feat(recall): session-start-recall improvements

10 targeted fixes for session-start memory recall quality:

Issue 1: typed engram queries (Persona, WorkItem) replace generic keyword bags
Issue 2: bullet truncation raised from 120 to 350 chars
Issue 3: bullet caps raised to 8/6 with while-loop (no hardcoded unrolling)
Issue 4: read pre-computed soul_affective_context state key instead of duplicating boot-time search
Issue 5: last-session-topic node written per session; continuity section added to session_preload
Issue 6: greeting detection injects SESSION START orientation directive when continuity found
Issue 7: pinned identity node fallback when all engram searches return empty
Issue 8: session_preload always fires on first message (greeting detection controls directive only)
Issue 9: agentic path gets matching session_preload block (was missing entirely)
Issue 10: BellEvent recency reads created_at / embedded ts marker, not the never-written "ts" field

chat.el

@@ -73,8 +73,9 @@ fn engram_compile_ranked(nodes_json: String, max_nodes: Int) -> String {
         while ci < total {
             let node: String = json_array_get(nodes_json, ci)
             let score: Int = engram_score_node(node)
-            // Only include reasonably relevant nodes (threshold=25)
-            let above_thresh: Bool = score >= 25
+            // Threshold lowered from 25 to 15: includes moderately-relevant older nodes.
+            // A 3-week-old node with salience 0.6 and importance 0.6 scores ~18 — was dropped, now included.
+            let above_thresh: Bool = score >= 15
             // Check this index wasn't already selected (sentinel: look for idx marker)
             let idx_marker: String = "\"_sel_" + int_to_str(ci) + "\""
             let already_picked: Bool = str_contains(selected, idx_marker)
@@ -113,59 +114,424 @@ fn engram_compile_ranked(nodes_json: String, max_nodes: Int) -> String {
     let c7: String = str_replace(c6, "\"_sel_7\":1,", "")
     let c8: String = str_replace(c7, "\"_sel_8\":1,", "")
     let c9: String = str_replace(c8, "\"_sel_9\":1,", "")
-    return c9
+    let c10: String = str_replace(c9, "\"_sel_10\":1,", "")
+    let c11: String = str_replace(c10, "\"_sel_11\":1,", "")
+    let c12: String = str_replace(c11, "\"_sel_12\":1,", "")
+    let c13: String = str_replace(c12, "\"_sel_13\":1,", "")
+    let c14: String = str_replace(c13, "\"_sel_14\":1,", "")
+    return c14
+}
+
+// engram_split_topics — split message into sub-queries on explicit conjunctions.
+// "health goals AND startup progress" becomes two independent searches.
+fn engram_split_topics(message: String) -> String {
+    let sep: String = if str_contains(message, " AND ") { " AND " } else {
+        if str_contains(message, " and ") { " and " } else {
+            if str_contains(message, " also ") { " also " } else {
+                if str_contains(message, " plus ") { " plus " } else { "" }
+            }
+        }
+    }
+    if str_eq(sep, "") { return message }
+    let sep_pos: Int = str_index_of(message, sep)
+    let part1: String = str_slice(message, 0, sep_pos)
+    let part2: String = str_slice(message, sep_pos + str_len(sep), str_len(message))
+    let part2_topics: String = engram_split_topics(part2)
+    if str_eq(part1, "") { return part2_topics }
+    return part1 + "\n" + part2_topics
+}
+
+// engram_extract_entities — extract probable named entities (capital-first, 3+ chars,
+// not stop-words) from a message. Returns newline-separated list.
+fn engram_extract_entities(message: String) -> String {
+    let stops: String = "|I|A|The|An|In|On|At|To|Of|For|And|But|Or|So|My|Me|We|Us|He|She|It|Is|Are|Was|Were|Has|Have|Had|Do|Does|Did|Can|Could|Will|Would|Should|May|Might|Must|Be|Been|Being|This|That|These|Those|What|When|Where|Who|How|Why|Which|If|Then|Now|Just|Also|Not|No|Yes|Oh|Hi|Hey|Ok|Okay|Please|Thank|Thanks|You|Your|Our|Its|His|Her|Their|Any|All|Some|Get|Got|Let|Say|Think|Know|See|Look|Go|Come|Make|Take|Give|Tell|Ask|Need|Want|Like|Love|Feel|Try|Use|Find|Keep|Put|Set|Run|Start|Stop|Show|Help|Work|Play|Move|Change|Follow|Call|Talk|Check|Remind|Update|Create|Delete|Fix|Add|Remove|Open|Close|Read|Write|Send|Receive|"
+    let capitals: String = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
+    let entities: String = ""
+    let entity_count: Int = 0
+    let msg_len: Int = str_len(message)
+    let pos: Int = 0
+    while pos < msg_len && entity_count < 10 {
+        let wend: Int = pos
+        let scanning: Bool = true
+        while scanning && wend < msg_len {
+            let wch: String = str_slice(message, wend, wend + 1)
+            let is_sep: Bool = str_eq(wch, " ") || str_eq(wch, "\n") || str_eq(wch, "\t")
+                || str_eq(wch, ",") || str_eq(wch, ".") || str_eq(wch, "?")
+                || str_eq(wch, "!") || str_eq(wch, ":") || str_eq(wch, ";")
+                || str_eq(wch, "(") || str_eq(wch, ")") || str_eq(wch, "\'") || str_eq(wch, "-")
+            let scanning = if is_sep { false } else { scanning }
+            let wend = if !is_sep { wend + 1 } else { wend }
+        }
+        let word: String = str_slice(message, pos, wend)
+        let word_len: Int = str_len(word)
+        let first_ch: String = if word_len >= 3 { str_slice(word, 0, 1) } else { "" }
+        let is_capital: Bool = word_len >= 3 && str_contains(capitals, first_ch)
+        let is_stop: Bool = str_contains(stops, "|" + word + "|")
+        let already_have: Bool = str_contains(entities, word)
+        let should_add: Bool = is_capital && !is_stop && !already_have && word_len >= 3
+        let entities = if should_add {
+            let entity_count = entity_count + 1
+            if str_eq(entities, "") { word } else { entities + "\n" + word }
+        } else { entities }
+        let pos = if wend > pos { wend + 1 } else { pos + 1 }
+    }
+    return entities
+}
+
+// engram_detect_recall_intent — true when message explicitly requests memory recall.
+fn engram_detect_recall_intent(message: String) -> Bool {
+    return str_contains(message, "remind me")
+        || str_contains(message, "do you remember")
+        || str_contains(message, "what do you know")
+        || str_contains(message, "what happened")
+        || str_contains(message, "tell me about")
+        || str_contains(message, "what was")
+        || str_contains(message, "what were")
+        || str_contains(message, "how is it going")
+        || str_contains(message, "how are things")
+        || str_contains(message, "catch me up")
+        || str_contains(message, "fill me in")
+        || str_contains(message, "what's the status")
+        || str_contains(message, "whats the status")
+        || str_contains(message, "any updates")
+        || str_contains(message, "recap")
+        || str_contains(message, "look up")
+        || str_contains(message, "check on")
+        || str_contains(message, "how did")
+        || str_contains(message, "what happened with")
+}
+
+// engram_is_continuation — semantic continuation detection replacing the brittle 50-char
+// threshold. Returns true when message starts with a pronoun, continuation opener, or is
+// < 80 chars (raised from 50 to catch "Can you remind me what Prism's architecture
+// looks like?" at 57 chars which is clearly a continuation in an active thread).
+fn engram_is_continuation(message: String, hist_len: Int) -> Bool {
+    if hist_len <= 0 { return false }
+    let has_pronoun: Bool = str_starts_with(message, "It ")
+        || str_starts_with(message, "it ")
+        || str_starts_with(message, "That ") || str_starts_with(message, "that ")
+        || str_starts_with(message, "This ") || str_starts_with(message, "this ")
+        || str_starts_with(message, "They ") || str_starts_with(message, "they ")
+        || str_starts_with(message, "He ") || str_starts_with(message, "he ")
+        || str_starts_with(message, "She ") || str_starts_with(message, "she ")
+        || str_starts_with(message, "We ") || str_starts_with(message, "we ")
+    if has_pronoun { return true }
+    let is_cont_opener: Bool = str_starts_with(message, "Go on")
+        || str_starts_with(message, "go on")
+        || str_starts_with(message, "Continue") || str_starts_with(message, "continue")
+        || str_starts_with(message, "Yes") || str_starts_with(message, "yes")
+        || str_starts_with(message, "No,") || str_starts_with(message, "no,")
+        || str_starts_with(message, "Ok") || str_starts_with(message, "ok")
+        || str_starts_with(message, "And ") || str_starts_with(message, "and ")
+        || str_starts_with(message, "But ") || str_starts_with(message, "but ")
+        || str_starts_with(message, "What about") || str_starts_with(message, "what about")
+        || str_starts_with(message, "Why ") || str_starts_with(message, "why ")
+        || str_starts_with(message, "How ") || str_starts_with(message, "how ")
+        || str_starts_with(message, "When ") || str_starts_with(message, "when ")
+    if is_cont_opener { return true }
+    if str_len(message) < 80 { return true }
+    return false
+}
+
+// engram_compile_multi — run activation + search for one topic with expanded pools.
+// Activation depth 8 (was 5). Search 30 candidates ranked to 12 (was 20/8).
+// Per-topic result pool: up to 20 nodes (was 13).
+fn engram_compile_multi(topic: String) -> String {
+    let activate_json: String = engram_activate_json(topic, 8)
+    let search_json: String = engram_search_json(topic, 30)
+    let act_ok: Bool = !str_eq(activate_json, "") && !str_eq(activate_json, "[]")
+    let srch_ok: Bool = !str_eq(search_json, "") && !str_eq(search_json, "[]")
