# Speck Self Eval

> Scores seeded defects against Speck gates. Use only in the Speck source repo before changing methodology gates.

- Skill: `telum-ai/speck-self-eval` (Agent Skill)
- Install (CLI): `npx skillmds@latest add telum-ai/speck-self-eval`
- Raw SKILL.md: https://api.skillmd.com/api/skills/telum-ai/speck-self-eval/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: telum-ai (https://skillmd.com/u/telum-ai)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/telum-ai/speck-self-eval

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# Speck self-eval (A1-lite)

Runs seeded artifacts through the candidate-corpus gate anchors and deterministic defect evaluator. Use before changing named Speck gate capabilities. This is a contract smoke test, not runtime agent-behavior proof.

Framework-repository-only: if `tests/eval/score.sh` or its immutable baseline is absent, STOP. Do not fabricate or copy a scorecard into a product repository.

## Do

1. Run `bash tests/eval/score.sh --check` while iterating; it must exit nonzero on a harness error, wrong fixture verdict, or regression from `reports/baseline.json`.
2. Read stdout + `tests/eval/reports/latest.md`.
3. Run `bash tests/eval/score.test.sh`; require the corpus-deletion and wrong-verdict mutations to turn red.
4. After the candidate is final, run `bash tests/eval/score.sh` once to refresh `latest.md`. Never rewrite `baseline.json` as a side effect of scoring.

## Output

Fail-closed scorecard with per-fixture verdicts, harness-error count, and immutable-baseline regressions.