feat(recall): context-format

chat.el

@@ -73,6 +73,181 @@ fn engram_score_node(node_json: String) -> Int {
     return salience_100 * importance_100 * recency_100 / 10000
 }
 
+// engram_render_node — render a single engram node JSON object as a human-readable
+// bullet line for inclusion in the system prompt. Format: - [TYPE age salience] content
+// Fixes Issue #1, #4: content extraction from raw JSON nodes.
+// Fixes Issue #3: age and salience annotations surface staleness/confidence to LLM.
+fn engram_render_node(node_json: String) -> String {
+    if str_eq(node_json, "") { return "" }
+    let content: String = json_get(node_json, "content")
+    if str_eq(content, "") { return "" }
+    let node_type: String = json_get(node_json, "node_type")
+    let type_label: String = if str_eq(node_type, "") { "mem" } else { node_type }
+    let now_ts: Int = time_now()
+    let created_str: String = json_get(node_json, "created_at")
+    let updated_str: String = json_get(node_json, "updated_at")
+    let ts_raw: String = if str_eq(created_str, "") { updated_str } else { created_str }
+    let age_label: String = if str_eq(ts_raw, "") { "" } else {
+        let node_ts: Int = str_to_int(ts_raw)
+        let age_secs: Int = now_ts - node_ts
+        let age_days: Int = if age_secs < 0 { 0 } else { age_secs / 86400 }
+        if age_days == 0 { "today" } else {
+            if age_days > 30 { "old" } else { int_to_str(age_days) + "d ago" }
+        }
+    }
+    let salience_str: String = json_get(node_json, "salience")
+    let sal_100: Int = if str_eq(salience_str, "") { 0 } else {
+        let s: Int = str_to_int(str_replace(salience_str, ".", ""))
+        if s > 100 { 100 } else { if s < 0 { 0 } else { s } }
+    }
+    let salience_hint: String = if str_eq(salience_str, "") { "" } else {
+        if sal_100 >= 80 { "high" } else { if sal_100 >= 50 { "med" } else { "low" } }
+    }
+    let ann_inner: String = type_label
+    let ann_inner = if str_eq(age_label, "") { ann_inner } else { ann_inner + " " + age_label }
+    let ann_inner = if str_eq(salience_hint, "") { ann_inner } else { ann_inner + " " + salience_hint }
+    let ann: String = "[" + ann_inner + "]"
+    let snip: String = if str_len(content) > 200 { str_slice(content, 0, 200) } else { content }
+    return "- " + ann + " " + snip
+}
+
+// engram_render_nodes — render a JSON array of nodes as newline-joined bullet lines.
+fn engram_render_nodes(nodes_json: String) -> String {
+    if str_eq(nodes_json, "") { return "" }
+    if str_eq(nodes_json, "[]") { return "" }
+    let total: Int = json_array_len(nodes_json)
+    if total == 0 { return "" }
+    let result: String = ""
+    let i: Int = 0
+    while i < total {
+        let node: String = json_array_get(nodes_json, i)
+        let line: String = engram_render_node(node)
+        let result = if str_eq(line, "") { result } else {
+            if str_eq(result, "") { line } else { result + "\n" + line }
+        }
+        let i = i + 1
+    }
+    return result
+}
+
+// engram_dedup_nodes — deduplicate a merged JSON node array by id / content fingerprint.
+// Fixes Issue #2: prevents same node appearing from both activation and search passes.
+fn engram_dedup_nodes(nodes_json: String) -> String {
+    if str_eq(nodes_json, "") { return "" }
+    if str_eq(nodes_json, "[]") { return "" }
+    let total: Int = json_array_len(nodes_json)
+    if total == 0 { return "" }
+    let seen_keys: String = ""
+    let result: String = ""
+    let i: Int = 0
+    while i < total {
+        let node: String = json_array_get(nodes_json, i)
+        let node_content: String = json_get(node, "content")
+        let node_id: String = json_get(node, "id")
+        let dedup_key: String = if str_eq(node_id, "") {
+            if str_len(node_content) > 80 { str_slice(node_content, 0, 80) } else { node_content }
+        } else { node_id }
+        let key_marker: String = "|" + dedup_key + "|"
+        let already_seen: Bool = str_contains(seen_keys, key_marker)
+        let seen_keys = if already_seen { seen_keys } else { seen_keys + key_marker }
+        let result = if already_seen { result } else {
+            if str_eq(result, "") { node } else { result + "," + node }
+        }
+        let i = i + 1
+    }
+    if str_eq(result, "") { return "" }
+    return "[" + result + "]"
+}
+
