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Add structured 5-axis self-evaluation framework for agent output quality: - Accuracy, Completeness, Clarity, Actionability, Conciseness - Evidence-based scoring with concrete improvement suggestions - Standalone Python evaluator script with keyword heuristics - Detailed scoring anchors reference guide - High-score and low-score annotated examples - Reusable evaluation report template - Optional hook integration for session-stop evaluation Agent persona (agent-evaluator) provides a dedicated subagent for applying the rubric to agent output with tool-backed verification. All files tested: Python script runs, examples score correctly (high 4.2, low 3.4), frontmatter parses clean, 183 lines (under 500).
60 lines
1.8 KiB
Markdown
60 lines
1.8 KiB
Markdown
# Hook Integration for Session-Stop Self-Evaluation
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Add this hook to `hooks/hooks.json` to automatically trigger self-evaluation at the end of every session:
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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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"matcher": "true",
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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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## 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:
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```json
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{
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"PostToolUse": [
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{
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"matcher": "tool == \"Bash\" && tool_input.command matches \"(test|pytest|npm test|go test)\"",
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"hooks": [
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{
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"type": "command",
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"command": "echo '[Self-Eval] Tests completed. Consider running agent-self-evaluation.'"
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}
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],
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"description": "Remind agent to self-evaluate after test runs"
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}
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]
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}
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```
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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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