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