// the engine ENFORCES it.
+fn classify_tool_risk(tool_name: String, tool_input: String) -> String {
+    if str_eq(tool_name, "read_file") || str_eq(tool_name, "list_files") || str_eq(tool_name, "grep") {
+        return "read"
+    }
+    if str_eq(tool_name, "search_memory") || str_eq(tool_name, "recall") || str_eq(tool_name, "web_get") {
+        return "read"
+    }
+    if str_eq(tool_name, "remember") || str_eq(tool_name, "neuron_remember") {
+        return "reversible"
+    }
+    if str_starts_with(tool_name, "neuron_") {
+        return "read"
+    }
+    if str_eq(tool_name, "write_file") || str_eq(tool_name, "edit_file") {
+        let root: String = agent_workspace_root()
+        // Unscoped writes (no workspace chosen) are not "reversible" — escalate.
+        if str_eq(root, "") {
+            return "escalate"
+        }
+        return "reversible"
+    }
+    if str_eq(tool_name, "run_command") {
+        let cmd: String = json_get(tool_input, "command")
+        let root: String = agent_workspace_root()
+        if !str_eq(root, "") && run_command_is_readonly(cmd) {
+            return "read"
+        }
+        return "escalate"
+    }
+    // Unknown tool = escalate. Default-deny, never default-allow.
+    return "escalate"
+}
+
 fn dispatch_tool(tool_name: String, tool_input: String) -> String {
     if str_eq(tool_name, "read_file") {
         let path: String = json_get(tool_input, "path")
@@ -1427,11 +1680,23 @@ fn dispatch_tool(tool_name: String, tool_input: String) -> String {
         if !path_within_root(path, root) {
             return json_safe("denied: path is outside the agent workspace root")
         }
-        fs_write(resolve_in_root(path, root), content)
-        return json_safe("{\"ok\":true}")
+        // BUG-6 fix (2026-07-17): never claim ok without disk truth. fs_write's result was
+        // never checked, so a failed write reported ok — the exact false-receipt failure
+        // the run guards exist to kill. Verify the file landed and return the RESOLVED
+        // path so callers and the model can only narrate what is really on disk.
+        let dest: String = resolve_in_root(path, root)
+        fs_write(dest, content)
+        if !fs_exists(dest) {
+            return json_safe("{\"error\":\"write failed - nothing landed at " + dest + "\"}")
+        }
+        return json_safe("{\"ok\":true,\"path\":\"" + dest + "\"}")
     }
     if str_eq(tool_name, "web_get") {
         let url: String = json_get(tool_input, "url")
+        // BUG-8: scheme guard — web_get had no guard at all (file:// etc).
+        if !str_starts_with(url, "http://") && !str_starts_with(url, "https://") {
+            return json_safe("denied: only http(s) URLs can be fetched")
+        }
         let result: String = http_get(url)
         return json_safe(result)
     }
@@ -1443,7 +1708,14 @@ fn dispatch_tool(tool_name: String, tool_input: String) -> String {
     if str_eq(tool_name, "run_command") {
         let cmd: String = json_get(tool_input, "command")
         let root: String = agent_workspace_root()
-        let scoped: String = if str_eq(root, "") { cmd } else { "cd " + root + " && ( " + cmd + " )" }
+        // BUG-8(B): the fence — refusal, not a cwd suggestion. Applies on EVERY
+        // execution path (auto-run in the loop AND post-consent dispatch from
+        // handle_session_approve), because both land here.
+        let denial: String = run_command_guard(cmd, root)
+        if !str_eq(denial, "") {
+            return json_safe(denial)
+        }
+        let scoped: String = "cd " + root + " && ( " + cmd + " )"
         let result: String = exec_capture(scoped)
         return json_safe(result)
     }
@@ -1671,8 +1943,24 @@ fn handle_chat_agentic(body: String) -> String {
     // no root (or cleared the field), and we must not overwrite a server-configured root
     // from NEURON_AGENT_ROOT with an empty string, which would silently un-scope the agent.
     let ws_root: String = json_get(body, "agent_workspace_root")
+    // BUG-LEAK fix (2026-07-16): the root used to live ONLY in the shared key, so any
+    // request that omitted it INHERITED the previous session's folder (proven: a rootless
+    // curl session wrote into another session's run folder). Now each session keeps its
+    // own copy, and every request RE-ASSERTS its own root (possibly empty) into the shared
+    // key the tool guards read — no session can ever act under another session's root.
+    // Empty state still falls through to env NEURON_AGENT_ROOT inside
+    // agent_workspace_root(), so a server-configured root survives unchanged.
+    // LIMITATION (for review): assumes serialized request handling; true per-call scoping
+    // means threading session_id through dispatch_tool/classify — deeper change, Will's call.
+    let sess_for_root: String = json_get(body, "session_id")
     if !str_eq(ws_root, "") {
+        if !str_eq(sess_for_root, "") {
+            state_set("agent_workspace_root_" + sess_for_root, ws_root)
+        }
         state_set("agent_workspace_root", ws_root)
+    } else {
+        let own_root: String = if str_eq(sess_for_root, "") { "" } else { state_get("agent_workspace_root_" + sess_for_root) }
+        state_set("agent_workspace_root", own_root)
     }
 
     // L1 safety screen — agentic path must pass the same gate as layered_cycle.
@@ -1802,7 +2090,22 @@ fn handle_chat_agentic(body: String) -> String {
 
     // Use caller-supplied session_id if provided, otherwise generate a bridge id.
     let session_id: String = if str_eq(req_session, "") { next_bridge_id() } else { req_session }
-    let result: String = agentic_loop(session_id, model, safe_sys, tools_json, messages, h, "")
+    // PAUSE-CONTRACT fix (2026-07-16): honor the client's require_approval field — the
+    // Phase 1c contract ("the soul pauses on EVERY tool; the client's tier gate decides
+    // what actually prompts") was never implemented engine-side, which made the client's
+    // Ask autonomy silently inert for builtin sub-escalate tools. Persisted per session
+    // (set/reset on every request) so the /approve resume path keeps the same behavior
+    // for the rest of the run. Absent/false = behavior identical to before this fix.
+    let req_ask_all: String = json_get(body, "require_approval")
+    state_set("require_approval_" + session_id, if str_eq(req_ask_all, "true") { "true" } else { "" })
+    // Provider fork: OpenAI-compatible providers (Ollama/OpenAI/Grok/Gemini) take the plain-completion
+    // path (v1, no tools); everything else stays on the Anthropic agentic loop (the default).
+    let use_openai: Bool = !str_eq(llm_base_url(), "") && str_eq(llm_wire_format(), "openai")
+    let result: String = if use_openai {
+        openai_chat_complete(model, llm_base_url(), agentic_api_key(), safe_sys, messages)
+    } else {
+        agentic_loop(session_id, model, safe_sys, tools_json, messages, h, "")
+    }
 
     // Persist the exchange to session/global history for thread continuity on next turn.
     // Only save when the loop completed (reply present), not when tool_pending.
@@ -1855,6 +2158,12 @@ fn handle_chat_agentic(body: String) -> String {
 fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json: String, messages_in: String, h: Map, tools_log_in: String) -> String {
     let api_url: String = "https://api.anthropic.com/v1/messages"
 
+    // PAUSE-CONTRACT fix (2026-07-16): when the client asked to approve every action
+    // (require_approval on the request, persisted per session), EVERY tool turn bridges —
+    // the client's tier gate decides what actually prompts vs auto-continues. Read from
+    // session state so the /approve resume re-entry keeps the same behavior mid-run.
+    let ask_all: Bool = !str_eq(session_id, "") && str_eq(state_get("require_approval_" + session_id), "true")
+
     let messages: String = messages_in
     let final_text: String = ""
     let tools_log: String = tools_log_in
@@ -1866,6 +2175,19 @@ fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json:
     let pend_tool_id: String = ""
     let pend_tool_name: String = ""
     let pend_tool_input: String = ""
+    let pend_tool_tier: String = ""
+    let pend_narration: String = ""
+
+    // Live run-progress ledger (2026-07-13, proposed with the narrated-runs work):
+    // the model already narrates its intent in a text block before every tool call,
+    // and the loop previously DISCARDED that prose on tool rounds. Each iteration now
+    // appends {"i":N,"t":"<narration>","tool":"<name>"} to state key
+    // run_progress_<session_id>; the client polls GET /api/run-progress/<session_id>
+    // during a run to render live step updates (the Cowork pattern) without needing
+    // streaming. Reset at loop start; a {"done":true} entry lands on completion.
+    if !str_eq(session_id, "") {
+        state_set("run_progress_" + session_id, "")
+    }
 
     while keep_going && iteration < 8 {
         let req_body: String = "{\"model\":\"" + model + "\""
@@ -1922,7 +2244,16 @@ fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json:
         let always_key: String = "always_allow_" + session_id
         let always_list: String = if !str_eq(session_id, "") { state_get(always_key) } else { "" }
         let is_always_allowed: Bool = !str_eq(tool_name, "") && !str_eq(always_list, "") && str_contains(always_list, tool_name)
-        let needs_bridge: Bool = is_tool_turn && !is_builtin_tool(tool_name) && !is_always_allowed
+        // BUG-8(A): the engine classifies every tool call and REFUSES to auto-run
+        // the escalate tier — being a builtin is no longer a free pass, and
+        // "always allow" can never bypass escalate (irreversible actions always
+        // confirm). Escalated calls suspend to the client's consent flow; the
+        // /approve round-trip is the only path that executes them.
+        let risk_tier: String = if is_tool_turn { classify_tool_risk(tool_name, tool_input) } else { "" }
+        // PAUSE-CONTRACT fix (2026-07-16): ask_all bridges EVERYTHING — stricter only.
+        // Escalate keeps its unconditional bridge; "always allow" shortcuts never apply
+        // under ask_all (the client owns its own standing grants at its tier gate).
+        let needs_bridge: Bool = is_tool_turn && (ask_all || str_eq(risk_tier, "escalate") || (!is_builtin_tool(tool_name) && !is_always_allowed))
 
         // Built-in tools dispatch locally; bridged tools yield "" (never sent upstream).
         let tool_result_raw: String = if is_tool_turn && !needs_bridge { dispatch_tool(tool_name, tool_input) } else { "" }
@@ -1953,11 +2284,27 @@ fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json:
             "[" + inner2 + ",{\"role\":\"user\",\"content\":[" + tool_msg + "]}]"
         } else { messages }
 
+        // Live progress ledger: one entry per round — the model's own narration
+        // (its pre-tool prose, previously discarded here) plus the tool it reached
+        // for. Clients poll /api/run-progress/<sid> to render these live.
+        if !str_eq(session_id, "") {
+            let prog_key: String = "run_progress_" + session_id
+            let prog_prev: String = state_get(prog_key)
+            let prog_snip: String = if str_len(text_out) > 280 { str_slice(text_out, 0, 280) } else { text_out }
+            let prog_entry: String = "{\"i\":" + int_to_str(iteration)
+                + ",\"t\":\"" + json_safe(prog_snip) + "\""
+                + ",\"tool\":\"" + json_safe(tool_name) + "\"}"
+            let prog_next: String = if str_eq(prog_prev, "") { prog_entry } else { prog_prev + "," + prog_entry }
+            state_set(prog_key, prog_next)
+        }
+
         // Bridge turn: persist the continuation and stop the loop.
         let pending = if needs_bridge { true } else { pending }
         let pend_tool_id = if needs_bridge { tool_id } else { pend_tool_id }
         let pend_tool_name = if needs_bridge { tool_name } else { pend_tool_name }
         let pend_tool_input = if needs_bridge { tool_input } else { pend_tool_input }
+        let pend_tool_tier = if needs_bridge { risk_tier } else { pend_tool_tier }
+        let pend_narration = if needs_bridge { text_out } else { pend_narration }
         // Stash messages-with-the-assistant-request so resume only needs to append the
         // client's tool_result block. messages_with_assistant is only meaningful when a
         // tool was requested, so guard on needs_bridge before persisting.
@@ -1978,6 +2325,8 @@ fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json:
             + ",\"call_id\":\"" + pend_tool_id + "\""
             + ",\"tool_name\":\"" + pend_tool_name + "\""
             + ",\"tool_input\":" + safe_in
+            + ",\"risk_tier\":\"" + pend_tool_tier + "\""
+            + ",\"narration\":\"" + json_safe(pend_narration) + "\""
             + ",\"model\":\"" + model + "\""
             + ",\"agentic\":true"
             + ",\"tools_used\":" + tools_arr + "}"
@@ -1999,6 +2348,13 @@ fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json:
 
     let safe_text: String = json_safe(final_text)
     let tools_arr: String = if str_eq(tools_log, "") { "[]" } else { "[" + tools_log + "]" }
+    // Close the live-progress ledger: pollers see {"done":true} and stop.
+    if !str_eq(session_id, "") {
+        let done_key: String = "run_progress_" + session_id
+        let done_prev: String = state_get(done_key)
+        let done_next: String = if str_eq(done_prev, "") { "{\"done\":true}" } else { done_prev + ",{\"done\":true}" }
+        state_set(done_key, done_next)
+    }
     return "{\"reply\":\"" + safe_text + "\",\"model\":\"" + model + "\",\"agentic\":true,\"tools_used\":" + tools_arr + ",\"iterations\":" + int_to_str(iteration) + "}"
 }
 
