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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.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/openai/openai-agents-python --skill test-coverage-improver명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
Analyze main branch implementation and configuration to find missing, incorrect, or outdated documentation in docs/. Use when asked to audit doc coverage, sync docs with code, or propose doc updates/structure changes. Only update English docs under docs/** and never touch translated docs under docs/ja, docs/ko, or docs/zh. Provide a report and ask for approval before editing docs.
Perform a risk-tiered zero-base final review loop before an implementation is declared complete. Use only when the user explicitly invokes $implementation-final-review or repository instructions authorize automatic invocation after implementation. Audit the complete merge-base diff for requirement fit, contract-surface coverage, await-boundary and lifecycle gaps, released compatibility, security, protocol, and persistence boundaries, unnecessary complexity, package and generated public surfaces, and adversarial test coverage; use compact self-contained reviewer packets and two concurrent no-history independent reviewers per round, defer broad final repository verification until review is clean and observable host capacity is available, preserve clean evidence for unchanged semantic components, close repeated root-cause groups instead of accumulating local patches, and enforce bounded review cycles in one task-global ledger.
Start and carry an explicitly invoked openai-agents-python implementation through a fresh isolated worktree and a local PR-ready handoff. Fetch the latest origin/main, keep task changes uncommitted, replay them onto the latest main before final review, run applicable verification and $implementation-final-review, use $pr-draft-summary to generate the complete PR draft and branch name, then create one clean local commit with takeover provenance when applicable. Use only when the user explicitly invokes this skill; never push, open a PR, or mutate GitHub.
SKILL.md 표시 중
| 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.