Research latest UI/UX trends from Dribbble and design communities. Use when starting a design project to understand current visual trends, color palettes, and layout patterns.
Forms a GitHub search query based on a natural language query and the type of search (issue or PR). This skill helps users create effective search queries to find relevant issues or pull requests on GitHub.
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.
Summarizes the results of a GitHub search query in a human friendly markdown table that is easy to read and understand. ALWAYS use this skill when displaying the results of a GitHub search query.
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.
Analyze CSV files in /mnt/data and return concise numeric summaries.
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.
Run the integration-tests pipeline that depends on a local npm registry (Verdaccio). Use when asked to execute integration tests or local publish workflows in this repo.
Keep pnpm current: run pnpm self-update/corepack prepare, align packageManager in package.json, and bump pnpm/action-setup + pinned pnpm versions in .github/workflows to the latest release. Use this when refreshing the pnpm toolchain manually or in automation.
Perform a release-readiness review by locating the previous release tag from remote tags and auditing the diff (e.g., v1.2.3...<commit>) for breaking changes, regressions, improvement opportunities, and risks before releasing openai-agents-js.
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.
Run examples:start-all in auto mode with parallel execution, per-script logs, and start/stop helpers.
Create a PR title and draft description after substantive code changes are finished. Trigger when wrapping up a moderate-or-larger change (runtime code, tests, build config, docs with behavior impact) and you need the PR-ready summary block with change summary plus PR draft text.
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.
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.
Core conventions and patterns for this codebase
Coding patterns and best practices — React components, promise handling, and TypeScript conventions.