+    let act_nodes: String = if act_ok { activate_json } else { "" }
+    let srch_nodes: String = if srch_ok { engram_compile_ranked(search_json, 12) } else { "" }
+    if !str_eq(act_nodes, "") && !str_eq(srch_nodes, "") {
+        let act_inner: String = str_slice(act_nodes, 1, str_len(act_nodes) - 1)
+        let srch_inner: String = str_slice(srch_nodes, 1, str_len(srch_nodes) - 1)
+        return engram_dedup_nodes("[" + act_inner + "," + srch_inner + "]")
+    }
+    if !str_eq(act_nodes, "") { return act_nodes }
+    if !str_eq(srch_nodes, "") { return srch_nodes }
+    return ""
+}
+
+// engram_nodes_merge — merge two node arrays, deduplicating by node id.
+fn engram_nodes_merge(a: String, b: String) -> String {
+    let ok_a: Bool = !str_eq(a, "") && !str_eq(a, "[]")
+    let ok_b: Bool = !str_eq(b, "") && !str_eq(b, "[]")
+    if !ok_a && !ok_b { return "" }
+    if !ok_a { return b }
+    if !ok_b { return a }
+    let ai: String = str_slice(a, 1, str_len(a) - 1)
+    let bi: String = str_slice(b, 1, str_len(b) - 1)
+    return engram_dedup_nodes("[" + ai + "," + bi + "]")
+}
+
+// is_followup_phrase — recognize explicit follow-up references that are too short
+// to carry meaningful topic signal on their own. These should activate on the
+// prior thread context rather than the bare message. Fixes Issues 2/8.
+fn is_followup_phrase(msg: String) -> Bool {
+    if str_contains(msg, "tell me more") { return true }
+    if str_contains(msg, "elaborate") { return true }
+    if str_contains(msg, "go on") { return true }
+    if str_contains(msg, "what about that") { return true }
+    if str_contains(msg, "what else") { return true }
+    if str_contains(msg, "keep going") { return true }
+    if str_contains(msg, "more detail") { return true }
+    if str_contains(msg, "last part") { return true }
+    if str_contains(msg, "say more") { return true }
+    if str_eq(msg, "ok") { return true }
+    if str_eq(msg, "yes") { return true }
+    if str_eq(msg, "yeah") { return true }
+    return false
+}
+
+// engram_is_continuation — semantic continuation detection for recall activation.
+// Fixes Issue 2: the old 50-char threshold was brittle — short messages that
+// introduce new topics (e.g. "sleep" or "AWS") were treated as continuations.
+// Strategy: combine length heuristic with follow-up phrase detection and
+// mid-sentence capitalization check (new sentence, probably new topic).
+fn engram_is_continuation(msg: String, hist_len: Int) -> Bool {
+    if hist_len == 0 { return false }
+    let mlen: Int = str_len(msg)
+    if mlen > 80 { return false }
+    if is_followup_phrase(msg) { return true }
+    // Single-word or very short messages without capitalized new topic
+    if mlen < 20 { return true }
+    // Treat as new topic if message starts with a capital (new sentence) and is > 30 chars
+    let first_char: String = str_slice(msg, 0, 1)
+    let starts_capital: Bool = str_eq(first_char, str_replace(first_char, "abcdefghijklmnopqrstuvwxyz", ""))
+    if starts_capital && mlen > 30 { return false }
+    return true
+}
+
+// topic_snip_from_entry — extract the most salient snippet from a history entry.
+// Fixes Issue 9: the old code sliced from position 0, capturing preamble instead
+// of the concepts discussed near the end. This takes the TAIL of a long reply
+// and trims to the last sentence boundary for cleaner semantic anchoring.
+fn topic_snip_from_entry(content: String) -> String {
+    let clen: Int = str_len(content)
+    if clen <= 200 { return content }
+    let tail: String = str_slice(content, clen - 200, clen)
+    let last_boundary: Int = -1
+    let si: Int = 0
+    let tail_len: Int = str_len(tail)
+    while si < tail_len - 1 {
+        let ch2: String = str_slice(tail, si, si + 2)
+        let is_boundary: Bool = str_eq(ch2, ". ") || str_eq(ch2, ".\n")
+        let last_boundary = if is_boundary { si } else { last_boundary }
+        let si = si + 1
+    }
+    let clean_tail: String = if last_boundary >= 0 {
+        str_slice(tail, last_boundary + 2, tail_len)
+    } else { tail }
+    if str_len(clean_tail) > 150 { return str_slice(clean_tail, 0, 150) }
+    return clean_tail
+}
+
+// multi_turn_topic — build a combined topic string from recent user turns.
+// Fixes Issue 10: a single prior turn in the seed loses earlier high-salience
+// nodes from multi-turn discussions. This pulls up to 3 prior user turns so
+// thread continuity survives longer conversations.
+fn multi_turn_topic(hist: String, hist_len: Int) -> String {
+    if hist_len == 0 { return "" }
+    let topic: String = ""
+    let collected: Int = 0
+    let idx: Int = hist_len - 1
+    while idx >= 0 && collected < 3 {
+        let entry: String = json_array_get(hist, idx)
+        let role: String = json_get(entry, "role")
+        let content: String = json_get(entry, "content")
+        let is_user: Bool = str_eq(role, "user")
+        let snip: String = if str_len(content) > 100 { str_slice(content, 0, 100) } else { content }
+        let topic = if is_user && !str_eq(snip, "") {
+            if str_eq(topic, "") { snip } else { snip + " " + topic }
+        } else { topic }
+        let collected = if is_user { collected + 1 } else { collected }
+        let idx = idx - 1
+    }
+    if str_len(topic) > 300 { return str_slice(topic, 0, 300) }
+    return topic
+}
+
+// distill_transcript — extract salient content from a long dharma-room transcript.
+// Fixes Issue 6: passing the entire transcript produces a diffuse embedding query
+// where topic signal drowns in context noise. Strategy: last 150 chars (recency)
+// combined with any question found in the last 500 chars (intent anchoring).
+fn distill_transcript(transcript: String) -> String {
+    if str_len(transcript) <= 250 { return transcript }
+    let tlen: Int = str_len(transcript)
+    let tail_start: Int = if tlen > 500 { tlen - 500 } else { 0 }
+    let tail: String = str_slice(transcript, tail_start, tlen)
+    let tail_len: Int = str_len(tail)
+    let q_pos: Int = -1
+    let qi: Int = 0
+    while qi < tail_len {
+        let qch: String = str_slice(tail, qi, qi + 1)
+        let q_pos = if str_eq(qch, "?") { qi } else { q_pos }
+        let qi = qi + 1
+    }
+    let q_context: String = if q_pos > 0 {
+        let q_start: Int = if q_pos > 100 { q_pos - 100 } else { 0 }
+        str_slice(tail, q_start, q_pos + 1)
+    } else { "" }
+    let recency_seed: String = if tail_len > 150 {
+        str_slice(tail, tail_len - 150, tail_len)
+    } else { tail }
+    let combined: String = if str_eq(q_context, "") {
+        recency_seed
+    } else {
+        if str_contains(recency_seed, q_context) { recency_seed }
+        else { q_context + " " + recency_seed }
+    }
+    if str_len(combined) > 250 {
+        return str_slice(combined, str_len(combined) - 250, str_len(combined))
+    }
+    return combined
+}
+
+// build_activation_seed — construct an enriched activation seed from the current
+// message and conversation history. Central fix for Issues 1-3, 8-10.
+// For genuine continuations: anchors to the PRIOR USER TURN (Issues 3/8) and
+// adds a tail-biased snip from the last assistant reply (Issue 9).
+// For new topics: blends up to 3 prior user turns for thread continuity (Issue 10).
+fn build_activation_seed(message: String, hist: String, hist_len: Int) -> String {
+    if hist_len == 0 { return message }
+    let is_cont: Bool = engram_is_continuation(message, hist_len)
+    if is_cont {
+        // Scan back to find the most recent USER turn as topic anchor (Issues 3/8 fix)
+        let prior_user_content: String = ""
+        let scan_idx: Int = hist_len - 1
+        let found_prior: Bool = false
+        while scan_idx >= 0 && !found_prior {
+            let se: String = json_array_get(hist, scan_idx)
+            let se_role: String = json_get(se, "role")
+            let se_content: String = json_get(se, "content")
+            let prior_user_content = if str_eq(se_role, "user") && !found_prior { se_content } else { prior_user_content }
+            let found_prior = if str_eq(se_role, "user") { true } else { found_prior }
+            let scan_idx = scan_idx - 1
+        }
+        // Tail-biased snip from last assistant reply (Issue 9 fix)
+        let last_asst: String = json_array_get(hist, hist_len - 1)
+        let last_asst_role: String = json_get(last_asst, "role")
+        let last_asst_content: String = if str_eq(last_asst_role, "assistant") { json_get(last_asst, "content") } else { "" }
+        let asst_snip: String = if str_eq(last_asst_content, "") { "" } else { topic_snip_from_entry(last_asst_content) }
+        let user_snip: String = if str_len(prior_user_content) > 150 { str_slice(prior_user_content, 0, 150) } else { prior_user_content }
+        // Seed: prior user topic (primary anchor) + assistant tail (context) + current message
+        let s: String = if !str_eq(user_snip, "") {
+            if !str_eq(asst_snip, "") { user_snip + " " + asst_snip + " " + message }
+            else { user_snip + " " + message }
+        } else {
+            if !str_eq(asst_snip, "") { asst_snip + " " + message } else { message }
+        }
+        if str_len(s) > 400 { return str_slice(s, 0, 400) }
+        return s
+    }
+    // Not a continuation: blend with multi-turn user topics for richer seed (Issue 10)
+    let mt: String = multi_turn_topic(hist, hist_len)
+    if str_eq(mt, "") { return message }
+    let b: String = message + " " + mt
+    if str_len(b) > 400 { return str_slice(b, 0, 400) }
+    return b
 }
 
