ktg-plugin-marketplace/plugins/ultraplan-local/skills/cc-architect-catalog/hooks-observability-pattern.md
Kjell Tore Guttormsen 4bbd17cbfa feat(ultraplan-local): v2.3.1 — qualified slug convention for cc-architect-catalog
Resolves v2.3.0 dogfood collision: skill-factory produced a
specialized hooks-pattern.md draft that would have overwritten the
generic seed. Qualified slugs let one feature host multiple named
patterns at different abstraction levels.

Slug convention: <cc_feature>[-<qualifier>]-<layer>.md. Unqualified =
canonical baseline. Qualified = sub-pattern (e.g., hooks-observability-
pattern.md) that does not displace the baseline.

Changes:
- SKILL.md: slug convention section, coverage-table qualified column,
  matcher logic for N patterns per feature, modification rules cover
  qualified-vs-canonical choice and collision handling.
- feature-matcher: catalog map is cc_feature -> {layer -> [skills]};
  selection rules (baseline by default, qualified when justified,
  multi-skill when non-overlapping); supporting_skill accepts list.
- gap-identifier: adds pattern_count[cc_feature] to coverage audit.
- architecture-critic: supporting-skill verification — every cited
  skill name must exist in the catalog (blocker severity).
- First qualified skill: hooks-observability-pattern.md (promoted from
  .drafts/, source ai-psychosis/README.md, ngram-overlap 0.01).
- Version bump 2.3.0 -> 2.3.1 across plugin.json, badges, table, root
  CLAUDE.md, CHANGELOG.

Non-breaking: existing unqualified slugs keep working, no cc_feature
taxonomy changes, hallucination gate unchanged.
2026-04-18 17:53:55 +02:00

3.3 KiB

name description layer cc_feature source concept last_verified ngram_overlap_score review_status
hooks-observability-pattern Observe user-interaction patterns across session lifecycle hooks and emit cooldown-gated nudges pattern hooks ../../../../ai-psychosis/README.md progressive alerts via lifecycle hooks 2026-04-18 0.01 approved

Hooks — Progressive-Alert Observability Pattern

Use this when

  • Measure behaviour the model itself cannot see: cadence, duration, repetition, time-of-day.
  • Surface soft nudges rather than hard blocks — the operator keeps the final call.
  • Separate "what happened" (metrics) from "what was said" (prompt text) so no conversation content touches disk.

Shape

  • Wire four lifecycle events: a start handler for baseline counters, a prompt handler for language-category flags, a tool handler for cadence and burst detection, and an end handler for totals and state cleanup.
  • Keep per-session counters in a tiny JSON file under the plugin data dir; keep aggregate events in an append-only JSONL log for later reporting.
  • Gate every nudge behind two things: a threshold (hard or soft) and a cooldown window, so repeat alerts do not spam the transcript.
  • Deliver alerts as additionalContext injection, never as a tool block — the goal is awareness, not control.

Forces

  • Privacy vs. signal. Richer signal wants more content logged; the user wants none. Resolve by computing boolean flags in-memory and discarding the raw text before the handler returns.
  • Latency budget. Handlers fire on every prompt and every tool call. Stay well under 100 ms per invocation; append-only JSONL is sub-millisecond and safe.
  • Portability. Hooks that assume a shell, jq, or npm dependencies break on half the operator fleet. Stick to Node stdlib so the same script runs on macOS, Linux, and Windows.
  • Instruction layer alone is not enough. Behavioural rules in a skill file shape tone but cannot measure duration or frequency. Layer the hook observability on top of the skill — each compensates for the other.

Gotchas

  • A handler that crashes blocks the turn. Catch everything, log, and exit zero by default.
  • Cooldowns must be per-category, not global, or the most-triggered alert silences the rarer, more informative ones.
  • Late-night and rapid-fire thresholds are legitimate signals but also easy to over-tune; start with generous bands and tighten only with data.
  • additionalContext from an end-of-session handler is discarded — inject alerts on start, prompt, or tool events where the model will actually see them.

Anti-patterns

  • Storing prompt text or tool arguments "just for debugging" — once it is on disk, the privacy guarantee is gone.
  • Treating every elevated metric as an intervention. If the hook starts blocking, the operator works around it and loses the awareness benefit.
  • Hardcoding thresholds into the handler. Pull them from a single config so future tuning does not require a rewrite of four scripts.

Decision quick-check

Reach for this pattern when you need visibility into how the user is interacting, not what they are saying, and when the response should be a gentle nudge rather than a gate. Otherwise use a PreToolUse denylist (hard limit) or a skill-only instruction layer (style, not cadence).