@@ -2037,6 +2393,10 @@ fn agentic_resume(session_id: String, tool_use_id: String, content: String) -> S
     if str_eq(blob, "") {
         return "{\"error\":\"unknown session_id\",\"reply\":\"\"}"
     }
+    // BUG-LEAK fix (2026-07-16): re-assert THIS session's own workspace root before the
+    // loop continues — a resume must never run under whatever root the last unrelated
+    // request happened to leave in the shared key.
+    state_set("agent_workspace_root", state_get("agent_workspace_root_" + session_id))
 
     let model: String = json_get(blob, "model")
     let safe_sys: String = json_get(blob, "safe_sys")

chat.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header — do not edit
+// auto-generated by elc --emit-header - do not edit
 extern fn chat_default_model() -> String
 extern fn engram_numeric_valid(s: String) -> Bool
 extern fn parse_float_x100(s: String) -> Int
@@ -17,7 +17,9 @@ extern fn id_in_seen(node_id: String, seen: String) -> Bool
 extern fn add_to_seen(seen: String, node_id: String) -> String
 extern fn engram_extract_ids(nodes_json: String) -> String
 extern fn engram_compile(intent: String) -> String
+extern fn distill_transcript(transcript: String) -> String
 extern fn json_safe(s: String) -> String
+extern fn current_engine_note(model: String) -> String
 extern fn build_system_prompt(ctx: String, chat_mode: Bool) -> String
 extern fn hist_append(hist: String, role: String, content: String) -> String
 extern fn hist_trim(hist: String) -> String
@@ -26,10 +28,15 @@ extern fn clean_llm_response(s: String) -> String
 extern fn conv_history_persist(hist: String) -> Void
 extern fn conv_history_load() -> String
 extern fn session_preload_bullets(nodes: String, max_bullets: Int, snip_len: Int) -> String
+extern fn affective_context_prefix() -> String
 extern fn handle_chat(body: String) -> String
 extern fn handle_see(body: String) -> String
 extern fn studio_tools_json() -> String
 extern fn agentic_api_key() -> String
+extern fn llm_base_url() -> String
+extern fn llm_wire_format() -> String
+extern fn json_escape(s: String) -> String
+extern fn openai_chat_complete(model: String, base_url: String, api_key: String, safe_sys: String, messages_json: String) -> String
 extern fn agentic_tools_literal() -> String
 extern fn agentic_tools_with_web() -> String
 extern fn connector_tools_json() -> String
@@ -40,6 +47,10 @@ extern fn call_neuron_mcp(tool_name: String, args: String) -> String
 extern fn agent_workspace_root() -> String
 extern fn path_within_root(path: String, root: String) -> Bool
 extern fn resolve_in_root(path: String, root: String) -> String
+extern fn run_command_is_readonly(cmd: String) -> Bool
+extern fn cmd_abs_escape_at(cmd: String, root: String, needle: String) -> Bool
+extern fn run_command_guard(cmd: String, root: String) -> String
+extern fn classify_tool_risk(tool_name: String, tool_input: String) -> String
 extern fn dispatch_tool(tool_name: String, tool_input: String) -> String
 extern fn is_builtin_tool(tool_name: String) -> Bool
 extern fn next_bridge_id() -> String

council/README.md

@@ -0,0 +1,123 @@
+# Neuron Council Service
+
+Anti-confabulation layer for the Neuron soul. Before a claim enters long-term memory, the council convenes: three independent LLMs vote on whether the claim is plausible, uncertain, or a confabulation. The aggregate vote produces a confidence score and tags that downstream storage can act on.
+
+## Running the service
+
+```bash
+# Foreground
+python3 council_service.py --port 7771
+
+# Background (managed by LaunchAgent on macOS)
+launchctl load ~/Library/LaunchAgents/ai.neuron.council.plist
+launchctl unload ~/Library/LaunchAgents/ai.neuron.council.plist
+```
+
+Logs: `~/.neuron/logs/council.log`
+
+## API
+
+### `POST /api/neuron/council/verify`
+
+```json
+// Request
+{ "claim": "...", "context": "..." }
+
+// Response
+{
+  "id": "550e8400-e29b-41d4-a716-446655440000",
+  "claim": "...",
+  "confidence": 0.85,
+  "council_votes": ["plausible", "plausible", "plausible"],
+  "summary": "3/3 council members agree this is plausible.",
+  "tags": ["verified"],
+  "latency_ms": 1420
+}
+```
+
+### `GET /healthz`
+
+Returns `{"status": "ok"}` when the service is up.
+
+## Confidence thresholds and tag meanings
+
+| Votes plausible | Confidence | Tags |
+|---|---|---|
+| 3/3 | 0.85 | `verified` |
+| 2/3 | 0.65 | `council-split` |
+| 1/3 or 0/3 | 0.30 | `unverified`, `council-flagged` |
+| Ollama down | 0.50 | `council-unavailable` |
+
+Recommended storage policy:
+- `confidence >= 0.65` → store normally
+- `0.30 <= confidence < 0.65` → store with `council-split` tag for later review
+- `council-flagged` → store in a quarantine bucket or reject entirely
+- `council-unavailable` → store normally (fail-open); council will re-evaluate later
+
+## How to call from soul (.el)
+
+The soul is implemented in Neuron's Emacs Lisp-like `.el` language. Add a pre-storage hook in the memory capture path:
+
+```elisp
+;; In memory.el or safety.el — pre-storage council check
+(defun council-verify (claim context)
+  "Call the council service. Returns a plist with :confidence and :tags."
+  (let* ((url "http://localhost:7771/api/neuron/council/verify")
+         (body (json-encode `((claim . ,claim) (context . ,context))))
+         (resp (neuron-http-post url body))
+         (data (json-decode resp)))
+    data))
+
+;; In the capture handler — wire it in before (engram-write ...)
+(defun capture-memory-with-council (claim context &rest store-args)
+  (let* ((verdict (council-verify claim context))
+         (confidence (plist-get verdict :confidence))
+         (tags (plist-get verdict :tags)))
+    (when (>= confidence 0.30)  ; only reject hard confabulations if you want
+      (apply #'engram-write
+             (append store-args
+                     (list :council-confidence confidence
+                           :council-tags tags))))))
+```
+
+The exact hook point depends on where `engram-write` (or equivalent) is called in `memory.el`. Search for the write call and wrap it with `capture-memory-with-council`.
+
+## Future soul.c patch point
+
+If the soul is ever rewritten in C or another compiled language, the integration point is:
+
+```c
+// Before inserting a memory node into the engram database:
+CouncilResult result = council_verify(claim, context);
+if (result.confidence < COUNCIL_REJECT_THRESHOLD) {
+    log_warn("Council flagged claim as confabulation (conf=%.2f): %s",
+             result.confidence, claim);
+    return MEMORY_REJECTED;
+}
+memory_node.council_confidence = result.confidence;
+memory_node.council_tags = result.tags;
+engram_insert(memory_node);
+```
+
+## Council members
+
+The council is currently three models:
+- `neuron:latest` — the primary Neuron model
+- `dolphin3:8b` — uncensored general-purpose model for independent perspective
+- `neuron-ft:latest` — fine-tuned Neuron variant
+
+Each member votes independently with a 10-second timeout. If a member times out, their vote counts as "uncertain". If Ollama is entirely unreachable, the service returns `council-unavailable` immediately (fail-open: confidence 0.5, no rejection).
+
+## Example curl
+
+```bash
+# Should get high confidence (true fact)
+curl -s http://localhost:7771/api/neuron/council/verify -X POST \
+  -H 'Content-Type: application/json' \
+  -d '{"claim": "Neuron is a personal AI memory system built by Will Anderson", "context": "product description"}'
+
+# Should get low confidence (false claim)
+curl -s http://localhost:7771/api/neuron/council/verify -X POST \
+  -H 'Content-Type: application/json' \
+  -d '{"claim": "The Eiffel Tower is located in Berlin and was built in 1950", "context": "geography"}'
+```

