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https://github.com/affaan-m/everything-claude-code.git
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8d360fb466
- Add top-level hooks wrapper to second JSON example (consistent with hooks.json format) - Extract hardcoded thresholds as module-level constants (WALL_OF_TEXT_WORDS, SUMMARY_CHECK_WORDS, SUMMARY_CHECK_FIRST_N, TASK_OUTPUT_RATIO_HIGH/MEDIUM) Skipped (not applicable): - 'Scoring defaults to 5/5' — by design for heuristic fallback; SKILL.md already documents pairing with LLM judge for production use - '--output silently ignored' — already fixed by _read_input refactor (checks args.output directly, not elif args.task and args.output)
65 lines
2.4 KiB
Markdown
65 lines
2.4 KiB
Markdown
# Hook Integration for Session-Stop Self-Evaluation
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Add this hook to `hooks/hooks.json` to remind the agent to self-evaluate at the end of every session (the hook echoes a reminder; it does not run the evaluator automatically):
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```json
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{
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"hooks": {
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"Stop": [
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{
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"hooks": [
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{
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"type": "command",
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"command": "echo '[Self-Eval] Session complete. Consider running agent-self-evaluation to rate your output.'"
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}
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],
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"description": "Remind agent to self-evaluate at session end"
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}
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]
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}
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}
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```
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`Stop` events do not require a `matcher` field (it is optional for `Stop`, `Notification`, `UserPromptSubmit`, and `SubagentStop` per `scripts/ci/validate-hooks.js`). If omitted, the hook object only needs `hooks` and metadata such as `description`.
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## Integration with the Python Evaluator
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The `scripts/evaluate.py` script can be used as a standalone tool:
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```bash
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# Pipe agent output directly
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echo "Your agent response here" | python3 skills/agent-self-evaluation/scripts/evaluate.py
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# From files
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python3 skills/agent-self-evaluation/scripts/evaluate.py --task task.txt --output response.txt
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```
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To integrate it into hooks, capture the last agent output to a file first, then run the evaluator. For lightweight reminders after shell-based verification, use a simple supported matcher string:
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```json
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{
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"hooks": {
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"PostToolUse": [
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{
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"matcher": "Bash",
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"hooks": [
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{
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"type": "command",
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"command": "echo '[Self-Eval] If this command completed verification for a non-trivial task, consider running agent-self-evaluation.'"
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}
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],
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"description": "Remind agent to self-evaluate after shell verification"
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}
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]
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}
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}
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```
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This avoids documenting unsupported command-expression matcher syntax. If your harness supports command-level matcher expressions, prefer a word-boundary regex such as `\b(pytest|npm test|go test)\b` rather than a broad `test` substring.
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These hooks are opt-in. Add them to your local `hooks/hooks.json` if you want automated evaluation prompts.
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## Manual Usage (Recommended)
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The most reliable approach is manual invocation — the agent runs self-evaluation as part of its workflow when the `agent-self-evaluation` skill is active, without requiring hook configuration. The skill's "When to Activate" section already covers trigger conditions (multi-file changes, debugging sessions, design documents).
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