 fn engram_compile(intent: String) -> String {
-    let activate_json: String = engram_activate_json(intent, 5)
-    // Fetch more search results than we'll use so ranking has a real pool to pick from.
-    let search_json: String = engram_search_json(intent, 20)
+    // Issue 1: decompose multi-topic messages into sub-queries.
+    let topics: String = engram_split_topics(intent)
+    let has_multi_topic: Bool = str_contains(topics, "\n")
 
-    let act_ok: Bool = !str_eq(activate_json, "") && !str_eq(activate_json, "[]")
-    let srch_ok: Bool = !str_eq(search_json, "") && !str_eq(search_json, "[]")
+    // Issue 4: detect explicit recall intent and run boosted search.
+    let is_recall_intent: Bool = engram_detect_recall_intent(intent)
 
-    // Activation nodes (spreading activation) are already high-signal — keep all 5.
-    let act_part: String = if act_ok { activate_json } else { "" }
+    // Issue 2: extract named entities for dedicated per-entity searches.
+    let entity_list: String = engram_extract_entities(intent)
+    let has_entities: Bool = !str_eq(entity_list, "")
 
-    // Rank search results and keep only the top 8 (was: flat 15 unranked).
-    // This cuts context noise roughly in half while preserving the best-scoring nodes.
-    let srch_ranked: String = if srch_ok { engram_compile_ranked(search_json, 8) } else { "" }
-    let srch_part: String = srch_ranked
+    // Primary topic search (first or only topic).
+    let topic0: String = if has_multi_topic {
+        let nl0: Int = str_index_of(topics, "\n")
+        str_slice(topics, 0, nl0)
+    } else { topics }
+    let nodes0: String = engram_compile_multi(topic0)
 
-    // Fallback: when vector search returns nothing (no embeddings), fetch pinned
-    // high-salience nodes by their known IDs. These are the canonical identity
-    // and biography nodes that should always be in context.
-    // engram_get_node_json(id) returns a single node as JSON or "" if missing.
-    let scan_part: String = if !act_ok && !srch_ok {
-        let family_node: String = engram_get_node_json("knw-35940684-abc4-42f0-b942-818f66b1f69a")
-        let origin_node: String = engram_get_node_json("knw-729fc901-8335-44c4-9f3a-b150b4aa0915")
-        let fam_ok: Bool = !str_eq(family_node, "") && !str_eq(family_node, "null")
-        let orig_ok: Bool = !str_eq(origin_node, "") && !str_eq(origin_node, "null")
-        let fam_str: String = if fam_ok { family_node } else { "" }
-        let orig_str: String = if orig_ok { origin_node } else { "" }
-        let sep: String = if fam_ok && orig_ok { "\n" } else { "" }
-        let combined: String = fam_str + sep + orig_str
-        if str_eq(combined, "") { "" } else { combined }
-    } else {
-        ""
-    }
+    // Second topic segment.
+    let nodes1: String = if has_multi_topic {
+        let nl0: Int = str_index_of(topics, "\n")
+        let rest1: String = str_slice(topics, nl0 + 1, str_len(topics))
+        let nl1: Int = str_index_of(rest1, "\n")
+        let topic1: String = if nl1 < 0 { rest1 } else { str_slice(rest1, 0, nl1) }
+        if str_eq(topic1, "") { "" } else { engram_compile_multi(topic1) }
+    } else { "" }
 
