菜单
Improve test coverage in the OpenAI Agents Python repository: run `make coverage`, inspect coverage artifacts, identify low-coverage files, propose high-impact tests, and confirm with the user before writing tests.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | test-coverage-improver |
| description | Improve test coverage in the OpenAI Agents Python repository: run `make coverage`, inspect coverage artifacts, identify low-coverage files, propose high-impact tests, and confirm with the user before writing tests. |
Use this skill whenever coverage needs assessment or improvement (coverage regressions, failing thresholds, or user requests for stronger tests). It runs the coverage suite, analyzes results, highlights the biggest gaps, and prepares test additions while confirming with the user before changing code.
make coverage to regenerate .coverage data and coverage.xml..coverage and coverage.xml, plus the console output from coverage report -m for drill-downs.tests/, rerun make coverage, and then run $code-change-verification before marking work complete.make coverage at repo root. Avoid watch flags and keep prior coverage artifacts only if comparing trends.coverage report -m for file-level totals; fallback to coverage.xml for tooling or spreadsheets.uv run coverage html to generate htmlcov/index.html if you need an interactive drill-down.src/agents/ before examples or docs.tests/ and avoid flaky async timing.scripts/, references/, or assets/ unless needed later.pnpm test:coverage instead of guessing.Create the required PR-ready summary block, branch suggestion, title, and draft description for openai-agents-python. Use before the final response whenever the current task changed runtime code, tests, examples, build/test configuration, or docs with behavior impact, regardless of perceived change size and including local-only or uncommitted work. Skip only for trivial or conversation-only tasks, repo-meta/doc-only tasks without behavior impact, or when the user explicitly says not to include the PR draft block.
Decide how to implement runtime and API changes in openai-agents-python before editing code. Use when a task changes exported APIs, runtime behavior, serialized state, tests, or docs and you need to choose the compatibility boundary, whether shims or migrations are warranted, and when unreleased interfaces can be rewritten directly.
Run python examples in auto mode with logging, rerun helpers, and background control.
Fix the tiny credit-note formatting bug and rerun the exact targeted test command.
Build a concise prior authorization packet from local case files and payer policy docs.
Use when the task requires capturing or automating a real browser from the terminal.