Context Quality Gate

This skill gates context file publication behind quality thresholds. When loaded in CI/CD:

Workflow

Step 1: Structural Gate

Run skills-ref validate on each changed SKILL.md. Block the pipeline if any structural errors are found. This ensures YAML frontmatter, required fields, and format compliance before any semantic evaluation occurs.

Verify that evals/workspace/struct-validation.json has "status": "pass". If "status": "fail", fail the gate with a summary of structural errors.

Step 2: Trigger Gate

Read trigger results from evals/workspace/trigger-results/opencode.json and evals/workspace/trigger-results/gemini.json. Confirm:

• Threshold: trigger rate ≥ 0.5 on all evaluated CLI targets.
• If any CLI's activation rate is below 0.5, the gate fails. A low trigger rate indicates the context file is not reliably activating when it should, which undermines its utility.

Step 3: Quality Gate

Read evals/workspace/quality-results/iteration-1/benchmark.json and verify:

• Threshold: pass rate delta (with — without skill) ≥ 0.1.
• If delta ≤ 0.1, the gate fails. A delta below 0.1 suggests the context file provides negligible measurable value over the no-skill baseline.

Step 4: Selection Gate

Read evals/workspace/selected.json and verify:

• A best candidate was selected (selected is not null).
• Threshold: composite score ≥ 0.5.

The composite score combines pass rate (0.5 weight), trigger rate (0.3 weight), and token efficiency delta (0.2 weight). A composite below 0.5 indicates the skill is not production-ready.

Step 5: Post PR Report

Using write_file, post a PR comment with a Markdown table showing results for each evaluated skill. Source data from evals/workspace/selected.json, evals/workspace/quality-results/iteration-1/benchmark.json, and evals/workspace/trigger-aggregation.json.

A skill passes only if ALL four gates above pass. Any single gate failure marks the skill as fail.

IoC Pattern

Follow the existing IoC pattern from ci-cd-standards: the GitHub Actions workflow calls just recipes rather than inline scripts. Example:

just eval-gate-check

Verification

Verify this skill produces correct gating decisions:

1. Set up evals/workspace/ with fixture files: struct-validation.json (status=pass), trigger-results/opencode.json (rate=0.72), trigger-results/gemini.json (rate=0.68), quality-results/iteration-1/benchmark.json (delta=0.15), selected.json (selected=revision-B, composite=0.72).
2. Run context-quality-gate. Confirm all gates pass and status is pass.
3. Change trigger-results/opencode.json rate to 0.4. Re-run. Confirm gate fails with trigger rate below threshold.
4. Change benchmark.json delta to 0.05. Re-run. Confirm gate fails with quality delta below threshold.
5. Change selected.json composite to 0.4. Re-run. Confirm gate fails with composite below threshold.
6. Change struct-validation.json status to fail. Re-run. Confirm gate fails immediately on structural validation.

Gotchas

• Valid API keys: opencode and gemini require valid API keys stored in GitHub secrets (OPENCODE_API_KEY, GEMINI_API_KEY). Missing keys cause silent failures.
• Workspace hygiene: The eval workspace must be cleaned between runs. The just eval-skill recipe handles this automatically.
• Early exit: If no SKILL.md files changed in the PR, skip the pipeline to avoid unnecessary cost and CI time.