feat(telemetry): the preload emits, and the always-on set stops being unfalsifiable (#3473)

The ranked rule arm became measurable in M333. The preload did not — and that is the surface whose value is actually in question. `list_always_on_rules`, the SessionStart block and every `rules_payload` caller handed rules over wholesale and emitted nothing, so the resident set's token cost was certain and its usefulness could not be tested even in principle. Bulk deliveries now record as AMBIENT, beside the ranked count and never inside pull-through. Folding them in would mean growing the always-on set depressed the arm's measured precision and trimming it flattered the arm, neither for any reason to do with the arm. `RANKED_SOURCES` inverts the note twin's `AMBIENT_SOURCES` deliberately: there is one ranked rule source and this change adds seven bulk ones, so naming the rare half makes a forgotten surface default to ambient — under-counting it — rather than padding the denominator with surfacings nobody chose. Two lookalike call sites are deliberately left silent, with a test to keep them that way: the write-path etag arm and `rules_etag_for` read the rules to build or compare a MARKER and show nobody anything. No migration — `event` and `source` are plain Text with no CHECK (rule 36 does not apply). Snippet #2858 updated to the new `rules_payload` contract. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011cPyzNnegXHr5iRMzzy5KJ
2026-09-02 23:06:40 -04:00
parent 6627cfc2f0
commit 8b9b3a1d9b
14 changed files with 505 additions and 48 deletions
@@ -103,7 +103,7 @@ async def get_task(task_id: int) -> dict:
        applicable = await rulebooks_svc.get_applicable_rules(
            project_id=note.project_id, user_id=uid,
        )
-        data.update(rulebooks_svc.rules_payload(applicable))
+        data.update(rulebooks_svc.rules_payload(applicable, user_id=uid, source="get_task"))
    data.update(await access_svc.describe_provenance(uid, note))
    # Same reasoning as get_note's record_pulled, and this is the tool where it
    # matters MOST: auto-inject ranks kind-blind over a corpus that is