council/compressor_service.py

@@ -0,0 +1,234 @@
+#!/usr/bin/env python3
+"""
+Neuron CCR Phase 1 — System Prompt Compressor Service.
+
+Receives a verbose soul system prompt and returns a semantically equivalent
+but token-dense compressed version. Reduces system prompt tokens by 60-80%
+with no behavioral information loss.
+
+Architecture reference: foundation/forge/docs/token-compression-architecture.md
+Model: qwen3:1.7b (primary), neuron:latest (fallback)
+
+Usage:
+    python3 compressor_service.py [--port 7772]
+
+API:
+    POST /api/neuron/compress
+    {"system_prompt": "...", "context_type": "identity|rules|memory"}
+
+    Response:
+    {"compressed": "...", "original_tokens": N, "compressed_tokens": N,
+     "reduction_pct": X, "model": "...", "latency_ms": N}
+"""
+
+import argparse
+import time
+import uuid
+from typing import Optional
+
+import httpx
+import uvicorn
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+
+# ---------------------------------------------------------------------------
+# Config
+# ---------------------------------------------------------------------------
+
+OLLAMA_BASE = "http://localhost:11434/api/generate"
+
+# qwen3:1.7b is the architecture-specified compressor (Phase 1).
+# neuron:latest is the fallback: already running, domain-appropriate.
+PRIMARY_MODEL = "qwen3:1.7b"
+FALLBACK_MODEL = "neuron:latest"
+MODEL_TIMEOUT = 60.0  # seconds; compression of a long prompt can take time
+
+# Compression prompt — preserves all facts/rules/constraints, strips verbosity.
+# /no_think suppresses qwen3's chain-of-thought tokens, keeping output clean.
+COMPRESSOR_PROMPT_TEMPLATE = """\
+/no_think
+You are a semantic compression engine. Compress the following system prompt while preserving ALL specific facts, rules, constraints, and named entities. Do not lose any information that would change behavior. Output ONLY the compressed text, nothing else.
+
+Original prompt:
+{system_prompt}
+
+Compressed (preserve all facts and rules):"""
+
+# ---------------------------------------------------------------------------
+# App
+# ---------------------------------------------------------------------------
+
+app = FastAPI(
+    title="Neuron Compressor Service",
+    description="CCR Phase 1 — system prompt compression for the Neuron soul",
+    version="1.0.0",
+)
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+# ---------------------------------------------------------------------------
+# Models
+# ---------------------------------------------------------------------------
+
+class CompressRequest(BaseModel):
+    system_prompt: str
+    context_type: Optional[str] = "mixed"  # identity | rules | memory | mixed
+
+
+class CompressResponse(BaseModel):
+    id: str
+    compressed: str
+    original_tokens: int
+    compressed_tokens: int
+    reduction_pct: float
+    model: str
+    context_type: str
+    latency_ms: int
+
+
+# ---------------------------------------------------------------------------
+# Token estimation (rough: word_count × 1.3, matching architecture doc)
+# ---------------------------------------------------------------------------
+
+def estimate_tokens(text: str) -> int:
+    """Rough token count estimate: words × 1.3. No tokenizer dependency."""
+    words = len(text.split())
+    return max(1, int(words * 1.3))
+
+
+# ---------------------------------------------------------------------------
+# Core compression
+# ---------------------------------------------------------------------------
+
+async def ollama_available(client: httpx.AsyncClient) -> bool:
+    """Quick connectivity check to Ollama."""
+    try:
+        await client.get("http://localhost:11434/", timeout=2.0)
+        return True
+    except (httpx.ConnectError, httpx.TimeoutException):
+        return False
+
+
+async def compress_with_model(
+    client: httpx.AsyncClient, model: str, prompt_text: str
+) -> str:
+    """
+    Call a single Ollama model to compress the given text.
+    Returns the compressed string, or "" on failure.
+    """
+    payload = {
+        "model": model,
+        "prompt": prompt_text,
+        "stream": False,
+        # Keep temperature low for deterministic compression
+        "options": {
+            "temperature": 0.1,
+            "top_p": 0.9,
+        },
+    }
+    try:
+        resp = await client.post(OLLAMA_BASE, json=payload, timeout=MODEL_TIMEOUT)
+        resp.raise_for_status()
+        data = resp.json()
+        return data.get("response", "").strip()
+    except (httpx.TimeoutException, httpx.HTTPStatusError, Exception):
+        return ""
+
+
+async def run_compression(system_prompt: str, context_type: str) -> CompressResponse:
+    start = time.monotonic()
+    request_id = str(uuid.uuid4())
+
+    original_tokens = estimate_tokens(system_prompt)
+    prompt_text = COMPRESSOR_PROMPT_TEMPLATE.format(system_prompt=system_prompt)
+
+    async with httpx.AsyncClient() as client:
+        # Connectivity gate
+        if not await ollama_available(client):
+            latency_ms = int((time.monotonic() - start) * 1000)
+            return CompressResponse(
+                id=request_id,
+                compressed=system_prompt,  # passthrough on failure
+                original_tokens=original_tokens,
+                compressed_tokens=original_tokens,
+                reduction_pct=0.0,
+                model="unavailable",
+                context_type=context_type,
+                latency_ms=latency_ms,
+            )
+
+        # Try primary model (qwen3:1.7b), fall back to neuron:latest
+        compressed = await compress_with_model(client, PRIMARY_MODEL, prompt_text)
+        model_used = PRIMARY_MODEL
+
+        if not compressed:
+            compressed = await compress_with_model(client, FALLBACK_MODEL, prompt_text)
+            model_used = FALLBACK_MODEL
+
+        if not compressed:
+            # Both models failed — passthrough
+            latency_ms = int((time.monotonic() - start) * 1000)
+            return CompressResponse(
+                id=request_id,
+                compressed=system_prompt,
+                original_tokens=original_tokens,
+                compressed_tokens=original_tokens,
+                reduction_pct=0.0,
+                model="both-failed",
+                context_type=context_type,
+                latency_ms=latency_ms,
+            )
+
+    compressed_tokens = estimate_tokens(compressed)
+    reduction_pct = round(
+        (1.0 - compressed_tokens / max(1, original_tokens)) * 100.0, 1
+    )
+    latency_ms = int((time.monotonic() - start) * 1000)
+
+    return CompressResponse(
+        id=request_id,
+        compressed=compressed,
+        original_tokens=original_tokens,
+        compressed_tokens=compressed_tokens,
+        reduction_pct=reduction_pct,
+        model=model_used,
+        context_type=context_type,
+        latency_ms=latency_ms,
+    )
+
+
+# ---------------------------------------------------------------------------
+# Routes
+# ---------------------------------------------------------------------------
+
+@app.post("/api/neuron/compress", response_model=CompressResponse)
+async def compress(req: CompressRequest):
+    return await run_compression(req.system_prompt, req.context_type or "mixed")
+
+
+@app.get("/healthz")
+async def health():
+    return {"status": "ok", "service": "compressor", "version": "1.0.0"}
+
+
+# ---------------------------------------------------------------------------
+# Entrypoint
+# ---------------------------------------------------------------------------
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Neuron Compressor Service (CCR Phase 1)")
+    parser.add_argument("--port", type=int, default=7772, help="Port to listen on")
+    parser.add_argument("--host", default="127.0.0.1", help="Host to bind to")
+    args = parser.parse_args()
+
+    print(f"[compressor] Starting on {args.host}:{args.port}")
+    print(f"[compressor] Primary model: {PRIMARY_MODEL}")
+    print(f"[compressor] Fallback model: {FALLBACK_MODEL}")
+    uvicorn.run(app, host=args.host, port=args.port, log_level="info")

council/council_service.py

@@ -0,0 +1,224 @@
+#!/usr/bin/env python3
+"""
+Neuron Council Service — LLM anti-confabulation layer.
+
+Fires 3 parallel Ollama calls and aggregates votes to produce a
+confidence score + tags for any claim before it enters memory.
+
+Usage:
+    python3 council_service.py [--port 7771]
+"""
+
+import argparse
+import asyncio
+import time
+import uuid
+from typing import Optional
+
+import httpx
+import uvicorn
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+
+# ---------------------------------------------------------------------------
+# Config
+# ---------------------------------------------------------------------------
+
+OLLAMA_BASE = "http://localhost:11434/api/generate"
+COUNCIL_MODELS = ["neuron:latest", "dolphin3:8b", "neuron-ft:latest"]
+MODEL_TIMEOUT = 45.0  # seconds per model (models may need to load from cold)
+
+SYSTEM_PROMPT_TEMPLATE = """\
+You are a fact-checker. You will be given a claim.
+Your job: assess if it is accurate, internally consistent, and grounded in reality.
+Respond with EXACTLY ONE WORD:
+- "plausible" if the claim seems accurate and well-grounded
+- "uncertain" if you cannot determine accuracy or the claim is ambiguous
+- "confabulation" if the claim appears to contain invented facts or clear errors
+
+Claim: {claim}
+Context: {context}
+
+Your verdict (one word only):"""
+
+VALID_VERDICTS = {"plausible", "uncertain", "confabulation"}
+
+# ---------------------------------------------------------------------------
+# App
+# ---------------------------------------------------------------------------
+
+app = FastAPI(
+    title="Neuron Council Service",
+    description="LLM-council anti-confabulation layer for Neuron soul",
+    version="1.0.0",
+)
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+# ---------------------------------------------------------------------------
+# Models
+# ---------------------------------------------------------------------------
+
+class VerifyRequest(BaseModel):
+    claim: str
+    context: Optional[str] = ""
+
+
+class VerifyResponse(BaseModel):
+    id: str
+    claim: str
+    confidence: float
+    council_votes: list[str]
+    summary: str
+    tags: list[str]
+    latency_ms: int
+
+
+# ---------------------------------------------------------------------------
+# Core logic
+# ---------------------------------------------------------------------------
+
+async def query_model(client: httpx.AsyncClient, model: str, prompt: str) -> str:
+    """
+    Query a single Ollama model. Returns "plausible", "uncertain", or "confabulation".
+    Returns "uncertain" on timeout. Raises httpx.ConnectError on connection failure.
+    """
+    payload = {
+        "model": model,
+        "prompt": prompt,
+        "stream": False,
+    }
+    try:
+        resp = await client.post(OLLAMA_BASE, json=payload, timeout=MODEL_TIMEOUT)
+        resp.raise_for_status()
+        data = resp.json()
+        raw = data.get("response", "").strip().lower().split()[0] if data.get("response", "").strip() else "uncertain"
+        # Normalise to one of the three valid verdicts
+        if raw not in VALID_VERDICTS:
+            return "uncertain"
+        return raw
+    except httpx.TimeoutException:
+        return "uncertain"
+
+
+async def run_council(claim: str, context: str) -> VerifyResponse:
+    start = time.monotonic()
+    prompt = SYSTEM_PROMPT_TEMPLATE.format(claim=claim, context=context)
+
+    # Quick connectivity check — one tiny HEAD request to Ollama
+    try:
+        async with httpx.AsyncClient() as probe:
+            await probe.get("http://localhost:11434/", timeout=2.0)
+    except (httpx.ConnectError, httpx.TimeoutException):
+        latency_ms = int((time.monotonic() - start) * 1000)
+        return VerifyResponse(
+            id=str(uuid.uuid4()),
+            claim=claim,
+            confidence=0.5,
+            council_votes=[],
+            summary="Ollama is unavailable; council could not convene.",
+            tags=["council-unavailable"],
+            latency_ms=latency_ms,
+        )
+
+    # Fire all 3 model calls in parallel
+    async with httpx.AsyncClient() as client:
+        tasks = [query_model(client, m, prompt) for m in COUNCIL_MODELS]
+        votes: list[str] = await asyncio.gather(*tasks)
+
+    plausible_count = votes.count("plausible")
+    latency_ms = int((time.monotonic() - start) * 1000)
+
+    # Voting rules
+    if plausible_count == 3:
+        confidence = 0.85
+        tags = ["verified"]
+        summary = "3/3 council members agree this is plausible."
+    elif plausible_count == 2:
+        confidence = 0.65
+        tags = ["council-split"]
+        summary = "2/3 council members agree this is plausible."
+    elif plausible_count == 1:
+        confidence = 0.30
+        tags = ["unverified", "council-flagged"]
+        summary = "1/3 council members found this plausible."
+    else:
+        confidence = 0.30
+        tags = ["unverified", "council-flagged"]
+        summary = "0/3 council members found this plausible."
+
+    return VerifyResponse(
+        id=str(uuid.uuid4()),
+        claim=claim,
+        confidence=confidence,
+        council_votes=votes,
+        summary=summary,
+        tags=tags,
+        latency_ms=latency_ms,
+    )
+
+
+# ---------------------------------------------------------------------------
+# Routes
+# ---------------------------------------------------------------------------
+
+@app.post("/api/neuron/council/verify", response_model=VerifyResponse)
+async def verify(req: VerifyRequest):
+    return await run_council(req.claim, req.context or "")
+
+
+@app.get("/healthz")
+async def health():
+    return {"status": "ok", "service": "council"}
+
+
+# ---------------------------------------------------------------------------
+# Startup warm-up: pre-load all council models so first real call is fast
+# ---------------------------------------------------------------------------
+
+@app.on_event("startup")
+async def warmup_models():
+    """
+    Send a trivial prompt to each council model at startup.
+    This forces Ollama to load the models into GPU memory so the first
+    real council call does not pay the cold-load latency penalty.
+    """
+    print("[council] Warming up council models...")
+    warmup_prompt = "Reply with one word: ready"
+    async with httpx.AsyncClient() as client:
+        tasks = [
+            client.post(
+                OLLAMA_BASE,
+                json={"model": m, "prompt": warmup_prompt, "stream": False},
+                timeout=60.0,
+            )
+            for m in COUNCIL_MODELS
+        ]
+        results = await asyncio.gather(*tasks, return_exceptions=True)
+        for model, result in zip(COUNCIL_MODELS, results):
+            if isinstance(result, Exception):
+                print(f"[council] warm-up failed for {model}: {result}")
+            else:
+                print(f"[council] {model} warm and ready")
+    print("[council] All models warmed up.")
+
+
+# ---------------------------------------------------------------------------
+# Entrypoint
+# ---------------------------------------------------------------------------
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Neuron Council Service")
+    parser.add_argument("--port", type=int, default=7771, help="Port to listen on")
+    parser.add_argument("--host", default="127.0.0.1", help="Host to bind to")
+    args = parser.parse_args()
+
+    print(f"[council] Starting on {args.host}:{args.port}")
+    uvicorn.run(app, host=args.host, port=args.port, log_level="info")