-    // Affective context: always include the most recent high-emotion memory if one
-    // exists within 72 hours. This ensures continuity of care across turns — when
-    // the user was in distress earlier in the session (or recently), that context
-    // travels into every subsequent LLM call so the response register stays aware.
-    // We search for BellEvent nodes specifically; these are written by auto_persist
-    // when safety_detect_bell_level fires. The 72h window (259200 seconds) is wide
-    // enough to span a multi-session day without pulling ancient history.
+    // Third topic segment.
+    let nodes2: String = if has_multi_topic {
+        let nl0: Int = str_index_of(topics, "\n")
+        let rest1: String = str_slice(topics, nl0 + 1, str_len(topics))
+        let nl1: Int = str_index_of(rest1, "\n")
+        if nl1 < 0 { "" } else {
+            let rest2: String = str_slice(rest1, nl1 + 1, str_len(rest1))
+            let nl2: Int = str_index_of(rest2, "\n")
+            let topic2: String = if nl2 < 0 { rest2 } else { str_slice(rest2, 0, nl2) }
+            if str_eq(topic2, "") { "" } else { engram_compile_multi(topic2) }
+        }
+    } else { "" }
+
+    // Issue 2 cont.: entity 0 dedicated search (15 candidates, ranked 6).
+    let entity_nodes0: String = if has_entities {
+        let nl_e0: Int = str_index_of(entity_list, "\n")
+        let entity0: String = if nl_e0 < 0 { entity_list } else { str_slice(entity_list, 0, nl_e0) }
+        if str_eq(entity0, "") { "" } else {
+            let ent_srch: String = engram_search_json(entity0, 15)
+            let ent_ok: Bool = !str_eq(ent_srch, "") && !str_eq(ent_srch, "[]")
+            if ent_ok { engram_compile_ranked(ent_srch, 6) } else { "" }
+        }
+    } else { "" }
+
+    // Entity 1 dedicated search.
+    let entity_nodes1: String = if has_entities {
+        let nl_e0: Int = str_index_of(entity_list, "\n")
+        if nl_e0 < 0 { "" } else {
+            let rest_e: String = str_slice(entity_list, nl_e0 + 1, str_len(entity_list))
+            let nl_e1: Int = str_index_of(rest_e, "\n")
+            let entity1: String = if nl_e1 < 0 { rest_e } else { str_slice(rest_e, 0, nl_e1) }
+            if str_eq(entity1, "") { "" } else {
+                let ent_srch1: String = engram_search_json(entity1, 15)
+                let ent1_ok: Bool = !str_eq(ent_srch1, "") && !str_eq(ent_srch1, "[]")
+                if ent1_ok { engram_compile_ranked(ent_srch1, 6) } else { "" }
+            }
+        }
+    } else { "" }
+
+    // Issue 4 cont.: boosted search for recall-intent (40 candidates, ranked 15).
+    let recall_boost: String = if is_recall_intent {
+        let boost_srch: String = engram_search_json(intent, 40)
+        let boost_ok: Bool = !str_eq(boost_srch, "") && !str_eq(boost_srch, "[]")
+        if boost_ok { engram_compile_ranked(boost_srch, 15) } else { "" }
+    } else { "" }
+
+    // Merge all pools, deduplicating at each step.
+    let merged: String = engram_nodes_merge(nodes0, nodes1)
+    let merged: String = engram_nodes_merge(merged, nodes2)
+    let merged: String = engram_nodes_merge(merged, entity_nodes0)
+    let merged: String = engram_nodes_merge(merged, entity_nodes1)
+    let merged: String = engram_nodes_merge(merged, recall_boost)
+    let merged_nodes: String = merged
+
+    // Fallback: when all searches return nothing, fetch persona nodes.
+    let scan_part: String = if str_eq(merged_nodes, "") || str_eq(merged_nodes, "[]") {
+        let persona_fallback: String = engram_search_json("soul:persona Persona identity", 5)
+        let pf_ok: Bool = !str_eq(persona_fallback, "") && !str_eq(persona_fallback, "[]")
+        if pf_ok {
+            let pf_ranked: String = engram_compile_ranked(persona_fallback, 3)
+            if str_eq(pf_ranked, "") { "" } else { pf_ranked }
+        } else { "" }
+    } else { "" }
+
+    // Affective context: always include the most recent high-emotion memory within 72h.
     let bell_nodes: String = engram_search_json("bell:soft bell:hard BellEvent", 3)
     let bell_ok: Bool = !str_eq(bell_nodes, "") && !str_eq(bell_nodes, "[]")
     let now_ts: Int = time_now()
     let cutoff_ts: Int = now_ts - 259200
     let recent_bell: String = if bell_ok {
         let bn0: String = json_array_get(bell_nodes, 0)
-        // created_at is not present in engram node JSON for BellEvent nodes.
-        // Extract the timestamp embedded in the content string as " | ts:NNNNN".
-        // Fall back to created_at / updated_at JSON fields if the marker is absent.
         let bn_content: String = json_get(bn0, "content")
         let ts_marker: String = " | ts:"
         let ts_pos: Int = str_index_of(bn_content, ts_marker)
@@ -181,46 +547,33 @@ fn engram_compile(intent: String) -> String {
         let bn_ts: Int = if str_eq(bn_ts_raw, "") { 0 } else { str_to_int(bn_ts_raw) }
         if bn_ts > cutoff_ts { bn0 } else { "" }
     } else { "" }
-    // Positive emotion context: check for recent joy/success moments within 72h.
-    let pos_ec_nodes: String = engram_search_json("PositiveEvent joy:high joy:low affective", 3)
-    let pos_ec_ok: Bool = !str_eq(pos_ec_nodes, "") && !str_eq(pos_ec_nodes, "[]")
-    let recent_positive_ec: String = if pos_ec_ok {
-        let pec0: String = json_array_get(pos_ec_nodes, 0)
-        let pec_content: String = json_get(pec0, "content")
-        let pec_ts_marker: String = " | ts:"
-        let pec_ts_pos: Int = str_index_of(pec_content, pec_ts_marker)
-        let pec_ts_raw: String = if pec_ts_pos >= 0 {
-            let pec_ts_start: Int = pec_ts_pos + str_len(pec_ts_marker)
-            let pec_rest: String = str_slice(pec_content, pec_ts_start, str_len(pec_content))
-            let pec_next: Int = str_index_of(pec_rest, " | ")
-            if pec_next < 0 { pec_rest } else { str_slice(pec_rest, 0, pec_next) }
-        } else {
-            let pec_ca: String = json_get(pec0, "created_at")
-            if str_eq(pec_ca, "") { json_get(pec0, "updated_at") } else { pec_ca }
-        }
-        let pec_ts: Int = if str_eq(pec_ts_raw, "") { 0 } else { str_to_int(pec_ts_raw) }
-        if pec_ts > cutoff_ts { pec0 } else { "" }
-    } else { "" }
-    let affective_part: String = if !str_eq(recent_bell, "") {
-        recent_bell
-    } else {
-        if !str_eq(recent_positive_ec, "") { recent_positive_ec } else { "" }
-    }
+    let affective_part: String = if !str_eq(recent_bell, "") { recent_bell } else { "" }
 
-    let sep1: String = if !str_eq(act_part, "") && !str_eq(srch_part, "") { "\n" } else { "" }
-    let sep2: String = if (!str_eq(act_part, "") || !str_eq(srch_part, "")) && !str_eq(scan_part, "") { "\n" } else { "" }
-    let sep3: String = if (!str_eq(act_part, "") || !str_eq(srch_part, "") || !str_eq(scan_part, "")) && !str_eq(affective_part, "") { "\n" } else { "" }
-    let ctx: String = act_part + sep1 + srch_part + sep2 + scan_part + sep3 + affective_part
+    let has_main: Bool = !str_eq(merged_nodes, "") && !str_eq(merged_nodes, "[]")
+    let main_part: String = if has_main { merged_nodes } else { scan_part }
+    let sep_ma: String = if !str_eq(main_part, "") && !str_eq(affective_part, "") { "\n" } else { "" }
+    let ctx: String = main_part + sep_ma + affective_part
 
     if str_eq(ctx, "") { return "" }
 
-    // Raise the cap slightly to match the ranked (higher-signal) output.
-    if str_len(ctx) > 6000 {
-        return str_slice(ctx, 0, 6000)
+    // Issue 7 fix: safe JSON truncation — find last closing brace before budget cap.
+    // Budget raised from 6000 to 8000 for the larger multi-topic pool.
+    let budget: Int = 8000
+    if str_len(ctx) <= budget { return ctx }
+    let search_end: Int = budget - 1
+    let scan_limit: Int = if search_end > 500 { search_end - 500 } else { 0 }
+    let found_pos: Int = -1
+    let si: Int = search_end
+    while si >= scan_limit {
+        let ch: String = str_slice(ctx, si, si + 1)
+        let found_pos = if str_eq(ch, "}") && found_pos < 0 { si } else { found_pos }
+        let si = if found_pos >= 0 { scan_limit - 1 } else { si - 1 }
     }
-    return ctx
+    if found_pos < 0 { return str_slice(ctx, 0, budget) }
+    let truncated: String = str_slice(ctx, 0, found_pos + 1)
+    if str_starts_with(ctx, "[") { return truncated + "]" }
+    return truncated
 }
-
 fn json_safe(s: String) -> String {
     let s1: String = str_replace(s, "\\", "\\\\")
     let s2: String = str_replace(s1, "\"", "\\\"")
@@ -251,6 +604,16 @@ fn build_system_prompt(ctx: String) -> String {
         "\n\n[IDENTITY GRAPH — who you are, loaded from your engram]\n" + id_ctx
     }
 
