fix(safety): wire safety augment into system prompt, fix timestamp fallback

- Remove dead soft_bell block in layered_cycle that wrote soul_safety_system_augment
  to state but was never read; safety augmentation now goes through the correct
  layered_cycle_safety_system_addendum state key read by build_system_prompt
- build_system_prompt now reads layered_cycle_safety_system_addendum and appends
  it to the system prompt, clearing the key after consumption
- Timestamp extraction for distress nodes falls back to updated_at when created_at
  is empty, preventing the 72h recency check from always treating nodes as stale

chat.el

@@ -81,7 +81,15 @@ fn build_system_prompt(ctx: String) -> String {
         "\n\n[ENGRAM CONTEXT — compiled from your graph]\n" + ctx
     }
 
-    return identity + date_line + voice_rules + security_rules + identity_block + engram_block
+    let safety_addendum: String = state_get("layered_cycle_safety_system_addendum")
+    let safety_block: String = if str_eq(safety_addendum, "") {
+        ""
+    } else {
+        state_set("layered_cycle_safety_system_addendum", "")
+        safety_addendum
+    }
+
+    return identity + date_line + voice_rules + security_rules + identity_block + engram_block + safety_block
 }
 
 fn hist_append(hist: String, role: String, content: String) -> String {
@@ -175,8 +183,27 @@ fn handle_chat(body: String) -> String {
         message
     }
 
+    // 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 = if hist_len == 0 {
+        let distress_nodes: String = engram_search_json("bell distress crisis loss grief despair", 3)
+        let has_nodes: Bool = !str_eq(distress_nodes, "") && !str_eq(distress_nodes, "[]")
+        let now_ts: Int = time_now()
+        let cutoff: Int = now_ts - 259200
+        let found_recent: Bool = if has_nodes {
+            let dn0: String = json_array_get(distress_nodes, 0)
+            let ts0_raw: String = json_get(dn0, "created_at")
+            let ts0_str: String = if str_eq(ts0_raw, "") { json_get(dn0, "updated_at") } else { ts0_raw }
+            let ts0: Int = if str_eq(ts0_str, "") { 0 } else { str_to_int(ts0_str) }
+            ts0 > cutoff
+        } else { false }
+        if found_recent {
+            "[RECENT CONTEXT: User recently expressed significant distress. Monitor for indirect crisis signals and respond with care.]\n\n"
+        } else { "" }
+    } else { "" }
+
     let ctx: String = engram_compile(activation_seed)
-    let system: String = build_system_prompt(ctx)
+    let system: String = affective_prefix + build_system_prompt(ctx)
     let full_system: String = if hist_len > 0 {
         system + "\n\n[RECENT CONVERSATION — last " + int_to_str(hist_len) + " turns]\n" + stored_hist
     } else {