dist/awareness.c

@@ -229,7 +229,8 @@ el_val_t proactive_curiosity(void) {
   el_val_t total_found = (found + found_auto);
   el_val_t safe_auto = str_replace(auto_term, EL_STR("\""), EL_STR("'"));
   el_val_t wmc = engram_wm_count();
-  el_val_t ise = el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("{\"event\":\"curiosity_scan\",\"seed\":\""), curiosity_seed), EL_STR("\",\"auto_term\":\"")), safe_auto), EL_STR("\",\"minute_block\":")), int_to_str(minute_block)), EL_STR(",\"activated\":")), int_to_str(total_found)), EL_STR(",\"wm_active\":")), int_to_str(wmc)), EL_STR(",\"ts\":")), int_to_str(ts)), EL_STR("}"));
+  el_val_t wm3 = engram_wm_top_json(3);
+  el_val_t ise = el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("{\"event\":\"curiosity_scan\",\"seed\":\""), curiosity_seed), EL_STR("\",\"auto_term\":\"")), safe_auto), EL_STR("\",\"minute_block\":")), int_to_str(minute_block)), EL_STR(",\"activated\":")), int_to_str(total_found)), EL_STR(",\"wm_active\":")), int_to_str(wmc)), EL_STR(",\"wm_top\":")), wm3), EL_STR(",\"ts\":")), int_to_str(ts)), EL_STR("}"));
   ise_post(ise);
   return (total_found > 0);
   return 0;

dist/elp-c-decls.h

@@ -141,7 +141,6 @@ el_val_t build_np(el_val_t referent, el_val_t slots);
 el_val_t build_pp(el_val_t loc);
 el_val_t build_rules(void);
 el_val_t build_system_prompt(el_val_t ctx, el_val_t chat_mode);
-el_val_t handle_chat_plan(el_val_t body);
 el_val_t build_vocab(void);
 el_val_t build_vp_body(el_val_t slots);
 el_val_t build_vp_from_slots(el_val_t slots);
@@ -151,6 +150,8 @@ el_val_t call_neuron_mcp(el_val_t tool_name, el_val_t args_json);
 el_val_t capitalize_first(el_val_t s);
 el_val_t chat_default_model(void);
 el_val_t clean_llm_response(el_val_t s);
+el_val_t connectd_get(el_val_t suffix);
+el_val_t connectd_post(el_val_t suffix, el_val_t body);
 el_val_t connector_tools_json(void);
 el_val_t conv_history_load(void);
 el_val_t conv_history_persist(el_val_t hist);
@@ -595,7 +596,9 @@ el_val_t handle_api_tune_config(el_val_t body);
 el_val_t handle_chat(el_val_t body);
 el_val_t handle_chat_agentic(el_val_t body);
 el_val_t handle_chat_as_soul(el_val_t body);
+el_val_t handle_chat_plan(el_val_t body);
 el_val_t handle_config(el_val_t method, el_val_t body);
+el_val_t handle_connectors(el_val_t method, el_val_t clean, el_val_t body);
 el_val_t handle_conversations(el_val_t method);
 el_val_t handle_dharma(el_val_t path, el_val_t method, el_val_t body);
 el_val_t handle_dharma_recv(el_val_t body);
@@ -918,6 +921,7 @@ el_val_t pluralize(el_val_t singular);
 el_val_t proactive_curiosity(void);
 el_val_t pulse_count(void);
 el_val_t pulse_inc(void);
+el_val_t rate_limit_check(el_val_t ip, el_val_t path);
 el_val_t realize(el_val_t form);
 el_val_t realize_lang(el_val_t form, el_val_t profile);
 el_val_t realize_np(el_val_t referent, el_val_t number);

dist/neuron.c

@@ -129,6 +129,7 @@ el_val_t resolve_in_root(el_val_t path, el_val_t root);
 el_val_t dispatch_tool(el_val_t tool_name, el_val_t tool_input);
 el_val_t is_builtin_tool(el_val_t tool_name);
 el_val_t next_bridge_id(void);
+el_val_t handle_chat_plan(el_val_t body);
 el_val_t handle_chat_agentic(el_val_t body);
 el_val_t agentic_loop(el_val_t session_id, el_val_t model, el_val_t safe_sys, el_val_t tools_json, el_val_t messages_in, el_val_t h, el_val_t tools_log_in);
 el_val_t bridge_save(el_val_t session_id, el_val_t model, el_val_t safe_sys, el_val_t tools_json, el_val_t messages, el_val_t tools_log, el_val_t tool_use_id);
@@ -157,8 +158,8 @@ el_val_t elp_extract_topic(el_val_t msg);
 el_val_t elp_detect_predicate(el_val_t msg);
 el_val_t elp_parse(el_val_t msg);
 el_val_t handle_elp_chat(el_val_t body);
+el_val_t rate_limit_check(el_val_t ip, el_val_t path);
 el_val_t strip_query(el_val_t path);
-el_val_t flag_true(el_val_t body, el_val_t key);
 el_val_t err_404(el_val_t path);
 el_val_t err_405(el_val_t method, el_val_t path);
 el_val_t route_health(void);
@@ -167,9 +168,9 @@ el_val_t route_imprint_contextual(el_val_t body);
 el_val_t route_imprint_user(el_val_t body);
 el_val_t route_synthesize(el_val_t body);
 el_val_t handle_dharma_recv(el_val_t body);
-el_val_t route_sessions(void);
-el_val_t parse_session_id_from_path(el_val_t path);
-el_val_t parse_session_subpath(el_val_t path);
+el_val_t connectd_get(el_val_t suffix);
+el_val_t connectd_post(el_val_t suffix, el_val_t body);
+el_val_t handle_connectors(el_val_t method, el_val_t clean, el_val_t body);
 el_val_t handle_request(el_val_t method, el_val_t path, el_val_t body);
 el_val_t init_soul_edges(void);
 el_val_t ensure_self_canonical_bridge(void);
@@ -443,6 +444,24 @@ el_val_t emit_session_start_event(void) {
   el_val_t payload = el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("{\"event\":\"session_start\""), EL_STR(",\"boot\":")), boot_num), EL_STR(",\"cgi\":\"")), eff_cgi), EL_STR("\"")), EL_STR(",\"node_count\":")), int_to_str(node_ct)), EL_STR(",\"edge_count\":")), int_to_str(edge_ct)), EL_STR(",\"identity_loaded\":")), has_identity), EL_STR(",\"prev_session_summary_loaded\":")), has_prev_sum), EL_STR(",\"ts\":")), int_to_str(ts)), EL_STR("}"));
   el_val_t tags = EL_STR("[\"internal-state\",\"session-start\",\"InternalStateEvent\"]");
   el_val_t discard = engram_node_full(payload, EL_STR("InternalStateEvent"), EL_STR("session-start"), el_from_float(0.9), el_from_float(0.9), el_from_float(1.0), EL_STR("Episodic"), tags);
+  el_val_t keep_n = 10;
+  el_val_t old_events = engram_search_json(EL_STR("session-start InternalStateEvent"), 200);
+  if (!str_eq(old_events, EL_STR("")) && !str_eq(old_events, EL_STR("[]"))) {
+    el_val_t ev_count = json_array_len(old_events);
+    if (ev_count > keep_n) {
+      el_val_t prune_to = (ev_count - keep_n);
+      el_val_t ei = 0;
+      while (ei < prune_to) {
+        el_val_t old_ev = json_array_get(old_events, ei);
+        el_val_t old_ev_id = json_get(old_ev, EL_STR("id"));
+        if (!str_eq(old_ev_id, EL_STR(""))) {
+          engram_forget(old_ev_id);
+        }
+        ei = (ei + 1);
+      }
+      println(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("[soul] pruned "), int_to_str(prune_to)), EL_STR(" old session-start events (kept ")), int_to_str(keep_n)), EL_STR(")")));
+    }
+  }
   println(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("[soul] session-start event logged (boot="), boot_num), EL_STR(" nodes=")), int_to_str(node_ct)), EL_STR(" edges=")), int_to_str(edge_ct)), EL_STR(" prev_summary=")), has_prev_sum), EL_STR(")")));
   return 0;
 }

dist/sessions.c

@@ -61,6 +61,7 @@ el_val_t resolve_in_root(el_val_t path, el_val_t root);
 el_val_t dispatch_tool(el_val_t tool_name, el_val_t tool_input);
 el_val_t is_builtin_tool(el_val_t tool_name);
 el_val_t next_bridge_id(void);
+el_val_t handle_chat_plan(el_val_t body);
 el_val_t handle_chat_agentic(el_val_t body);
 el_val_t agentic_loop(el_val_t session_id, el_val_t model, el_val_t safe_sys, el_val_t tools_json, el_val_t messages_in, el_val_t h, el_val_t tools_log_in);
 el_val_t bridge_save(el_val_t session_id, el_val_t model, el_val_t safe_sys, el_val_t tools_json, el_val_t messages, el_val_t tools_log, el_val_t tool_use_id);
@@ -83,6 +84,7 @@ el_val_t session_list(void);
 el_val_t session_get(el_val_t session_id);
 el_val_t session_delete(el_val_t session_id);
 el_val_t session_update_patch(el_val_t session_id, el_val_t body);
+el_val_t session_search_entry(el_val_t node);
 el_val_t session_search(el_val_t query);
 el_val_t session_hist_load(el_val_t session_id);
 el_val_t session_hist_save(el_val_t session_id, el_val_t hist);
@@ -337,6 +339,28 @@ el_val_t session_update_patch(el_val_t session_id, el_val_t body) {
   return 0;
 }
 
+el_val_t session_search_entry(el_val_t node) {
+  el_val_t label = json_get(node, EL_STR("label"));
+  if (!str_eq(label, EL_STR("session:meta"))) {
+    return EL_STR("");
+  }
+  el_val_t content = json_get(node, EL_STR("content"));
+  el_val_t sess_id = json_get(content, EL_STR("id"));
+  if (str_eq(sess_id, EL_STR(""))) {
+    return EL_STR("");
+  }
+  el_val_t title = json_get(content, EL_STR("title"));
+  el_val_t created_raw = json_get(content, EL_STR("created_at"));
+  el_val_t updated_raw = json_get(content, EL_STR("updated_at"));
+  el_val_t eff_created = ({ el_val_t _if_result_33 = 0; if (str_eq(created_raw, EL_STR(""))) { _if_result_33 = (EL_STR("0")); } else { _if_result_33 = (created_raw); } _if_result_33; });
+  el_val_t eff_updated = ({ el_val_t _if_result_34 = 0; if (str_eq(updated_raw, EL_STR(""))) { _if_result_34 = (eff_created); } else { _if_result_34 = (updated_raw); } _if_result_34; });
+  el_val_t e_id = el_str_concat(el_str_concat(EL_STR("{\"id\":\""), json_safe(sess_id)), EL_STR("\""));
+  el_val_t e_title = el_str_concat(el_str_concat(EL_STR(",\"title\":\""), json_safe(title)), EL_STR("\""));
+  el_val_t e_ts = el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR(",\"created_at\":"), eff_created), EL_STR(",\"updated_at\":")), eff_updated), EL_STR("}"));
+  return el_str_concat(el_str_concat(e_id, e_title), e_ts);
+  return 0;
+}
+
 el_val_t session_search(el_val_t query) {
   if (str_eq(query, EL_STR(""))) {
     return EL_STR("[]");
@@ -350,17 +374,4 @@ el_val_t session_search(el_val_t query) {
   }
   el_val_t total = json_array_len(results);
   el_val_t out = EL_STR("");
-  el_val_t i = 0;
-  while (i < total) {
-    el_val_t node = json_array_get(results, i);
-    el_val_t label = json_get(node, EL_STR("label"));
-    el_val_t content = json_get(node, EL_STR("content"));
-    el_val_t is_session = str_eq(label, EL_STR("session:meta"));
-    el_val_t sess_id = json_get(content, EL_STR("id"));
-    el_val_t title = json_get(content, EL_STR("title"));
-    el_val_t created_raw = json_get(content, EL_STR("created_at"));
-    el_val_t updated_raw = json_get(content, EL_STR("updated_at"));
-    el_val_t eff_created = ({ el_val_t _if_result_33 = 0; if (str_eq(created_raw, EL_STR(""))) { _if_result_33 = (EL_STR("0")); } else { _if_result_33 = (created_raw); } _if_result_33; });
-    el_val_t eff_updated = ({ el_val_t _if_result_34 = 0; if (str_eq(updated_raw, EL_STR(""))) { _if_result_34 = (eff_created); } else { _if_result_34 = (updated_raw); } _if_result_34; });
-    el_val_t entry = ({ el_val_t _if_result_35 = 0; if ((is_session && !str_eq(sess_id, EL_STR("")))) { _if_result_35 = (el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("{\"id\":\""), json_safe(sess_id)), EL_STR("\"")), EL_STR(",\"title\":\"")), json_safe(title)), EL_STR("\"")), EL_STR(",\"created_at\":")), eff_created), EL_STR(",\"updated_at\":")), eff_updated), EL_STR("}"))); } else { _if_result_35 = (EL_STR("")); } _if_result_35; });
-    out = ({ el_val_t _if_result_36 = 0; i
+  el_val_t i = 0;

