| name | eval-triggers |
| description | Run the trigger evaluation pipeline — classify, analyze, and optionally compare against a baseline. Only run when explicitly asked — evals are expensive. |
| disable-model-invocation | true |
| metadata | {"internal":true} |
IMPORTANT: This skill is expensive (makes many LLM API calls). Only run when the user explicitly asks for it. Never run proactively.
Before running, ask the user which eval source to run unless they already specified it in $ARGUMENTS:
- Claude Code only — uses
run_trigger_eval.py --track claude
- Codex only — uses
run_trigger_eval.py --track codex
- Both — runs both tracks sequentially
Step 1 — Classify:
The runner writes to the canonical layout at evals/results/trigger/<skill>/<track>/<source>/results.json. You do not pass an output directory.
For Claude Code:
python3 evals/scripts/run_trigger_eval.py --track claude --source combined
For Codex:
python3 evals/scripts/run_trigger_eval.py --track codex
Step 2 — Analyze:
python3 evals/scripts/analyze_trigger_results.py \
--track claude --source frontmatter
This writes the cross-skill summary to evals/results/trigger/_summary/<track>/<source>/summary.{json,md}. Report:
- The gate verdict (pass/fail at F1 ≥ 0.90, with the list of skills below threshold).
- Per-skill precision, recall, F1.
- Any noteworthy false negatives / positives.
Step 3 — Compare (optional):
If the user provides a baseline summary or you have one from a previous run:
python3 evals/scripts/compare_trigger_runs.py \
--baseline <baseline-summary>.json \
--candidate evals/results/trigger/_summary/<track>/<source>/summary.json \
--output-markdown local/comparison.md
Summarize regressions and improvements. For ad-hoc baselines that should not be committed, store them under local/ (gitignored).