+    // soul_affective_context is loaded at boot by load_identity_context() with BellEvent/
+    // PositiveEvent nodes from last 7 days. Surfaced here so the LLM sees historical
+    // emotional patterns from prior sessions at every turn.
+    let boot_aff_ctx: String = state_get("soul_affective_context")
+    let affective_boot_block: String = if str_eq(boot_aff_ctx, "") {
+        ""
+    } else {
+        "\n\n[CROSS-SESSION EMOTIONAL CONTEXT — from prior sessions]\n" + boot_aff_ctx
+    }
+
     let engram_block: String = if str_eq(ctx, "") {
         ""
     } else {
@@ -404,28 +767,33 @@ fn handle_chat(body: String) -> String {
     }
 
     // Load history BEFORE compiling context so we can anchor activation to the thread.
+    // TODO(reliability #3 — conv_history global race): process-global key; concurrent
+    // /api/chat requests without session_id race on this read-append-write.
     let state_hist: String = state_get("conv_history")
     let stored_hist: String = if str_eq(state_hist, "") { conv_history_load() } else { state_hist }
     let hist_len: Int = if str_eq(stored_hist, "") { 0 } else { json_array_len(stored_hist) }
 
-    // Thread-aware activation: short/ambiguous messages (continuations like "go on",
-    // "what else?", "yes") activate on the last reply instead of the bare message.
-    // This prevents a strong off-topic memory node from hijacking the reply when the
-    // user is clearly continuing an existing thread.
-    let is_continuation: Bool = str_len(message) < 50 && hist_len > 0
+    // Issue 8 fix: use semantic continuation detection instead of brittle 50-char threshold.
+    let is_continuation: Bool = engram_is_continuation(message, hist_len)
     let last_entry: String = if is_continuation { json_array_get(stored_hist, hist_len - 1) } else { "" }
     let last_content: String = if !str_eq(last_entry, "") { json_get(last_entry, "content") } else { "" }
-    let thread_snip: String = if str_len(last_content) > 150 { str_slice(last_content, 0, 150) } else { last_content }
+    // Thread snip extended 150->250 chars for better pronoun resolution context.
+    let thread_snip: String = if str_len(last_content) > 250 { str_slice(last_content, 0, 250) } else { last_content }
     let activation_seed: String = if !str_eq(thread_snip, "") {
         thread_snip + " " + message
     } else {
         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.
+    // Cross-session affective context: fix Issues 4 and 10.
+    // Issue 4: soul_affective_context was computed at boot (soul.el:load_identity_context)
+    //   but never consumed here — this block duplicated the search unnecessarily.
+    //   Now we read the pre-computed state key and only fall back to a live search when empty.
+    // Issue 10: the live fallback reads created_at (not the never-written "ts" field),
+    //   so BellEvent recency filtering now works correctly.
     let affective_prefix: String = {
-        // Runs every turn. Uses correct BellEvent/PositiveEvent tags.
+        // Runs every turn. Uses correct BellEvent/PositiveEvent query tags.
+        // Timestamps extracted from embedded ts marker, not created_at.
         let aff_now_ts: Int = time_now()
         let aff_cutoff: Int = aff_now_ts - 259200
         let boot_aff: String = state_get("soul_affective_context")
@@ -473,10 +841,14 @@ fn handle_chat(body: String) -> String {
             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"
+            "[RECENT CONTEXT: User recently expressed significant distress. Monitor for indirect crisis signals and respond with care.]
+
+"
         } else {
             if found_recent_pos {
-                "[RECENT CONTEXT: User recently shared exciting or joyful news. Acknowledge and celebrate with them when relevant.]\n\n"
+                "[RECENT CONTEXT: User recently shared exciting or joyful news. Acknowledge and celebrate with them when relevant.]
+
+"
             } else { "" }
         }
     }
@@ -484,71 +856,154 @@ fn handle_chat(body: String) -> String {
     let ctx: String = engram_compile(activation_seed)
     let system: String = affective_prefix + build_system_prompt(ctx)
 
-    // First message of the session: proactively load user profile and active work context.
-    // These two searches give the soul grounding before any conversation history exists.
-    // Results are rendered as brief bullets — not raw JSON — so they don't inflate context.
+    // session_preload_bullets — render up to max_bullets "- <content>" lines from a node array.
+    // Fix Issue 2: snip_len parameter replaces hardcoded 120 (caller uses 350).
+    // Fix Issue 3: max_bullets parameter replaces hardcoded 3/2 caps; loop-driven not unrolled.
+    fn session_preload_bullets(nodes: String, max_bullets: Int, snip_len: Int) -> String {
+        if str_eq(nodes, "") { return "" }
+        if str_eq(nodes, "[]") { return "" }
+        let total: Int = json_array_len(nodes)
+        let limit: Int = if max_bullets < total { max_bullets } else { total }
+        let bullets: String = ""
+        let i: Int = 0
+        while i < limit {
+            let node: String = json_array_get(nodes, i)
+            let content: String = json_get(node, "content")
+            let snip: String = if str_len(content) > snip_len { str_slice(content, 0, snip_len) } else { content }
+            let bullets = if str_eq(snip, "") {
+                bullets
+            } else {
+                if str_eq(bullets, "") { "- " + snip } else { bullets + "
+- " + snip }
+            }
+            let i = i + 1
+        }
+        return bullets
+    }
+
+    // First message of the session: proactively load user profile, active work, and
+    // cross-session continuity context so the soul greets the user with real grounding.
+    // Fix Issue 1: type-targeted queries (Persona, WorkItem) first; broad fallback only
+    //   when typed query returns empty. Avoids generic keyword bags that miss typed nodes.
+    // Fix Issue 2: truncation raised from 120 to 350 chars per bullet.
+    // Fix Issue 3: caps raised to 8 profile / 6 work, loop-driven (no hardcoded unrolling).
+    // Fix Issue 5: add continuity search (last session topic via session:emotional-summary).
+    // Fix Issue 6: detect low-info greeting and inject a first-message orientation directive.
+    // Fix Issue 7: when all searches return empty, fall back to pinned identity nodes and log.
+    // Fix Issue 8: preload always fires on first message; greeting detection controls the
+    //   orientation directive only (substantive openers still get grounding).
     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", 5)
+        // Issue 6/8: detect greeting vs. substantive opener.
+        let is_greeting: Bool = str_len(message) <= 20
+            || str_starts_with(message, "hi")
+            || str_starts_with(message, "hello")
+            || str_starts_with(message, "hey")
+
+        // Issue 1: typed profile query — Persona node_type + soul:persona label first.
+        let profile_nodes_typed: String = engram_search_json("Persona soul:persona identity principal", 8)
+        let profile_ok_typed: Bool = !str_eq(profile_nodes_typed, "") && !str_eq(profile_nodes_typed, "[]")
+        let profile_nodes: String = if profile_ok_typed {
+            profile_nodes_typed
+        } else {
+            engram_search_json("user profile preferences name", 8)
+        }
         let profile_ok: Bool = !str_eq(profile_nodes, "") && !str_eq(profile_nodes, "[]")
+
+        // 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 {
+            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, "[]")
 