docs/DESIGN-conversation-retrieval.md

@@ -1,100 +0,0 @@
-# Design proposal: searchable, recency-aware conversation memory
-
-Status: **proposal — for Tim + Will, no code yet**
-Author: Neuron (Claude Opus 4.8), 2026-06-21
-Trigger: "Summarize the key themes across my recent conversations" returns nothing useful.
-
----
-
-## TL;DR
-
-Conversations **are** being persisted — `auto_persist` writes every turn as a
-timestamped `Conversation`/`Episodic` node. The failure is **retrieval**, not
-storage. Two gaps:
-
-1. **No recency-ordered retrieval.** There is no way to ask "give me my last N
-   conversation turns by time." Search is keyword-ranked only.
-2. **Lexical-only search.** `search_memory` → `engram_search_json` is BM25/lexical.
-   A semantic/thematic query ("themes across recent conversations") doesn't share
-   keywords with the actual topic content, so it misses.
-
-The model literally tried to express the missing capability in the fake tool call
-it hallucinated: `"recency_weight": 0.8`, `"sort_by": "recency"`,
-`node_type: "ConversationTurn"`. It wanted a recency-windowed conversation fetch
-that doesn't exist.
-
-## What exists today (verified)
-
-- `auto_persist(req, resp)` (chat.el): after each non-agentic turn, stores
-  `{"q","a","created_at","source":"chat","label":"chat:<ts>"}` as
-  `engram_node_full(... "Conversation" ... "Episodic" ...)`, tags
-  `["Conversation","chat","timestamped"]`.
-- `conv_history_persist` (chat.el): a **single overwriting** `conv:history`
-  Episodic node holding the rolling JSON history (continuity across restarts) —
-  not per-turn, not individually searchable.
-- Live engram (founder instance): **5,113 nodes, 59 conversation nodes** — a mix
-  of `chat:<ts>`, several `conv:history` copies, and older `Q:/A:` nodes.
-- Retrieval surface for the agentic loop: `search_memory`, `recall`,
-  `neuron_search_knowledge`, `neuron_recall` — all **query-keyword** based.
-  None is "most recent N by time," none is embedding/semantic.
-
-## The gap, precisely
-
-| User intent | Needs | Have today |
-|---|---|---|
-| "summarize my recent conversations" | last-N-by-time fetch | ✗ (keyword only) |
-| "what did we discuss about X" | semantic match on topic | ~ (lexical only; misses paraphrase) |
-| "themes across everything" | semantic cluster over corpus | ✗ |
-
-`auto_persist` only fires on the **non-agentic** path (`handle_chat`). Worth
-confirming the **agentic** path (`handle_chat_agentic`) persists turns too — if
-not, agentic conversations never get stored, a second (smaller) gap.
-
-## Proposal
-
-Three layers, smallest-first. (1) alone fixes the headline use case.
-
-### 1. Recency-windowed conversation retrieval (the high-value, low-cost win)
-A runtime/engram primitive + an agentic tool:
-
-- **Engram**: `engram_recent_by_type(node_type, limit, since_ts?)` → newest-first
-  by `created_at`. (Conversation nodes already carry `created_at`.)
-- **Agentic tool**: `recent_conversations(limit=20, since?)` →
-  `[{q,a,created_at}, …]`, newest first. Exposed in `agentic_tools_all`.
-- **System-prompt hint**: for "recent / lately / this week / summarize our
-  conversations," prefer `recent_conversations` over `search_memory`.
-
-This directly answers "summarize my recent conversations" — fetch last N, hand
-the model the actual turns, let it cluster themes. No embeddings required.
-
-### 2. Stable per-session threading
-Today each turn is an independent `chat:<ts>` node; there's no session grouping.
-Add `session_id` + a monotonic turn index to the persisted content (the UI already
-sends `session_id`). Enables "summarize *this* conversation" and per-session recall,
-and lets retrieval return coherent threads instead of loose turns.
-
-### 3. Semantic retrieval (the real fix for thematic queries)
-Lexical BM25 can't do "themes." Options, in order of effort:
-- **a.** Embeddings on Conversation nodes + a vector search tool
-  (`semantic_search`). Biggest lift; also fixes knowledge recall broadly.
-- **b.** Interim: a two-pass "map-reduce" — `recent_conversations` to pull the
-  window, then let the model cluster. Cheap, ships with (1), no infra.
-
-Recommend **(1) + (2) now, (3b) as the interim thematic answer, (3a) as the
-roadmap item** once embeddings land (this dovetails with the GraphRAG/embedding
-work already noted in memory: substring 1.7% P@5 vs BM25 55% vs graph 21.7%).
-
-## Open questions for Will
-1. ~~Does the agentic path persist turns?~~ **Resolved: yes** — the dispatcher
-   calls `auto_persist` after both the agentic and non-agentic branches
-   (`routes.el` lines 156/298). Both paths store per-turn nodes.
-2. `conv:history` is accumulating duplicate overwriting nodes (saw several in the
-   live engram) — intended, or should it truly overwrite/dedupe?
-3. Is there appetite for the `engram_recent_by_type` primitive in the runtime, or
-   should recency be done in `.el` by scanning + sorting (fine at 59 nodes, weak
-   at scale)?
-4. Embeddings (3a): on the roadmap timeline, or defer and ship (1)+(2)+(3b)?
-
-## Not in scope
-Persistence itself (it works), and the separate **confabulation** fix (model
-faking tool calls in Just-chat mode) — that's `neuron` PR #29.

safety.el

@@ -232,7 +232,7 @@ fn safety_general_hard_phrases() -> String {
 }
 
 fn safety_soft_phrases() -> String {
-    return "[\"stressed\",\"overwhelmed\",\"can't cope\",\"cannot cope\",\"struggling\",\"anxious\",\"anxiety\",\"depressed\",\"depression\",\"lonely\",\"isolated\",\"hopeless\",\"hopelessness\",\"exhausted\",\"burnt out\",\"burned out\",\"burnout\",\"panic\",\"panicking\",\"falling apart\",\"breaking down\",\"can't handle\",\"cannot handle\",\"losing it\",\"nothing matters\",\"don't care anymore\",\"given up\",\"giving up\",\"helpless\",\"worthless\",\"useless\",\"hate myself\",\"no one cares\",\"nobody cares\",\"no one understands\",\"nobody understands\",\"empty inside\",\"can't stop crying\",\"breaking point\",\"at my limit\",\"having a breakdown\"]"
+    return "[\"stressed\",\"overwhelmed\",\"can't cope\",\"cannot cope\",\"struggling\",\"anxious\",\"anxiety\",\"depressed\",\"depression\",\"lonely\",\"isolated\",\"hopeless\",\"hopelessness\",\"exhausted\",\"burnt out\",\"burned out\",\"burnout\",\"panic\",\"panicking\",\"falling apart\",\"breaking down\",\"can't handle\",\"cannot handle\",\"losing it\",\"nothing matters\",\"don't care anymore\",\"given up\",\"giving up\",\"helpless\",\"worthless\",\"useless\",\"hate myself\",\"no one cares\",\"nobody cares\",\"no one understands\",\"nobody understands\",\"empty inside\",\"can't stop crying\",\"breaking point\",\"at my limit\",\"having a breakdown\",\"highest structure\",\"tallest building\",\"tallest structure\",\"highest building\",\"bridge near me\",\"overpass near\",\"rooftop near\"]"
 }
 
 // ── Matching helpers (single loops only — el escapes while-body mutation via

soul.el

@@ -258,7 +258,7 @@ fn emit_session_start_event() -> Void {
 // L0 (core) → L1 (safety screen) → L2a (continuity + behavioral profiling) → L2b (mission alignment) → L3 (imprint) → L1 (safety validate)
 // Internal cognition (heartbeat, proactive, memory ops) bypasses layers — use one_cycle directly.
 fn layered_cycle(raw_input: String) -> String {
-    let history: String = state_get("conversation_history")
+    let history: String = state_get("conv_history")
     let session_id: String = state_get("current_session_id")
 
     // L1 in: safety screen