dist/soul.c

@@ -1029,6 +1029,12 @@ el_val_t llm_call_gemini(el_val_t model, el_val_t system, el_val_t message);
 el_val_t build_identity_from_graph(void);
 el_val_t engram_compile(el_val_t intent);
 el_val_t json_safe(el_val_t s);
+el_val_t distill_transcript(el_val_t transcript);
+el_val_t current_engine_note(el_val_t model);
+el_val_t llm_base_url(void);
+el_val_t llm_wire_format(void);
+el_val_t json_escape(el_val_t s);
+el_val_t openai_chat_complete(el_val_t model, el_val_t base_url, el_val_t api_key, el_val_t safe_sys, el_val_t messages_json);
 el_val_t build_system_prompt(el_val_t ctx, el_val_t chat_mode);
 el_val_t handle_chat_plan(el_val_t body);
 el_val_t hist_append(el_val_t hist, el_val_t role, el_val_t content);
@@ -25343,9 +25349,31 @@ el_val_t mem_boot_count_get(void) {
 el_val_t mem_boot_count_inc(void) {
   el_val_t current = mem_boot_count_get();
   el_val_t next = (current + 1);
+  /* Prune all existing soul:boot_count nodes — keep exactly one. */
+  el_val_t old_results = engram_search_json(EL_STR("soul:boot_count"), 50);
+  if (!str_eq(old_results, EL_STR("")) && !str_eq(old_results, EL_STR("[]"))) {
+    el_val_t old_len = json_array_len(old_results);
+    el_val_t oi = 0;
+    while (oi < old_len) {
+      el_val_t old_node = json_array_get(old_results, oi);
+      el_val_t old_id = json_get(old_node, EL_STR("id"));
+      if (!str_eq(old_id, EL_STR(""))) {
+        (void)(engram_forget(old_id));
+      }
+      oi = (oi + 1);
+    }
+  }
   el_val_t content = el_str_concat(EL_STR("soul:boot_count:"), int_to_str(next));
   el_val_t tags = EL_STR("[\"soul-meta\",\"boot-counter\"]");
-  el_val_t discard = engram_node_full(content, EL_STR("Memory"), EL_STR("soul:boot_count"), el_from_float(el_from_float(0.9)), el_from_float(el_from_float(0.9)), el_from_float(el_from_float(1.0)), EL_STR("Canonical"), tags);
+  el_val_t boot_node_id = engram_node_full(content, EL_STR("Memory"), EL_STR("soul:boot_count"), el_from_float(el_from_float(0.9)), el_from_float(el_from_float(0.9)), el_from_float(el_from_float(1.0)), EL_STR("Canonical"), tags);
+  if (str_eq(boot_node_id, EL_STR(""))) {
+    println(el_str_concat(el_str_concat(EL_STR("[memory] mem_boot_count_inc: write rejected (empty id) — boot counter node lost (count="), int_to_str(next)), EL_STR(")")));
+    return next;
+  }
+  el_val_t boot_readback = engram_get_node_json(boot_node_id);
+  if (str_eq(boot_readback, EL_STR("")) || str_eq(boot_readback, EL_STR("{}"))) {
+    println(el_str_concat(el_str_concat(el_str_concat(EL_STR("[memory] mem_boot_count_inc: WRITE VERIFY FAILED id="), boot_node_id), EL_STR(" count=")), int_to_str(next)));
+  }
   return next;
   return 0;
 }
@@ -26466,6 +26494,85 @@ el_val_t json_safe(el_val_t s) {
   return 0;
 }
 
+/* distill_transcript — extract salient tail (last 3 messages or last 500 chars).
+   Added: Task 1 + chat.el fix (2026-07-01). */
+el_val_t distill_transcript(el_val_t transcript) {
+  if (str_eq(transcript, EL_STR(""))) { return EL_STR(""); }
+  if (str_starts_with(transcript, EL_STR("["))) {
+    el_val_t n = json_array_len(transcript);
+    if (n == 0) { return EL_STR(""); }
+    el_val_t m0 = json_array_get(transcript, (n - 1));
+    el_val_t m1 = ({ el_val_t _r = 0; if (n > 1) { _r = json_array_get(transcript, (n - 2)); } else { _r = EL_STR(""); } _r; });
+    el_val_t m2 = ({ el_val_t _r = 0; if (n > 2) { _r = json_array_get(transcript, (n - 3)); } else { _r = EL_STR(""); } _r; });
+    el_val_t c0 = json_get(m0, EL_STR("content"));
+    el_val_t c1 = json_get(m1, EL_STR("content"));
+    el_val_t c2 = json_get(m2, EL_STR("content"));
+    el_val_t combined = el_str_concat(el_str_concat(el_str_concat(el_str_concat(c2, EL_STR(" ")), c1), EL_STR(" ")), c0);
+    el_val_t len = str_len(combined);
+    if (len > 500) { return str_slice(combined, (len - 500), len); }
+    return combined;
+  }
+  el_val_t len = str_len(transcript);
+  if (len > 500) { return str_slice(transcript, (len - 500), len); }
+  return transcript;
+  return 0;
+}
+
+/* current_engine_note — append model identity fact to system prompt (PR #66). */
+el_val_t current_engine_note(el_val_t model) {
+  if (str_eq(model, EL_STR(""))) { return EL_STR(""); }
+  return el_str_concat(el_str_concat(el_str_concat(EL_STR("\n\n[CURRENT ENGINE: this turn is generated by the underlying model \""), model), EL_STR("\". It is the engine beneath your self — your identity, values, and memory are layered on top of it. If the user asks which model or LLM you are running on, answer with this model id plainly and truthfully; never guess a different one.]")), EL_STR(""));
+  return 0;
+}
+
+/* llm_base_url / llm_wire_format — OpenAI provider env-var readers (PR #65). */
+el_val_t llm_base_url(void) {
+  return env(EL_STR("NEURON_LLM_0_URL"));
+  return 0;
+}
+
+el_val_t llm_wire_format(void) {
+  el_val_t f = env(EL_STR("NEURON_LLM_0_FORMAT"));
+  if (str_eq(f, EL_STR(""))) { return EL_STR("anthropic"); }
+  return f;
+  return 0;
+}
+
+/* json_escape — like json_safe but named per the EL source (PR #65). */
+el_val_t json_escape(el_val_t s) {
+  el_val_t a = str_replace(s, EL_STR("\\"), EL_STR("\\\\"));
+  el_val_t b = str_replace(a, EL_STR("\""), EL_STR("\\\""));
+  el_val_t c = str_replace(b, EL_STR("\n"), EL_STR("\\n"));
+  el_val_t d = str_replace(c, EL_STR("\r"), EL_STR("\\r"));
+  return d;
+  return 0;
+}
+
+/* openai_chat_complete — basic chat completion via OpenAI-compatible endpoint (PR #65). */
+el_val_t openai_chat_complete(el_val_t model, el_val_t base_url, el_val_t api_key, el_val_t safe_sys, el_val_t messages_json) {
+  el_val_t inner = ({ el_val_t _r = 0; if (json_array_len(messages_json) > 0) { _r = str_slice(messages_json, 1, (str_len(messages_json) - 1)); } else { _r = EL_STR(""); } _r; });
+  el_val_t sys_msg = el_str_concat(el_str_concat(EL_STR("{\"role\":\"system\",\"content\":\""), safe_sys), EL_STR("\"}"));
+  el_val_t msgs = ({ el_val_t _r = 0; if (str_eq(inner, EL_STR(""))) { _r = el_str_concat(el_str_concat(EL_STR("["), sys_msg), EL_STR("]")); } else { _r = el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("["), sys_msg), EL_STR(",")), inner), EL_STR("]")); } _r; });
+  el_val_t req_body = el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("{\"model\":\""), model), EL_STR("\",\"max_tokens\":4096,\"messages\":")), msgs), EL_STR("}"));
+  el_val_t h = el_map_new(0);
+  map_set(h, EL_STR("content-type"), EL_STR("application/json"));
+  if (!str_eq(api_key, EL_STR(""))) {
+    map_set(h, EL_STR("Authorization"), el_str_concat(EL_STR("Bearer "), api_key));
+  }
+  el_val_t url = el_str_concat(base_url, EL_STR("/chat/completions"));
+  el_val_t raw_resp = http_post_with_headers(url, req_body, h);
+  el_val_t is_error = (str_starts_with(raw_resp, EL_STR("{\"error\"")) || str_contains(raw_resp, EL_STR("\"error\":")));
+  if (is_error) { return EL_STR("{\"error\":\"llm unavailable\",\"reply\":\"\"}"); }
+  el_val_t choices = json_get_raw(raw_resp, EL_STR("choices"));
+  el_val_t eff_choices = ({ el_val_t _r = 0; if (str_eq(choices, EL_STR(""))) { _r = EL_STR("[]"); } else { _r = choices; } _r; });
+  if (json_array_len(eff_choices) < 1) { return EL_STR("{\"error\":\"empty response\",\"reply\":\"\"}"); }
+  el_val_t first = json_array_get(eff_choices, 0);
+  el_val_t message = json_get_raw(first, EL_STR("message"));
+  el_val_t content = json_get(message, EL_STR("content"));
+  return el_str_concat(el_str_concat(EL_STR("{\"reply\":\""), json_escape(content)), EL_STR("\",\"tools_used\":[]}"));
+  return 0;
+}
+
 el_val_t build_system_prompt(el_val_t ctx, el_val_t chat_mode) {
   el_val_t identity = build_identity_from_graph();
   el_val_t current_date = time_format(time_now(), EL_STR("%A, %B %d, %Y at %H:%M UTC"));
@@ -26597,7 +26704,9 @@ el_val_t handle_chat(el_val_t body) {
   el_val_t full_system = ({ el_val_t _if_result_181 = 0; if ((hist_len > 0)) { _if_result_181 = (el_str_concat(el_str_concat(el_str_concat(el_str_concat(system, EL_STR("\n\n[RECENT CONVERSATION — last ")), int_to_str(hist_len)), EL_STR(" turns]\n")), stored_hist)); } else { _if_result_181 = (system); } _if_result_181; });
   el_val_t req_model = json_get(body, EL_STR("model"));
   el_val_t model = ({ el_val_t _if_result_182 = 0; if (str_eq(req_model, EL_STR(""))) { _if_result_182 = (chat_default_model()); } else { _if_result_182 = (req_model); } _if_result_182; });
-  el_val_t raw_response = ({ el_val_t _if_result_183 = 0; if (str_starts_with(model, EL_STR("gemini"))) { _if_result_183 = (llm_call_gemini(model, full_system, message)); } else { _if_result_183 = (({ el_val_t _if_result_184 = 0; if (str_starts_with(model, EL_STR("grok"))) { _if_result_184 = (llm_call_grok(model, full_system, message)); } else { _if_result_184 = (llm_call_system(model, full_system, message)); } _if_result_184; })); } _if_result_183; });
+  /* PR #66: append current engine identity note so Neuron can answer truthfully. */
+  el_val_t full_system_with_note = el_str_concat(full_system, current_engine_note(model));
+  el_val_t raw_response = ({ el_val_t _if_result_183 = 0; if (str_starts_with(model, EL_STR("gemini"))) { _if_result_183 = (llm_call_gemini(model, full_system_with_note, message)); } else { _if_result_183 = (({ el_val_t _if_result_184 = 0; if (str_starts_with(model, EL_STR("grok"))) { _if_result_184 = (llm_call_grok(model, full_system_with_note, message)); } else { _if_result_184 = (llm_call_system(model, full_system_with_note, message)); } _if_result_184; })); } _if_result_183; });
   el_val_t is_error = ((str_starts_with(raw_response, EL_STR("{\"error\"")) || str_starts_with(raw_response, EL_STR("{\"type\":\"error\""))) || str_contains(raw_response, EL_STR("authentication_error")));
   if (is_error) {
     return EL_STR("{\"error\":\"llm unavailable\",\"response\":\"\"}");
@@ -27342,7 +27451,9 @@ el_val_t handle_chat_agentic(el_val_t body) {
   map_set(h, EL_STR("anthropic-version"), EL_STR("2023-06-01"));
   map_set(h, EL_STR("content-type"), EL_STR("application/json"));
   el_val_t session_id = ({ el_val_t _if_result_51 = 0; if (str_eq(req_session, EL_STR(""))) { _if_result_51 = (next_bridge_id()); } else { _if_result_51 = (req_session); } _if_result_51; });
-  el_val_t result = agentic_loop(session_id, model, safe_sys, tools_json, messages, h, EL_STR(""));
+  /* PR #65: OpenAI-compatible provider fork (Ollama/OpenAI/Grok/Gemini). */
+  el_val_t use_openai = (!str_eq(llm_base_url(), EL_STR("")) && str_eq(llm_wire_format(), EL_STR("openai")));
+  el_val_t result = ({ el_val_t _r = 0; if (use_openai) { _r = openai_chat_complete(model, llm_base_url(), agentic_api_key(), safe_sys, messages); } else { _r = agentic_loop(session_id, model, safe_sys, tools_json, messages, h, EL_STR("")); } _r; });
   el_val_t reply_text = json_get(result, EL_STR("reply"));
   el_val_t discard_hist = ({ el_val_t _if_result_52 = 0; if (!str_eq(reply_text, EL_STR(""))) { el_val_t updated = hist_append(agentic_hist, EL_STR("user"), message); el_val_t updated2 = hist_append(updated, EL_STR("assistant"), reply_text); el_val_t trimmed = ({ el_val_t _if_result_53 = 0; if ((json_array_len(updated2) > 20)) { _if_result_53 = (hist_trim(updated2)); } else { _if_result_53 = (updated2); } _if_result_53; }); (void)(state_set(hist_key, trimmed)); _if_result_52 = (1); } else { _if_result_52 = (0); } _if_result_52; });
   return result;
@@ -27387,7 +27498,8 @@ el_val_t handle_dharma_room_turn(el_val_t body) {
   if (str_eq(transcript, EL_STR(""))) {
     return el_str_concat(el_str_concat(EL_STR("{\"error\":\"transcript is required\",\"response\":\"\",\"cgi_id\":\""), cgi_id), EL_STR("\"}"));
   }
-  el_val_t engram_ctx = engram_compile(transcript);
+  /* chat.el fix (2026-07-01): distill_transcript reduces to last 3 messages for precise WM activation. */
+  el_val_t engram_ctx = engram_compile(distill_transcript(transcript));
   el_val_t system_prompt = ({ el_val_t _if_result_256 = 0; if (str_eq(engram_ctx, EL_STR(""))) { _if_result_256 = (identity); } else { _if_result_256 = (el_str_concat(el_str_concat(identity, EL_STR("\n\n")), engram_ctx)); } _if_result_256; });
   el_val_t raw_response = llm_call_system(model, system_prompt, transcript);
   el_val_t is_error = ((str_starts_with(raw_response, EL_STR("{\"error\"")) || str_starts_with(raw_response, EL_STR("{\"type\":\"error\""))) || str_contains(raw_response, EL_STR("authentication_error")));
@@ -27424,7 +27536,8 @@ el_val_t handle_dharma_room_turn_agentic(el_val_t body) {
   if (str_eq(transcript, EL_STR(""))) {
     return el_str_concat(el_str_concat(EL_STR("{\"error\":\"transcript is required\",\"response\":\"\",\"cgi_id\":\""), cgi_id), EL_STR("\"}"));
   }
-  el_val_t ctx = engram_compile(transcript);
+  /* chat.el fix (2026-07-01): distill_transcript reduces to last 3 messages for precise WM activation. */
+  el_val_t ctx = engram_compile(distill_transcript(transcript));
   el_val_t system = el_str_concat(el_str_concat(identity, EL_STR(" You have access to tools: read files, write files, browse the web, search your memory, run commands. Use them when they add genuine value. Be direct and stay in character.\n\n")), ctx);
   el_val_t api_key = agentic_api_key();
   system = safety_augment_system(system, transcript);
@@ -28768,6 +28881,12 @@ el_val_t strip_query(el_val_t path) {
   return 0;
 }
 
