菜单
Improve test coverage in the OpenAI Agents JS monorepo: run `pnpm test:coverage`, inspect coverage artifacts, identify low-coverage files and branches, 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
Run the mandatory verification stack when changes affect runtime code, tests, or build/test behavior in the OpenAI Agents JS monorepo.
Plan and execute runtime-behavior investigations with temporary TypeScript probe scripts, validation matrices, state controls, and findings-first reports. Use only when the user explicitly invokes this skill to verify actual runtime behavior beyond normal code-level checks, especially to uncover edge cases, undocumented behavior, or common failure modes in local or live integrations. A baseline smoke check is fine as an entry point, but do not stop at happy-path confirmation.
Review a GitHub issue or pull request URL as an openai-agents-js maintainer, with a staged assessment of whether the claim is real, practically important, already solvable with supported functionality, correctly scoped, better served by another design, and worth maintainer and contributor effort. Use when assessing issue validity or severity, deciding whether an issue should be prioritized or closed, determining whether a requested feature represents an unmet need rather than a discoverability or usage gap, judging whether a PR is worth bringing to mergeable quality, comparing open PRs or alternative designs, separating code quality from repository readiness, or drafting a concise maintainer assessment. When closure, additional evidence, or code changes should be requested, also produce a polite, concise, complete, copy-paste-ready maintainer comment.
Run examples:start-all in auto mode with parallel execution, per-script logs, and start/stop helpers.
Create the required PR-ready summary block, branch suggestion, title, and draft description for openai-agents-js. Must be used before the final response whenever the actual task diff includes runtime code, tests, examples, build/test configuration, or docs with behavior impact, regardless of perceived change size. Skip only when no eligible files changed, every change is repo-meta or docs-only without behavior impact, the task is conversation-only, or the user explicitly opts out.
Decide how to implement runtime and API changes in openai-agents-js before editing code. Use when a task changes exported APIs, runtime behavior, schemas, 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.
| name | test-coverage-improver |
| description | Improve test coverage in the OpenAI Agents JS monorepo: run `pnpm test:coverage`, inspect coverage artifacts, identify low-coverage files and branches, 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.
pnpm test:coverage (set CI=1 if needed) to regenerate coverage/.coverage/coverage-summary.json (preferred) or coverage/coverage-final.json, plus coverage/lcov.info and coverage/lcov-report/index.html for drill-downs.pnpm test:coverage, and then run $code-change-verification before marking work complete.CI=1 pnpm test:coverage at repo root. Avoid watch flags and keep prior coverage artifacts only if comparing trends.coverage/coverage-summary.json for file-level totals; fallback to coverage/coverage-final.json if the summary file is absent.coverage/lcov.info or coverage/lcov-report/index.html to spot branch- and line-level holes.packages/*/src before examples or docs.packages/<pkg>/test/*.test.ts) and avoid flaky async timing.scripts/, references/, or assets/ unless needed later.pnpm test:coverage instead of guessing.