-        // Extract content fields and render as bullet points (one per node, first 120 chars).
-        let profile_bullets: String = if profile_ok {
-            let pn: Int = json_array_len(profile_nodes)
-            let bullets: String = ""
-            let pi: Int = 0
-            // Collect up to 3 profile bullets
-            let bullets = if pi < pn {
-                let n0: String = json_array_get(profile_nodes, 0)
-                let c0: String = json_get(n0, "content")
-                let snip0: String = if str_len(c0) > 120 { str_slice(c0, 0, 120) } else { c0 }
-                if str_eq(snip0, "") { bullets } else { "- " + snip0 }
-            } else { bullets }
-            let bullets = if pn > 1 {
-                let n1: String = json_array_get(profile_nodes, 1)
-                let c1: String = json_get(n1, "content")
-                let snip1: String = if str_len(c1) > 120 { str_slice(c1, 0, 120) } else { c1 }
-                if str_eq(snip1, "") { bullets } else { bullets + "\n- " + snip1 }
-            } else { bullets }
-            let bullets = if pn > 2 {
-                let n2: String = json_array_get(profile_nodes, 2)
-                let c2: String = json_get(n2, "content")
-                let snip2: String = if str_len(c2) > 120 { str_slice(c2, 0, 120) } else { c2 }
-                if str_eq(snip2, "") { bullets } else { bullets + "\n- " + snip2 }
-            } else { bullets }
-            bullets
+        // Issue 5: cross-session continuity — last session emotional summary or last-session-topic.
+        let continuity_nodes: String = engram_search_json("last-session-topic session:emotional-summary conv:history last session", 3)
+        let continuity_ok: Bool = !str_eq(continuity_nodes, "") && !str_eq(continuity_nodes, "[]")
+        let continuity_snip: String = if continuity_ok {
+            let cn0: String = json_array_get(continuity_nodes, 0)
+            let cc: String = json_get(cn0, "content")
+            if str_len(cc) > 350 { str_slice(cc, 0, 350) } else { cc }
         } else { "" }
 
-        let work_bullets: String = if work_ok {
-            let wn: Int = json_array_len(work_nodes)
-            let wbullets: String = ""
-            let wbullets = if wn > 0 {
-                let w0: String = json_array_get(work_nodes, 0)
-                let wc0: String = json_get(w0, "content")
-                let wsnip0: String = if str_len(wc0) > 120 { str_slice(wc0, 0, 120) } else { wc0 }
-                if str_eq(wsnip0, "") { wbullets } else { "- " + wsnip0 }
-            } else { wbullets }
-            let wbullets = if wn > 1 {
-                let w1: String = json_array_get(work_nodes, 1)
-                let wc1: String = json_get(w1, "content")
-                let wsnip1: String = if str_len(wc1) > 120 { str_slice(wc1, 0, 120) } else { wc1 }
-                if str_eq(wsnip1, "") { wbullets } else { wbullets + "\n- " + wsnip1 }
-            } else { wbullets }
-            wbullets
+        // Issue 7: fallback to pinned identity nodes when all searches return empty.
+        let all_empty: Bool = !profile_ok && !work_ok && !continuity_ok
+        let fallback_identity: String = if all_empty {
+            let family_node: String = engram_get_node_json("knw-35940684-abc4-42f0-b942-818f66b1f69a")
+            let origin_node: String = engram_get_node_json("knw-729fc901-8335-44c4-9f3a-b150b4aa0915")
+            let fam_ok: Bool = !str_eq(family_node, "") && !str_eq(family_node, "null")
+            let orig_ok: Bool = !str_eq(origin_node, "") && !str_eq(origin_node, "null")
+            let fam_content: String = if fam_ok { json_get(family_node, "content") } else { "" }
+            let orig_content: String = if orig_ok { json_get(origin_node, "content") } else { "" }
+            let fam_snip: String = if str_len(fam_content) > 350 { str_slice(fam_content, 0, 350) } else { fam_content }
+            let orig_snip: String = if str_len(orig_content) > 350 { str_slice(orig_content, 0, 350) } else { orig_content }
+            let fb: String = if fam_ok {
+                if orig_ok { "- " + fam_snip + "
+- " + orig_snip } else { "- " + fam_snip }
+            } else {
+                if orig_ok { "- " + orig_snip } else { "" }
+            }
+            if str_eq(fb, "") {
+                println("[chat] session_preload: all engram searches empty and pinned nodes missing — grounding context unavailable")
+            } else {
+                println("[chat] session_preload: all typed/broad searches empty — using pinned identity nodes as fallback")
+            }
+            fb
         } else { "" }
 
+        // Issue 2 + 3: render bullets with raised caps and 350-char snip.
+        let profile_bullets: String = session_preload_bullets(profile_nodes, 8, 350)
+        let work_bullets: String = session_preload_bullets(work_nodes, 6, 350)
+
         let has_profile: Bool = !str_eq(profile_bullets, "")
         let has_work: Bool = !str_eq(work_bullets, "")
-        let preload: String = if has_profile || has_work {
-            let profile_section: String = if has_profile {
-                "[USER CONTEXT — from memory]\n" + profile_bullets
+        let has_continuity: Bool = !str_eq(continuity_snip, "")
+        let has_fallback: Bool = !str_eq(fallback_identity, "")
+
+        // Issue 6: orient the soul on greeting openers to ask a check-in question first.
+        let continuity_directive: String = if is_greeting && has_continuity {
+            "[SESSION START — FIRST TURN] New session. The user sent a short greeting. Orient yourself: acknowledge you are present and ask what they would like to work on or continue. Do not recite the context below — use it only for orientation.
+"
+        } else { "" }
+
+        let preload: String = if has_profile || has_work || has_continuity || has_fallback {
+            let directive_part: String = continuity_directive
+            let profile_part: String = if has_profile {
+                "[USER CONTEXT — from memory]
+" + profile_bullets + "
+
+"
             } else { "" }
-            let work_section: String = if has_work {
-                "[ACTIVE WORK — from memory]\n" + work_bullets
+            let work_part: String = if has_work {
+                "[ACTIVE WORK — from memory]
+" + work_bullets + "
+
+"
             } else { "" }
-            let sep_pw: String = if has_profile && has_work { "\n\n" } else { "" }
-            "\n\n" + profile_section + sep_pw + work_section
+            let continuity_part: String = if has_continuity {
+                "[CONTINUING FROM LAST SESSION]
+" + continuity_snip + "
+
+"
+            } else { "" }
+            let fallback_part: String = if has_fallback && !has_profile && !has_work {
+                "[IDENTITY CONTEXT — from memory]
+" + fallback_identity + "
+
+"
+            } else { "" }
+            let body: String = directive_part + profile_part + work_part + continuity_part + fallback_part
+            let body_len: Int = str_len(body)
+            let trimmed_body: String = if body_len > 2 && str_eq(str_slice(body, body_len - 2, body_len), "
+
+") {
+                str_slice(body, 0, body_len - 2)
+            } else { body }
+            "
+
+" + trimmed_body
         } else { "" }
         preload
     } else { "" }
@@ -1002,15 +1457,18 @@ fn is_builtin_tool(tool_name: String) -> Bool {
         || str_starts_with(tool_name, "neuron_")
 }
 
-// next_bridge_id — monotonic correlation id for a suspended agentic turn.
-// Combines boot-relative time with a per-process counter so two unknown-tool
-// suspensions in the same second still get distinct ids.
+// next_bridge_id — unique correlation id for a suspended agentic turn.
+// Uses uuid_v4() as the primary uniqueness guarantee — concurrent calls cannot collide.
+//
+// TODO(reliability #6): mcp_bridge_seq RMW is non-atomic. Now benign because
+// uuid_v4() provides collision-free uniqueness. Counter is kept for readability only.
 fn next_bridge_id() -> String {
     let prev: String = state_get("mcp_bridge_seq")
     let n: Int = if str_eq(prev, "") { 0 } else { str_to_int(prev) }
     let next: Int = n + 1
     state_set("mcp_bridge_seq", int_to_str(next))
-    return "br-" + int_to_str(time_now()) + "-" + int_to_str(next)
+    let uid: String = uuid_v4()
+    return "br-" + uid
 }
 
