Validate changesets in openai-agents-js using LLM judgment against git diffs (including uncommitted local changes). Use when packages/ or .changeset/ are modified, or when verifying PR changeset compliance and bump level.
Create the required PR-ready summary block, branch suggestion, title, and draft description for openai-agents-js. Use in the final handoff after moderate-or-larger changes to runtime code, tests, examples, build/test configuration, or docs with behavior impact; 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.
Analyze main branch implementation and configuration to find missing, incorrect, or outdated documentation in docs/.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 (docs/src/content/docs/**) and never touch translated docs under docs/src/content/docs/ja, ko, or zh. Provide a report and ask for approval before editing docs.
Use when working with the OpenAI API (Responses API) or OpenAI platform features (tools, streaming, Realtime API, auth, models, rate limits, MCP) and you need authoritative, up-to-date documentation (schemas, examples, limits, edge cases). Prefer the OpenAI Developer Documentation MCP server tools when available; otherwise guide the user to enable `openaiDeveloperDocs`.
Run the mandatory verification stack when changes affect runtime code, tests, or build/test behavior in the OpenAI Agents JS monorepo.
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.
Core conventions and patterns for this codebase
This skill should be used when users need to generate detailed, structured prompts for creating UI/UX prototypes. Trigger when users request help with "create a prototype prompt", "design a mobile app", "generate UI specifications", or need comprehensive design documentation for web/mobile applications. Works with multiple design systems including WeChat Work, iOS Native, Material Design, and Ant Design Mobile.
Install Claude skills from GitHub repositories with automated security scanning. Triggers when users want to install skills from a GitHub URL, need to browse available skills in a repository, or want to safely add new skills to their Claude environment.
Audit translation accuracy for strings changed in a GitHub PR. Use when asked to check, review, audit, or verify translations in a pull request. Identifies inaccurate translated strings by comparing PR changes against the English source.
Add new Room database persistence to Trail-Sense Android app. Use when the user asks to create, add, or implement database persistence for a model, including Entity, DAO, Repository, and AppDatabase migration. Covers entity-to-model mapping, index configuration, and standard CRUD operations.
Add UI automation tests to Trail-Sense Android app using AutomationLibrary. Use when asked to create, add, write, or implement automated tests, UI tests, integration tests, or androidTests for Trail Sense tools. Covers test class structure, AutomationLibrary functions, and testing patterns.
Write or update user guide documentation for Trail-Sense tools. Use when asked to create, write, update, or modify a tool's user guide, help documentation, or user-facing documentation. Covers guide structure, formatting conventions, and common sections.
Documentation-only master skill for GLM ecosystem discovery and installation. This skill does not execute scripts or subprocess commands. It provides a curated list of official GLM skills, install methods, and source links.
Summarizes the content of a GitHub issue, pull request (PR), or notification, providing a concise overview of the main points and key details. ALWAYS use the skill when asked to summarize an issue, PR, or notification.
Given the details of an issue, suggests a fix for the issue.
Guide for ingesting the latest OpenAI TypeSpec specification into the openai-dotnet SDK. Use this when asked to update or ingest OpenAI API specs, copy base TypeSpec files from upstream, fix client TSP compile errors, or run code generation for new API areas.