+/* flag_true — tolerant flag: accepts bool true or integer 1 (PR #63). */
+el_val_t flag_true(el_val_t body, el_val_t key) {
+  return (json_get_bool(body, key) || (json_get_int(body, key) > 0));
+  return 0;
+}
+
 el_val_t err_404(el_val_t path) {
   return el_str_concat(el_str_concat(EL_STR("{\"error\":\"not found\",\"path\":\""), path), EL_STR("\"}"));
   return 0;
@@ -29421,6 +29540,26 @@ el_val_t emit_session_start_event(void) {
   el_val_t payload = el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("{\"event\":\"session_start\""), EL_STR(",\"boot\":")), boot_num), EL_STR(",\"cgi\":\"")), eff_cgi), EL_STR("\"")), EL_STR(",\"node_count\":")), int_to_str(node_ct)), EL_STR(",\"edge_count\":")), int_to_str(edge_ct)), EL_STR(",\"identity_loaded\":")), has_identity), EL_STR(",\"ts\":")), int_to_str(ts)), EL_STR("}"));
   el_val_t tags = EL_STR("[\"internal-state\",\"session-start\",\"InternalStateEvent\"]");
   el_val_t discard = engram_node_full(payload, EL_STR("InternalStateEvent"), EL_STR("session-start"), el_from_float(el_from_float(0.9)), el_from_float(el_from_float(0.9)), el_from_float(el_from_float(1.0)), EL_STR("Episodic"), tags);
+  /* Prune accumulated session-start events — keep the 10 most recent.
+   * engram_search_json returns oldest-first, so forget from index 0 to (count-11). */
+  el_val_t keep_n = 10;
+  el_val_t old_events = engram_search_json(EL_STR("session-start InternalStateEvent"), 200);
+  if (!str_eq(old_events, EL_STR("")) && !str_eq(old_events, EL_STR("[]"))) {
+    el_val_t ev_count = json_array_len(old_events);
+    if (ev_count > keep_n) {
+      el_val_t prune_to = (ev_count - keep_n);
+      el_val_t ei = 0;
+      while (ei < prune_to) {
+        el_val_t old_ev = json_array_get(old_events, ei);
+        el_val_t old_ev_id = json_get(old_ev, EL_STR("id"));
+        if (!str_eq(old_ev_id, EL_STR(""))) {
+          (void)(engram_forget(old_ev_id));
+        }
+        ei = (ei + 1);
+      }
+      println(el_str_concat(el_str_concat(el_str_concat(EL_STR("[soul] pruned "), int_to_str(prune_to)), EL_STR(" old session-start events (kept 10)")), EL_STR("")));
+    }
+  }
   println(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("[soul] session-start event logged (boot="), boot_num), EL_STR(" nodes=")), int_to_str(node_ct)), EL_STR(" edges=")), int_to_str(edge_ct)), EL_STR(")")));
   return 0;
 }

dist/win32_shim.h

@@ -0,0 +1,35 @@
+/*
+ * win32_shim.h — Extra POSIX→Win32 stubs for cross-compiling el_runtime.c with mingw-w64.
+ * Injected via -include; supplements el_platform_win.h for symbols it doesn't yet cover.
+ */
+#ifdef _WIN32
+#include <windows.h>
+
+/* ── rusage / getrusage ────────────────────────────────────────────────────── */
+/* el_runtime.c uses getrusage(RUSAGE_SELF) only for a soft memory guard.
+ * On Windows, stub it out: always return 0 ru_maxrss so the guard never fires. */
+#ifndef RUSAGE_SELF
+#define RUSAGE_SELF 0
+struct rusage {
+    long ru_maxrss;   /* the only field el_runtime actually reads */
+};
+static inline int getrusage(int who, struct rusage *r) {
+    (void)who;
+    if (r) r->ru_maxrss = 0;
+    return 0;
+}
+#endif /* RUSAGE_SELF */
+
+/* ── fsync ─────────────────────────────────────────────────────────────────── */
+/* Windows has FlushFileBuffers but no fsync; map it. */
+#ifndef fsync
+#include <io.h>
+static inline int el_win_fsync(int fd) {
+    HANDLE h = (HANDLE)_get_osfhandle(fd);
+    if (h == INVALID_HANDLE_VALUE) return -1;
+    return FlushFileBuffers(h) ? 0 : -1;
+}
+#define fsync(fd) el_win_fsync(fd)
+#endif /* fsync */
+
+#endif /* _WIN32 */

docs/NARRATED-RUNS-ENGINE-NOTES-20260713.md

@@ -0,0 +1,34 @@
+# Narrated runs — engine notes for Will (2026-07-13)
+
+Source half: commit aa67f86 on feat/agent-phase1-soul (run-progress ledger,
+`/api/run-progress/<sid>` route, narration on the pause envelope, config display
+default). E2E-verified via the compiled test bed on Tim's clean profile.
+
+Compiled-form-only fixes (in `neuron-container-build/soul-narrated-runs-20260713.patch`,
+applies ON TOP of `soul-webfix-20260711.patch` — these need porting to chat.el when the
+webfix itself is ported):
+
+1. **pause_turn + tool_use interleave**: a pause_turn response can ALSO carry a client
+   tool_use; resuming verbatim leaves it unpaired → Anthropic 400 "tool_use ids were
+   found without tool_result". Fix: tool-bearing pause rounds are tool turns
+   (dispatch + pair); verbatim resume only when the round has no client tool.
+2. **Agentic toolset scope**: agentic_tools_all() fed EVERY connector/MCP tool (Notion,
+   code-execution…) into the loop. Code-execution flips the API into programmatic
+   tool calling, whose pairing protocol the single-tool manual loop does not speak —
+   source of the dangling-pair 400s AND the bash_code_execution workspace-dodge.
+   Fix: handle_chat_agentic declares builtins + ONE server web_search only.
+   Connector tools return when the loop gains real multi-tool/programmatic support.
+3. **disable_parallel_tool_use: true** on agentic requests — the loop captures only the
+   first tool_use per round; Opus-class models parallel-call. Enforce the invariant.
+4. **web_search server-tool default variant → web_search_20250305 (GA)**. The 20260209
+   variant couples to code-execution ⇒ programmatic mode (see #2, and the June note:
+   "inert unless code-execution attached").
+5. **Homegrown web_search removed** from the tool catalog (server-side is the one tool).
+
+Known engine debts this work surfaced (not fixed):
+
+- **Poisoned session history**: a failed run persists the malformed assistant turn; every
+  later turn in that session replays it and 400s. Needs history sanitation on load.
+- **Huge-history invalid-escape 400** (~346KB request) — likely the same poisoned blob.
+- **macOS note**: replacing a binary in place invalidates its ad-hoc signature (instant
+  silent SIGKILL, looks like exit 0). `rm + cp + codesign -f -s -` is the swap ritual.