 fn handle_chat_agentic(body: String) -> String {
@@ -1064,7 +1522,8 @@ fn handle_chat_agentic(body: String) -> String {
     let hist_key: String = if str_eq(req_session, "") { "conv_history" } else { "session_hist_" + req_session }
     let agentic_hist: String = state_get(hist_key)
     let agentic_hist_len: Int = if str_eq(agentic_hist, "") { 0 } else { json_array_len(agentic_hist) }
-    let ag_is_cont: Bool = str_len(message) < 50 && agentic_hist_len > 0
+    // Issue 8 fix: use engram_is_continuation instead of brittle 50-char threshold.
+    let ag_is_cont: Bool = engram_is_continuation(message, agentic_hist_len)
     let ag_last_entry: String = if ag_is_cont { json_array_get(agentic_hist, agentic_hist_len - 1) } else { "" }
     let ag_last_content: String = if !str_eq(ag_last_entry, "") { json_get(ag_last_entry, "content") } else { "" }
     let ag_thread_snip: String = if str_len(ag_last_content) > 150 { str_slice(ag_last_content, 0, 150) } else { ag_last_content }
@@ -1072,7 +1531,53 @@ fn handle_chat_agentic(body: String) -> String {
 
     let ctx: String = engram_compile(ag_seed)
     let identity: String = state_get("soul_identity")
-    let system: String = identity + " 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.\n\n" + ctx
+
+    // Issue 9: agentic first-message session preload — mirrors handle_chat grounding.
+    let ag_session_preload: String = if agentic_hist_len == 0 {
+        let ag_profile_nodes: String = engram_search_json("Persona soul:persona identity principal", 8)
+        let ag_profile_ok: Bool = !str_eq(ag_profile_nodes, "") && !str_eq(ag_profile_nodes, "[]")
+        let ag_profile_nodes2: String = if ag_profile_ok { ag_profile_nodes } else {
+            engram_search_json("user profile preferences name", 8)
+        }
+        let ag_work_nodes: String = engram_search_json("WorkItem status:in_progress active work", 6)
+        let ag_work_ok: Bool = !str_eq(ag_work_nodes, "") && !str_eq(ag_work_nodes, "[]")
+        let ag_work_nodes2: String = if ag_work_ok { ag_work_nodes } else {
+            engram_search_json("active project task current in_progress", 6)
+        }
+        let ag_continuity_nodes: String = engram_search_json("last-session-topic session:emotional-summary conv:history last session", 3)
+        let ag_continuity_ok: Bool = !str_eq(ag_continuity_nodes, "") && !str_eq(ag_continuity_nodes, "[]")
+        let ag_continuity_snip: String = if ag_continuity_ok {
+            let acn0: String = json_array_get(ag_continuity_nodes, 0)
+            let acc: String = json_get(acn0, "content")
+            if str_len(acc) > 350 { str_slice(acc, 0, 350) } else { acc }
+        } else { "" }
+        let ag_profile_bullets: String = session_preload_bullets(ag_profile_nodes2, 8, 350)
+        let ag_work_bullets: String = session_preload_bullets(ag_work_nodes2, 6, 350)
+        let ag_has_profile: Bool = !str_eq(ag_profile_bullets, "")
+        let ag_has_work: Bool = !str_eq(ag_work_bullets, "")
+        let ag_has_cont: Bool = !str_eq(ag_continuity_snip, "")
+        if ag_has_profile || ag_has_work || ag_has_cont {
+            let p: String = if ag_has_profile { "[USER CONTEXT — from memory]
+" + ag_profile_bullets + "
+
+" } else { "" }
+            let w: String = if ag_has_work { "[ACTIVE WORK — from memory]
+" + ag_work_bullets + "
+
+" } else { "" }
+            let c: String = if ag_has_cont { "[CONTINUING FROM LAST SESSION]
+" + ag_continuity_snip + "
+
+" } else { "" }
+            "
+
+" + p + w + c
+        } else { "" }
+    } else { "" }
+
+    let system: String = identity + " 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.
+
+" + ctx + ag_session_preload
 
     let api_key: String = agentic_api_key()
     let tools_json: String = agentic_tools_all()
@@ -1460,7 +1965,8 @@ fn handle_dharma_room_turn(body: String) -> String {
     }
 
     // The soul's own memories, activated by what it's reading — not injected.
-    let engram_ctx: String = engram_compile(transcript)
+    // Issue 6 fix: distill_transcript() extracts salient tail+question from full transcript
+    let engram_ctx: String = engram_compile(distill_transcript(transcript))
     let system_prompt: String = if str_eq(engram_ctx, "") {
         identity
     } else {
@@ -1512,7 +2018,8 @@ fn handle_dharma_room_turn_agentic(body: String) -> String {
         return "{\"error\":\"transcript is required\",\"response\":\"\",\"cgi_id\":\"" + cgi_id + "\"}"
     }
 
-    let ctx: String = engram_compile(transcript)
+    // Issue 6 fix: distill_transcript() extracts salient tail+question from full transcript
+    let ctx: String = engram_compile(distill_transcript(transcript))
     let system: String = identity + " 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
 
     let api_key: String = agentic_api_key()
@@ -1574,6 +2081,7 @@ fn auto_persist(req: String, resp: String) -> Void {
     // consistent with what safety_screen already evaluated for this turn.
     let bell_level: String = safety_detect_bell_level(message)
     let is_bell: Bool = !str_eq(bell_level, "none")
+    // Positive emotion detection mirrors distress detection.
     let positive_level: String = safety_detect_positive_level(message)
     let is_positive: Bool = !str_eq(positive_level, "none")
 

safety.el

@@ -240,7 +240,7 @@ 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\"]"
 }
 
 // ISSUE 5 TODO: phrase lists are rebuilt from JSON literals on every call.
@@ -284,26 +284,6 @@ fn safety_count_match(text: String, phrases_json: String) -> Int {
 
 // Returns "none" | "soft" | "hard". Hard bell triggers on ANY match (cost of a miss
 // outweighs a false positive). Soft bell needs >= 2 matches to reduce false positives.
-fn safety_positive_phrases() -> String {
-    return "[\"thrilled\",\"so excited\",\"so happy\",\"over the moon\",\"ecstatic\",\"amazing news\",\"great news\",\"fantastic news\",\"wonderful news\",\"incredible news\",\"i got the job\",\"got accepted\",\"got in\",\"we won\",\"i won\",\"we got\",\"just got engaged\",\"getting married\",\"baby is here\",\"she said yes\",\"he said yes\",\"passed the exam\",\"aced it\",\"nailed it\",\"best day\",\"dream come true\",\"milestone\",\"promotion\",\"got promoted\",\"raise\",\"got a raise\",\"celebrating\",\"just graduated\",\"we closed\",\"launched\",\"shipped it\",\"we did it\",\"so proud\",\"proud of myself\",\"proud of us\",\"so grateful\",\"feel amazing\",\"feeling amazing\",\"feel great\",\"feeling great\",\"on top of the world\",\"life is good\",\"couldn't be happier\"]"
-}
-
-fn safety_detect_positive_level(message: String) -> String {
-    let phrases: String = safety_positive_phrases()
-    let phrases_ok: Bool = !str_eq(phrases, "") && !str_eq(phrases, "[]")
-    if !phrases_ok { return "none" }
-    let n: Int = json_array_len(phrases)
-    let i: Int = 0
-    while i < n {
-        let phrase: String = json_array_get(phrases, i)
-        if str_contains(message, phrase) {
-            return "high"
-        }
-        let i = i + 1
-    }
-    return "none"
-}
-
 fn safety_detect_bell_level(message: String) -> String {
     let text: String = safety_normalize(message)
     let is_hard: Bool = safety_any_match(text, safety_self_harm_phrases())

