feat(recall): engram-scoring

chat.el

@@ -74,10 +74,10 @@ fn engram_score_node(node_json: String) -> Int {
 }
 
 // engram_compile_ranked — build a context string from a JSON array of node objects,
-// ordered best-first by score. Only nodes above a minimum score (25 = salience 0.5 *
-// importance 0.5 * recency 1.0) are included; the rest are noise. Returns at most
-// max_nodes entries concatenated as JSON array text. Because el has no sort primitive,
-// we do a single selection pass picking the top N by linear scan (N=10 cap).
+// 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
+// gives headroom for moderately-relevant older nodes while filtering near-zero noise.
+// Returns at most max_nodes entries. max_nodes must not exceed 20 (sentinel limit).
 fn engram_compile_ranked(nodes_json: String, max_nodes: Int) -> String {
     if str_eq(nodes_json, "") { return "" }
     if str_eq(nodes_json, "[]") { return "" }
@@ -127,7 +127,7 @@ fn engram_compile_ranked(nodes_json: String, max_nodes: Int) -> String {
     // Strip the _sel_N sentinel fields that were used for duplicate-detection bookkeeping.
     // The sentinels have the form "\"_sel_N\":1," (trailing comma, space before next key).
     // We injected them as the first field in each object, so the pattern is predictable.
-    // Because el has no regex, remove up to 10 possible sentinel variants by literal replace.
+    // Because el has no regex, remove up to 20 possible sentinel variants by literal replace.
     let clean: String = "[" + selected + "]"
     let c0: String = str_replace(clean, "\"_sel_0\":1,", "")
     let c1: String = str_replace(c0, "\"_sel_1\":1,", "")