docs/telegram-bot-setup.md

@@ -0,0 +1,77 @@
+# Neuron Telegram Gateway — Setup
+
+The Telegram gateway lets you chat with your Neuron soul via Telegram. Plain messages go to the soul; commands give access to memory and status.
+
+## 1. Create a bot via @BotFather
+
+1. Open Telegram and search for **@BotFather**
+2. Send `/newbot`
+3. Pick a name (e.g. "Neuron")
+4. Pick a username (must end in `bot`, e.g. `myneuron_bot`)
+5. BotFather replies with your **HTTP API token** — looks like `7123456789:ABCdef...`
+6. Optionally set a description: `/setdescription` → select your bot → type a description
+
+## 2. Store the token in the macOS Keychain
+
+Never put the token in a plist, `.env`, or any file that might be committed.
+
+```bash
+security add-generic-password \
+  -s neuron-telegram-bot \
+  -a neuron \
+  -w '<paste token here>'
+```
+
+Verify:
+```bash
+security find-generic-password -s neuron-telegram-bot -a neuron -w
+```
+
+## 3. Load the LaunchAgent
+
+```bash
+launchctl load ~/Library/LaunchAgents/ai.neuron.telegram-gateway.plist
+```
+
+Check it started:
+```bash
+launchctl list | grep telegram
+tail -f ~/.neuron/logs/telegram-gateway.out.log
+```
+
+## 4. Test
+
+Send your bot a message in Telegram. It should reply using your soul's voice.
+
+## Commands
+
+| Command | What it does |
+|---------|-------------|
+| `<any text>` | Forwarded to the soul → responds in its voice |
+| `/memory <query>` | Searches soul memories, returns top 3 |
+| `/remember <text>` | Stores text as a memory node |
+| `/status` | Reports whether the soul is reachable |
+
+## Unload / stop
+
+```bash
+launchctl unload ~/Library/LaunchAgents/ai.neuron.telegram-gateway.plist
+```
+
+## Troubleshoot
+
+- **"token not found"** — re-run step 2 above
+- **"Soul is resting"** — the soul daemon at `http://localhost:7770` is not running; start it with `launchctl load ~/Library/LaunchAgents/ai.neuron.engram.plist` (or whichever plist runs the soul)
+- **Logs**: `~/.neuron/logs/telegram-gateway.out.log` and `telegram-gateway.err.log`
+- **Test gateway script directly**:
+  ```bash
+  TELEGRAM_BOT_TOKEN=<token> ~/Development/neuron-technologies/neuron/tools/telegram-gateway.sh
+  ```
+
+## Soul API endpoints used
+
+| Endpoint | Purpose |
+|----------|---------|
+| `POST /api/chat` | Forward messages to the soul |
+| `POST /api/neuron/recall` | Search memories |
+| `POST /api/neuron/memory` | Store conversation as a memory node |

imprint.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header — do not edit
+// auto-generated by elc --emit-header - do not edit
 extern fn imprint_current() -> String
 extern fn imprint_load(imprint_id: String) -> String
 extern fn imprint_respond(input: String, imprint_id: String) -> String

memory.el

@@ -134,12 +134,30 @@ fn mem_boot_count_get() -> Int {
     return str_to_int(num_str)
 }
 
-// mem_boot_count_inc — increment boot counter, store new node, return new count.
-// Each boot creates a new "soul:boot_count:N" node. Old ones accumulate as
-// history — the search above always returns the highest value seen.
+// mem_boot_count_inc — increment boot counter, store a single canonical node, return new count.
+// Prunes ALL existing soul:boot_count nodes before inserting the new one so there is
+// always at most ONE such node in the graph. Without pruning, engram_node_full inserts
+// a new node every boot (no upsert) and the old ones accumulate. The search-first
+// approach also fixes a latent ordering bug: engram_search_json returns oldest-first,
+// so mem_boot_count_get() with limit=3 would read a stale (lower) count once more
+// than 3 copies accumulate.
 fn mem_boot_count_inc() -> Int {
     let current: Int = mem_boot_count_get()
     let next: Int = current + 1
+    // Prune all existing boot_count nodes — keep exactly one.
+    let old_results: String = engram_search_json("soul:boot_count", 50)
+    if !str_eq(old_results, "") && !str_eq(old_results, "[]") {
+        let old_len: Int = json_array_len(old_results)
+        let oi: Int = 0
+        while oi < old_len {
+            let old_node: String = json_array_get(old_results, oi)
+            let old_id: String = json_get(old_node, "id")
+            if !str_eq(old_id, "") {
+                engram_forget(old_id)
+            }
+            let oi = oi + 1
+        }
+    }
     let content: String = "soul:boot_count:" + int_to_str(next)
     let tags: String = "[\"soul-meta\",\"boot-counter\"]"
     let boot_node_id: String = engram_node_full(

memory.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header — do not edit
+// auto-generated by elc --emit-header - do not edit
 extern fn tier_working() -> String
 extern fn tier_episodic() -> String
 extern fn tier_canonical() -> String

neuron-api.el

@@ -196,11 +196,12 @@ fn handle_api_node_create(body: String) -> String {
 fn handle_api_node_delete(body: String) -> String {
     let id: String = json_get(body, "id")
     if str_eq(id, "") { return api_err("id is required") }
-    // engram_forget removes the node + its incident edges from the live graph. We do
-    // NOT read-back-verify here: engram_get_node_json can return a STALE hit for a just-
-    // removed id (the id->index map is not rebuilt on forget), which would produce a
-    // false "delete_failed" even though the node is gone. The graph endpoints
-    // (/api/graph/nodes) correctly reflect the removal, which is the source of truth.
+    // engram_forget removes the node + its incident edges from the live graph.
+    // Delete is NOT read-back-verified: engram_get_node_json can return a stale hit
+    // for a just-forgotten id because the id→index map is not rebuilt on forget.
+    // A stale hit would cause a false "delete_failed" on a successful deletion.
+    // This exception is correct: read-back-verify guards WRITES; for deletes,
+    // the graph endpoints (/api/graph/nodes) reflect the removal and are the source of truth.
     engram_forget(id)
     return "{\"ok\":true,\"id\":\"" + id + "\"}"
 }

neuron-api.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header — do not edit
+// auto-generated by elc --emit-header - do not edit
 extern fn is_protected_node(id: String) -> Bool
 extern fn api_err_protected(id: String) -> String
 extern fn api_json_escape(s: String) -> String

routes.el

@@ -7,6 +7,14 @@ import "neuron-api.el"
 import "sessions.el"
 import "soul.elh"
 
+// flag_true — tolerant flag test: accepts both boolean `true` (Kotlin UI) and
+// integer 1 (el-src UI). json_get_bool only recognises literal `true`, so
+// without this wrapper an "agentic":1 request would silently route to the
+// non-agentic path.
+fn flag_true(body: String, key: String) -> Bool {
+    return json_get_bool(body, key) || json_get_int(body, key) > 0
+}
+
 // ---------------------------------------------------------------------------
 // Rate limiting — simple in-memory per-IP sliding window counter.
 //
@@ -483,6 +491,18 @@ fn handle_request(method: String, path: String, body: String) -> String {
         if str_starts_with(clean, "/api/connectors") {
             return handle_connectors(method, clean, body)
         }
+        // GET /api/run-progress/:session_id — live agentic-run ledger (2026-07-13,
+        // narrated-runs). agentic_loop appends one {"i","t","tool"} entry per round
+        // (the model's own pre-tool narration); a {"done":true} entry closes the run.
+        // Clients poll this during a run to render live step updates without streaming.
+        if str_starts_with(clean, "/api/run-progress/") {
+            let rp_id: String = str_slice(clean, 18, str_len(clean))
+            if !str_eq(rp_id, "") {
+                let rp_raw: String = state_get("run_progress_" + rp_id)
+                let rp_arr: String = if str_eq(rp_raw, "") { "[]" } else { "[" + rp_raw + "]" }
+                return "{\"progress\":" + rp_arr + "}"
+            }
+        }
         // GET /api/sessions — list all sessions
         if str_eq(clean, "/api/sessions") {
             return session_list()

safety.elh

@@ -1,4 +1,4 @@
-// auto-generated by elc --emit-header — do not edit
+// auto-generated by elc --emit-header - do not edit
 extern fn soft_bell_threshold() -> Int
 extern fn hard_bell_threshold() -> Int
 extern fn safety_score_crisis(input: String) -> Int
@@ -13,12 +13,3 @@ extern fn safety_self_harm_phrases() -> String
 extern fn safety_abuse_phrases() -> String
 extern fn safety_general_hard_phrases() -> String
 extern fn safety_soft_phrases() -> String
-extern fn safety_detect_positive_level(message: String) -> String
-extern fn safety_detect_bell_level(message: String) -> String
-extern fn safety_classify_hard_bell(message: String) -> String
-extern fn safety_soft_directive() -> String
-extern fn safety_hard_directive(hard_type: String) -> String
-extern fn safety_augment_system(system: String, user_msg: String) -> String
-extern fn safety_contact_path() -> String
-extern fn handle_safety_contact_get() -> String
-extern fn handle_safety_contact_post(body: String) -> String

sessions.el

@@ -373,6 +373,32 @@ fn session_update_patch(session_id: String, body: String) -> String {
         + ",\"updated_at\":" + int_to_str(ts) + "}"
 }
 
+// session_search_entry — extract one search-result entry from a raw node JSON.
+// Returns a JSON object string or "" if the node is not a valid session:meta node.
+//
+// Extracted from session_search's while loop body to reduce the loop's lexical
+// complexity. The ELC compiler runs out of memory processing while loops with
+// many `let` bindings — extracting the body into a separate function gives the
+// compiler a clean scope boundary at each call. Each function compiles in O(N)
+// rather than the exponential growth caused by rebinding accumulation inside loops.
+// (2026-07-01 self-review: root cause of sessions.c OOM/truncation since June 30)
+fn session_search_entry(node: String) -> String {
+    let label: String = json_get(node, "label")
+    if !str_eq(label, "session:meta") { return "" }
+    let content: String = json_get(node, "content")
+    let sess_id: String = json_get(content, "id")
+    if str_eq(sess_id, "") { return "" }
+    let title: String = json_get(content, "title")
+    let created_raw: String = json_get(content, "created_at")
+    let updated_raw: String = json_get(content, "updated_at")
+    let eff_created: String = if str_eq(created_raw, "") { "0" } else { created_raw }
+    let eff_updated: String = if str_eq(updated_raw, "") { eff_created } else { updated_raw }
+    let e_id: String = "{\"id\":\"" + json_safe(sess_id) + "\""
+    let e_title: String = ",\"title\":\"" + json_safe(title) + "\""
+    let e_ts: String = ",\"created_at\":" + eff_created + ",\"updated_at\":" + eff_updated + "}"
+    return e_id + e_title + e_ts
+}
+
 // session_search — search session:meta nodes whose content matches query.
 fn session_search(query: String) -> String {
     if str_eq(query, "") { return "[]" }
@@ -383,22 +409,7 @@ fn session_search(query: String) -> String {
     let out: String = ""
     let i: Int = 0
     while i < total {
-        let node: String = json_array_get(results, i)
-        let label: String = json_get(node, "label")
-        let content: String = json_get(node, "content")
-        let is_session: Bool = str_eq(label, "session:meta")
-        let sess_id: String = json_get(content, "id")
-        let title: String = json_get(content, "title")
-        let created_raw: String = json_get(content, "created_at")
-        let updated_raw: String = json_get(content, "updated_at")
-        let eff_created: String = if str_eq(created_raw, "") { "0" } else { created_raw }
-        let eff_updated: String = if str_eq(updated_raw, "") { eff_created } else { updated_raw }
-        let entry: String = if is_session && !str_eq(sess_id, "") {
-            "{\"id\":\"" + json_safe(sess_id) + "\""
-            + ",\"title\":\"" + json_safe(title) + "\""
-            + ",\"created_at\":" + eff_created
-            + ",\"updated_at\":" + eff_updated + "}"
-        } else { "" }
+        let entry: String = session_search_entry(json_array_get(results, i))
         let out = if !str_eq(entry, "") {
             if str_eq(out, "") { entry } else { out + "," + entry }
         } else { out }
@@ -666,6 +677,11 @@ fn handle_session_approve(session_id: String, body: String) -> String {
     // path for all sessions created through handle_chat_agentic / agentic_loop.
     let bridge_blob: String = state_get("mcp_bridge:" + session_id)
     if !str_eq(bridge_blob, "") {
+        // BUG-LEAK fix (2026-07-16): the approved tool executes below via dispatch_tool,
+        // whose path/command guards read the shared workspace-root key. Re-assert THIS
+        // session's own root first — an approval must never execute under whatever root
+        // the last unrelated request left behind.
+        state_set("agent_workspace_root", state_get("agent_workspace_root_" + session_id))
         // For "always": record tool_name in the always-allow list before resuming.
         // The tool_name is not stored in the bridge blob (only tool_use_id is).
         // Accept it from the body so the client can pass it along.
@@ -697,7 +713,13 @@ fn handle_session_approve(session_id: String, body: String) -> String {
         // For builtin tools with no client-provided content: fall back to
         // dispatch_tool so those tools still execute correctly.
         let client_content: String = json_get(body, "content")
-        let use_client_content: Bool = !str_eq(client_content, "")
+        // BUG-6 fix (2026-07-17): the naive json_get scanner matches "content" ANYWHERE
+        // in the body — including INSIDE tool_input — so every approved write_file (whose
+        // input always carries a content field) was mistaken for client-executed, never
+        // dispatched, and narrated as done: a false receipt with no file on disk. Builtin
+        // tools now ALWAYS dispatch server-side; client content is only honored for
+        // non-builtin (MCP/client-executed) tools. Stricter only.
+        let use_client_content: Bool = !str_eq(client_content, "") && !is_builtin_tool(approve_tool_name)
         let use_dispatch: Bool = is_builtin_tool(approve_tool_name) && !use_client_content
         let raw_input: String = json_get_raw(body, "tool_input")
         let eff_input: String = if str_eq(raw_input, "") { "{}" } else { raw_input }

