AGENT SKILL

model-routing-golden

Maintain model-routing audit golden fixtures and expected outputs.

License 许可
MIT
所属仓库
github/gh-aw
最近更新
2026-11-11
Stars
★ 5.6k
Forks
626

01 前言 Front Matter

name
model-routing-golden
description
Maintain model-routing audit golden fixtures and expected outputs.

03 SKILL.md 正文

Model-Routing Golden Fixtures

Use this skill when a model-routing golden test fails, analysis output changes intentionally, or a new routed workflow run needs coverage.

Verify

Run make verify-model-routing-golden (or python3 scripts/model-routing-golden.py --verify) before changing fixtures. Treat a mismatch as a behavior change to investigate, not a reason to regenerate immediately.

Refresh expected outputs

When analysis behavior intentionally changes, run make update-model-routing-golden. Review the complete diff for each expected*.json file and confirm that routing status, classifier attribution, AWF credits, token totals, warnings, and subagent costs match the intended behavior. Keep separate legacy goldens when missing artifacts cause documented information loss. Do not regenerate outputs merely to silence an unexplained failure.

Add or replace a fixture

Capture a run with:

python3 scripts/model-routing-golden.py --run <id-or-url> --case <case-name>

Use --replace only when intentionally updating an existing source run. The tool downloads through the local gh aw logs artifact path, minimizes and redacts its files, and refuses to write if analysis on the fixture differs from analysis on the full download. Use --source-dir to exercise capture against the synthetic downloaded-run fixture without GitHub access.

Add the case and its source scenario to modelRoutingGoldenCases and the fixture README. Then run make update-model-routing-golden, inspect all generated files, and run make verify-model-routing-golden. Retain the established file layout and logs/ ignore exception so raw proxy-log fixtures remain tracked.

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