+// engram_compile_ranked — build a ranked list of nodes, best-first by score.
+// Fix (Issue #11): uses "|N|" index tracking instead of _sel_N JSON mutation,
+// which leaked sentinel fields into the node objects passed to the LLM.
+fn engram_compile_ranked(nodes_json: String, max_nodes: Int) -> String {
+    if str_eq(nodes_json, "") { return "" }
+    if str_eq(nodes_json, "[]") { return "" }
+    let total: Int = json_array_len(nodes_json)
+    if total == 0 { return "" }
+    let selected_indices: String = ""
+    let selected_nodes: String = ""
+    let pass: Int = 0
+    while pass < max_nodes && pass < total {
+        let best_idx: Int = -1
+        let best_score: Int = -1
+        let ci: Int = 0
+        while ci < total {
+            let node: String = json_array_get(nodes_json, ci)
+            let score: Int = engram_score_node(node)
+            // Threshold: includes moderately-relevant older nodes (score >= 15).
+            let above_thresh: Bool = score >= 15
+            let idx_marker: String = "|" + int_to_str(ci) + "|"
+            let already_picked: Bool = str_contains(selected_indices, idx_marker)
+            let is_better: Bool = score > best_score && above_thresh && !already_picked
+            let best_score = if is_better { score } else { best_score }
+            let best_idx = if is_better { ci } else { best_idx }
+            let ci = ci + 1
+        }
+        if best_idx < 0 {
+            let pass = total  // break
+        } else {
+            let chosen: String = json_array_get(nodes_json, best_idx)
+            let sep: String = if str_eq(selected_nodes, "") { "" } else { "," }
+            let selected_nodes = selected_nodes + sep + chosen
+            let selected_indices = selected_indices + "|" + int_to_str(best_idx) + "|"
+        }
+        let pass = pass + 1
+    }
+    if str_eq(selected_nodes, "") { return "" }
+    return "[" + selected_nodes + "]"
+}ory.el"
+
+fn chat_default_model() -> String {
+    let m: String = state_get("soul_model")
+    if !str_eq(m, "") {
+        return m
+    }
+    let e: String = env("SOUL_LLM_MODEL")
+    if !str_eq(e, "") {
+        return e
+    }
+    return "claude-sonnet-4-5"
+}
+
+// engram_score_node — compute a recency x relevance score for a single engram
+// node JSON object. Higher is better. Score = salience * importance * recency_factor.
+// recency_factor decays linearly over 30 days: nodes updated today score 1.0,
+// nodes 30+ days old score 0.1 (floor). Nodes with no created_at score 0.5.
+// This keeps fresh, high-salience nodes at the top and pushes stale low-signal
+// nodes to the bottom so they get trimmed when we cap context size.
+fn engram_score_node(node_json: String) -> Int {
+    let salience_str: String = json_get(node_json, "salience")
+    let importance_str: String = json_get(node_json, "importance")
+    let created_str: String = json_get(node_json, "created_at")
+
+    // Parse as floats via * 100 integer arithmetic (el has no float math)
+    let salience_100: Int = if str_eq(salience_str, "") { 70 } else {
+        let s: Int = str_to_int(str_replace(salience_str, ".", ""))
+        // Clamp to 0-100 range (value was e.g. "0.85" -> parsed "085" = 85)
+        if s > 100 { 100 } else { if s < 0 { 0 } else { s } }
+    }
+    let importance_100: Int = if str_eq(importance_str, "") { 70 } else {
+        let v: Int = str_to_int(str_replace(importance_str, ".", ""))
+        if v > 100 { 100 } else { if v < 0 { 0 } else { v } }
+    }
+
+    // Recency: decay from 100 (today) to 10 (30+ days). created_at is Unix seconds.
+    let now_ts: Int = time_now()
+    let recency_100: Int = if str_eq(created_str, "") { 50 } else {
+        let created_ts: Int = str_to_int(created_str)
+        let age_secs: Int = now_ts - created_ts
+        let age_days: Int = age_secs / 86400
+        let decay: Int = if age_days >= 30 { 10 } else { 100 - (age_days * 3) }
+        if decay < 10 { 10 } else { decay }
+    }
+
+    // Combined score 0-1000000 (no floats): salience * importance * recency / 10000
+    return salience_100 * importance_100 * recency_100 / 10000
+}
+
 // engram_compile_ranked — build a context string from a JSON array of node objects,
 // ordered best-first by score. Only nodes above threshold=15 are included.
 // With corrected parsing: sal=0.5 * imp=0.5 at max recency scores 25; threshold 15