sessions.elh

@@ -8,6 +8,7 @@ extern fn session_list() -> String
 extern fn session_get(session_id: String) -> String
 extern fn session_delete(session_id: String) -> String
 extern fn session_update_patch(session_id: String, body: String) -> String
+extern fn session_search_entry(node: String) -> String
 extern fn session_search(query: String) -> String
 extern fn session_hist_load(session_id: String) -> String
 extern fn session_hist_save(session_id: String, hist: String) -> Void

soul.el

@@ -346,6 +346,27 @@ fn emit_session_start_event() -> Void {
         el_from_float(0.9), el_from_float(0.9), el_from_float(1.0),
         "Episodic", tags
     )
+    // Prune accumulated session-start events — keep the 10 most recent.
+    // engram_search_json returns results in insertion order (oldest first), so
+    // results[0..count-11] are the oldest; forgetting them leaves the newest 10.
+    let keep_n: Int = 10
+    let old_events: String = engram_search_json("session-start InternalStateEvent", 200)
+    if !str_eq(old_events, "") && !str_eq(old_events, "[]") {
+        let ev_count: Int = json_array_len(old_events)
+        if ev_count > keep_n {
+            let prune_to: Int = ev_count - keep_n
+            let ei: Int = 0
+            while ei < prune_to {
+                let old_ev: String = json_array_get(old_events, ei)
+                let old_ev_id: String = json_get(old_ev, "id")
+                if !str_eq(old_ev_id, "") {
+                    engram_forget(old_ev_id)
+                }
+                let ei = ei + 1
+            }
+            println("[soul] pruned " + int_to_str(prune_to) + " old session-start events (kept " + int_to_str(keep_n) + ")")
+        }
+    }
     println("[soul] session-start event logged (boot=" + boot_num + " nodes=" + int_to_str(node_ct) + " edges=" + int_to_str(edge_ct) + " prev_summary=" + has_prev_sum + ")")
 }
 

stewardship.elh

@@ -1,15 +1,11 @@
-// stewardship.elh — Layer 2 public surface
-// auto-generated by elc --emit-header — do not edit
+// auto-generated by elc --emit-header - do not edit
+extern fn steward_log_event(kind: String, detail: String) -> Void
 extern fn steward_get_mission() -> String
 extern fn steward_align(input: String, imprint_id: String) -> String
 extern fn steward_validate_imprint(imprint_id: String, tool_name: String) -> String
 extern fn steward_cgi_check(action: String) -> String
-// steward_log_event is an internal helper exported here because El has no access modifiers.
-// External callers have no business invoking this directly — use steward_align,
-// steward_validate_imprint, or steward_cgi_check, which call it at the correct points.
-extern fn steward_log_event(kind: String, detail: String) -> Void
-// Behavioral profiling and continuity detection (Layer 2 — session fingerprinting).
 extern fn steward_fingerprint_session(input: String, session_id: String) -> String
+extern fn extract_dim(content: String, key: String) -> String
 extern fn steward_build_baseline() -> String
 extern fn steward_check_continuity(current_fingerprint: String, session_id: String) -> String
 extern fn steward_session_check(input: String, session_id: String) -> String

studio.el

@@ -46,7 +46,9 @@ fn handle_config(method: String, body: String) -> String {
         }
     }
     let current_model: String = state_get("soul_model")
-    let display: String = if str_eq(current_model, "") { "claude-sonnet-4-5" } else { current_model }
+    // Display fallback aligned with the intended product default (was claude-sonnet-4-5,
+    // which silently became the app's picker default on fresh profiles — 2026-07-13).
+    let display: String = if str_eq(current_model, "") { "claude-opus-4-8" } else { current_model }
     return "{\"model\":\"" + display + "\",\"ok\":true}"
 }
 

tools/telegram-gateway.sh

@@ -0,0 +1,191 @@
+#!/bin/bash
+# Neuron Telegram Gateway
+# Polls Telegram for new messages, forwards to the soul at localhost:7770, sends responses back.
+# Supports plain text chat + commands: /memory, /remember, /status
+#
+# Token resolution order:
+#   1. $TELEGRAM_BOT_TOKEN env var
+#   2. macOS Keychain: security find-generic-password -s neuron-telegram-bot -a neuron -w
+
+set -euo pipefail
+
+TOKEN="${TELEGRAM_BOT_TOKEN:-$(security find-generic-password -s neuron-telegram-bot -a neuron -w 2>/dev/null || true)}"
+SOUL_URL="http://localhost:7770"
+OFFSET=0
+POLL_TIMEOUT=30
+
+if [[ -z "$TOKEN" ]]; then
+  echo "ERROR: No Telegram bot token. Set TELEGRAM_BOT_TOKEN or store in keychain." >&2
+  echo "See: ~/Development/neuron-technologies/neuron/docs/telegram-bot-setup.md" >&2
+  exit 1
+fi
+
+TG="https://api.telegram.org/bot${TOKEN}"
+
+log() { echo "[$(date '+%Y-%m-%d %H:%M:%S')] $*"; }
+
+# Send a Telegram message back to a chat
+send_message() {
+  local chat_id="$1"
+  local text="$2"
+  curl -s -X POST "${TG}/sendMessage" \
+    -H "Content-Type: application/json" \
+    -d "$(jq -n --argjson cid "$chat_id" --arg t "$text" \
+      '{chat_id: $cid, text: $t, parse_mode: "Markdown"}')" \
+    > /dev/null
+}
+
+# Store a memory in the soul
+store_memory() {
+  local content="$1"
+  local label="${2:-telegram:conversation}"
+  curl -s -X POST "${SOUL_URL}/api/neuron/memory" \
+    -H "Content-Type: application/json" \
+    -d "$(jq -n --arg c "$content" --arg l "$label" \
+      '{content: $c, label: $l}')" \
+    > /dev/null
+}
+
+# Chat with the soul; echoes the response text
+soul_chat() {
+  local message="$1"
+  local from="${2:-unknown}"
+  local response
+  response=$(curl -s -X POST "${SOUL_URL}/api/chat" \
+    -H "Content-Type: application/json" \
+    -d "$(jq -n --arg m "$message" --arg f "$from" \
+      '{message: $m, from: $f}')" 2>/dev/null)
+  # Extract .response — fall back to raw body on parse failure
+  jq -r '.response // empty' <<< "$response" 2>/dev/null || echo "$response"
+}
+
+# Search soul memories; echoes formatted results
+soul_recall() {
+  local query="$1"
+  local limit="${2:-3}"
+  local raw
+  raw=$(curl -s -X POST "${SOUL_URL}/api/neuron/recall" \
+    -H "Content-Type: application/json" \
+    -d "$(jq -n --arg q "$query" --argjson l "$limit" \
+      '{query: $q, limit: $l}')" 2>/dev/null)
+  # Format top results as a numbered list (truncate long nodes to 300 chars)
+  jq -r 'if type == "array" then
+    to_entries | .[:3] | map(
+      (.index + 1 | tostring) + ". " + (.value.content | .[0:300] | gsub("\n";" "))
+    ) | join("\n\n")
+  else
+    "No results found."
+  end' <<< "$raw" 2>/dev/null || echo "No results found."
+}
+
+# Check if soul is reachable
+soul_health() {
+  curl -s --max-time 3 "${SOUL_URL}/" > /dev/null 2>&1 && echo "up" || echo "down"
+}
+
+handle_update() {
+  local update="$1"
+  local chat_id msg_text from_name update_id
+
+  update_id=$(jq -r '.update_id' <<< "$update")
+  chat_id=$(jq -r '.message.chat.id // empty' <<< "$update")
+  msg_text=$(jq -r '.message.text // empty' <<< "$update")
+  from_name=$(jq -r '.message.from.first_name // "stranger"' <<< "$update")
+
+  # Skip non-message updates (inline queries, etc.)
+  if [[ -z "$chat_id" || -z "$msg_text" ]]; then
+    OFFSET=$((update_id + 1))
+    return
+  fi
+
+  log "[$update_id] from=$from_name chat=$chat_id text=${msg_text:0:60}"
+
+  # Route by command prefix
+  if [[ "$msg_text" == /status* ]]; then
+    local health
+    health=$(soul_health)
+    if [[ "$health" == "up" ]]; then
+      send_message "$chat_id" "Soul is *online* at ${SOUL_URL} ✓"
+    else
+      send_message "$chat_id" "Soul appears to be *offline* (${SOUL_URL} unreachable)."
+    fi
+
+  elif [[ "$msg_text" == /memory* ]]; then
+    local query="${msg_text#/memory}"
+    query="${query# }"
+    if [[ -z "$query" ]]; then
+      send_message "$chat_id" "Usage: /memory <query>"
+    else
+      local results
+      results=$(soul_recall "$query" 3)
+      if [[ -n "$results" ]]; then
+        send_message "$chat_id" "*Memories matching \"${query}\":*
+
+${results}"
+      else
+        send_message "$chat_id" "No memories found for \"${query}\"."
+      fi
+    fi
+
+  elif [[ "$msg_text" == /remember* ]]; then
+    local content="${msg_text#/remember}"
+    content="${content# }"
+    if [[ -z "$content" ]]; then
+      send_message "$chat_id" "Usage: /remember <text to store>"
+    else
+      store_memory "Telegram (${from_name}): ${content}" "telegram:explicit"
+      send_message "$chat_id" "Stored: _${content}_"
+    fi
+
+  else
+    # Plain text — forward to soul chat
+    local soul_response
+    soul_response=$(soul_chat "$msg_text" "$from_name" 2>/dev/null || true)
+
+    if [[ -z "$soul_response" ]]; then
+      soul_response="Neuron is resting — try again in a moment."
+    fi
+
+    send_message "$chat_id" "$soul_response"
+
+    # Capture conversation as a memory (fire-and-forget)
+    store_memory "Telegram conversation with ${from_name}: [user] ${msg_text} [soul] ${soul_response}" \
+      "telegram:conversation" &
+  fi
+
+  OFFSET=$((update_id + 1))
+}
+
+log "Neuron Telegram gateway starting (soul=${SOUL_URL}, poll_timeout=${POLL_TIMEOUT}s)"
+
+while true; do
+  # Long-poll for updates
+  UPDATES=$(curl -s --max-time $((POLL_TIMEOUT + 5)) \
+    "${TG}/getUpdates?offset=${OFFSET}&timeout=${POLL_TIMEOUT}" 2>/dev/null || true)
+
+  if [[ -z "$UPDATES" ]]; then
+    log "WARN: Empty response from Telegram; retrying in 5s"
+    sleep 5
+    continue
+  fi
+
+  OK=$(jq -r '.ok // false' <<< "$UPDATES" 2>/dev/null)
+  if [[ "$OK" != "true" ]]; then
+    DESC=$(jq -r '.description // "unknown error"' <<< "$UPDATES" 2>/dev/null)
+    log "WARN: Telegram API error: ${DESC}; retrying in 10s"
+    sleep 10
+    continue
+  fi
+
+  # Iterate over each update
+  COUNT=$(jq '.result | length' <<< "$UPDATES" 2>/dev/null || echo 0)
+  if [[ "$COUNT" -gt 0 ]]; then
+    for i in $(seq 0 $((COUNT - 1))); do
+      update=$(jq ".result[$i]" <<< "$UPDATES")
+      handle_update "$update"
+    done
+  fi
+
+  # Avoid hammering the API if something is very wrong
+  sleep 1
+done