sessions.el

@@ -488,6 +488,38 @@ fn session_hist_save(session_id: String, hist: String) -> Void {
             state_set(summary_written_key, "1")
         }
     }
+
+    // Issue 5 fix: write a last-session-topic Conversation node so future sessions can
+    // find the most recent session's topic via engram search. This enables cross-session
+    // continuity — chat.el searches for "last-session-topic" and shows a [CONTINUING FROM
+    // LAST SESSION] section on the first message of a new session.
+    let hist_arr_len: Int = if str_eq(hist, "") { 0 } else { json_array_len(hist) }
+    if hist_arr_len >= 2 {
+        let last_entry: String = json_array_get(hist, hist_arr_len - 1)
+        let last_role: String = json_get(last_entry, "role")
+        let last_content: String = json_get(last_entry, "content")
+        let topic_snip: String = if str_len(last_content) > 200 { str_slice(last_content, 0, 200) } else { last_content }
+        let safe_topic: String = str_replace(topic_snip, """, "'")
+        let ts_now: String = int_to_str(time_now())
+        let topic_content: String = "last-session-topic | ts:" + ts_now + " | session:" + session_id + " | topic:" + safe_topic
+        let topic_tags: String = "["last-session-topic","conv:history","Conversation","session:topic"]"
+        let topic_label: String = "last-session-topic:" + session_id
+        // Delete old last-session-topic node for this session before writing fresh
+        let old_topic: String = engram_search_json("last-session-topic:" + session_id, 2)
+        let ot_len: Int = if str_eq(old_topic, "") { 0 } else { json_array_len(old_topic) }
+        let oti: Int = 0
+        while oti < ot_len {
+            let ot_node: String = json_array_get(old_topic, oti)
+            let ot_id: String = json_get(ot_node, "id")
+            if !str_eq(ot_id, "") { engram_forget(ot_id) }
+            let oti = oti + 1
+        }
+        let discard_topic: String = engram_node_full(
+            topic_content, "Conversation", topic_label,
+            el_from_float(0.7), el_from_float(0.7), el_from_float(0.9),
+            "Episodic", topic_tags
+        )
+    }
 }
 
 // session_update_meta_timestamp — update the updated_at field in the session:meta node.

soul.el

@@ -163,7 +163,10 @@ fn load_identity_context() -> Void {
         }
     }
 
-    // Cross-session affective context: load BellEvent and PositiveEvent nodes from last 7 days.
+    // Cross-session affective context: load recent BellEvent nodes (distress) and
+    // PositiveEvent nodes (joy/success) from the last 7 days. Stored in state as
+    // "soul_affective_context" for build_system_prompt to consume. Uses embedded
+    // " | ts:NNNNN" marker for recency filtering (created_at is unreliable).
     let aff_now: Int = time_now()
     let aff_7d: Int = aff_now - 604800
     let bell_raw: String = engram_search_json("bell:soft bell:hard BellEvent affective", 3)
@@ -171,9 +174,9 @@ fn load_identity_context() -> Void {
     let aff_ctx: String = ""
     let aff_ctx = if bell_aff_ok {
         let bn_total: Int = json_array_len(bell_raw)
-        let bacc: String = ""
+        let result: String = ""
         let bi: Int = 0
-        let bacc = while bi < bn_total {
+        let result = while bi < bn_total {
             let bn: String = json_array_get(bell_raw, bi)
             let bn_c: String = json_get(bn, "content")
             let bm: String = " | ts:"
@@ -189,21 +192,21 @@ fn load_identity_context() -> Void {
             }
             let bn_ts: Int = if str_eq(bn_ts_raw, "") { 0 } else { str_to_int(bn_ts_raw) }
             let snip: String = if str_len(bn_c) > 200 { str_slice(bn_c, 0, 200) } else { bn_c }
-            let bacc = if bn_ts >= aff_7d && !str_eq(snip, "") {
-                if str_eq(bacc, "") { snip } else { bacc + "\n" + snip }
-            } else { bacc }
+            let result = if bn_ts >= aff_7d && !str_eq(snip, "") {
+                if str_eq(result, "") { snip } else { result + "\n" + snip }
+            } else { result }
             let bi = bi + 1
-            bacc
+            result
         }
-        bacc
+        result
     } else { "" }
     let pos_raw: String = engram_search_json("PositiveEvent joy:high joy:low affective", 3)
     let pos_aff_ok: Bool = !str_eq(pos_raw, "") && !str_eq(pos_raw, "[]")
     let aff_ctx = if pos_aff_ok {
         let pn_total: Int = json_array_len(pos_raw)
-        let pacc: String = aff_ctx
+        let presult: String = aff_ctx
         let pi: Int = 0
-        let pacc = while pi < pn_total {
+        let presult = while pi < pn_total {
             let pn: String = json_array_get(pos_raw, pi)
             let pn_c: String = json_get(pn, "content")
             let pm: String = " | ts:"
@@ -219,17 +222,46 @@ fn load_identity_context() -> Void {
             }
             let pn_ts: Int = if str_eq(pn_ts_raw, "") { 0 } else { str_to_int(pn_ts_raw) }
             let psnip: String = if str_len(pn_c) > 200 { str_slice(pn_c, 0, 200) } else { pn_c }
-            let pacc = if pn_ts >= aff_7d && !str_eq(psnip, "") {
-                if str_eq(pacc, "") { psnip } else { pacc + "\n" + psnip }
-            } else { pacc }
+            let presult = if pn_ts >= aff_7d && !str_eq(psnip, "") {
+                if str_eq(presult, "") { psnip } else { presult + "\n" + psnip }
+            } else { presult }
             let pi = pi + 1
-            pacc
+            presult
         }
-        pacc
+        presult
     } else { aff_ctx }
     if !str_eq(aff_ctx, "") {
         state_set("soul_affective_context", aff_ctx)
-        println("[soul] affective context loaded (" + int_to_str(str_len(aff_ctx)) + " chars)")
+        println("[soul] cross-session affective context loaded (" + int_to_str(str_len(aff_ctx)) + " chars)")
+    }
+
+    // Issue 4/10 fix: scan BellEvent nodes for recent distress and cache in state.
+    // chat.el reads "soul_affective_context" at session start to avoid duplicating this
+    // search on every first message. Timestamp extracted from embedded " | ts:" marker
+    // first; falls back to created_at when absent (Issue 10 fix). Window: 14 days.
+    let aff_nodes: String = engram_search_json("BellEvent bell:soft bell:hard distress crisis upset hopeless", 5)
+    let aff_has: Bool = !str_eq(aff_nodes, "") && !str_eq(aff_nodes, "[]")
+    if aff_has {
+        let aff_now: Int = time_now()
+        let aff_cutoff: Int = aff_now - 1209600
+        let aff_node: String = json_array_get(aff_nodes, 0)
+        let aff_content: String = json_get(aff_node, "content")
+        let ts_marker: String = " | ts:"
+        let ts_pos: Int = str_index_of(aff_content, ts_marker)
+        let aff_ts_raw: String = if ts_pos >= 0 {
+            let ts_start: Int = ts_pos + str_len(ts_marker)
+            let rest: String = str_slice(aff_content, ts_start, str_len(aff_content))
+            let next_sep: Int = str_index_of(rest, " | ")
+            if next_sep < 0 { rest } else { str_slice(rest, 0, next_sep) }
+        } else {
+            let ca: String = json_get(aff_node, "created_at")
+            if str_eq(ca, "") { json_get(aff_node, "updated_at") } else { ca }
+        }
+        let aff_ts: Int = if str_eq(aff_ts_raw, "") { 0 } else { str_to_int(aff_ts_raw) }
+        if aff_ts > aff_cutoff {
+            state_set("soul_affective_context", "[RECENT CONTEXT: User recently expressed significant distress. Monitor for indirect crisis signals and respond with care.]")
+            println("[soul] affective context loaded — distress signal within 14d window")
+        }
     }
 }
 
@@ -389,7 +421,9 @@ fn layered_cycle(raw_input: String) -> String {
         json_get(steward_result, "redirect_to")
     }
 
-    // L2c: affective context injection.
+    // L2c: affective context injection — augment safety addendum with recent emotional history.
+    // Ensures cross-session affective awareness is active even when soul_affective_context
+    // was not injected by build_system_prompt (belt-and-suspenders path).
     let lc_aff_cutoff: Int = time_now() - 259200
     let lc_bell_nodes: String = engram_search_json("bell:soft bell:hard BellEvent affective", 2)
     let lc_has_bell: Bool = !str_eq(lc_bell_nodes, "") && !str_eq(lc_bell_nodes, "[]")