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.
npx skills add https://github.com/openai/openai-agents-js --skill changeset-validation
This skill validates whether changesets correctly reflect package changes and follow the repository rules. It relies on the shared prompt in references/validation-prompt.md so local Codex reviews and GitHub Actions share the same logic.
Experimental or preview-only feature additions that are explicitly labeled as such in the diff may remain a patch bump when they do not change existing behavior.
Major bumps are only allowed after the first major release; before that, do not use major bumps for feature-level changes.
Local (Codex-driven):
pnpm changeset:validate-prompt
references/validation-prompt.md to the generated prompt.CI (Codex Action):
pnpm changeset:validate-prompt -- --ci --output .github/codex/prompts/changeset-validation.generated.md
openai/codex-action with the generated prompt and JSON schema to get a structured verdict.pnpm changeset:validate-prompt.references/validation-prompt.md to judge correctness..changeset/*.md file is already present in the current branch diff, treat it as the active changeset. Do not add a new changeset file.main. Do not try to capture every incremental update.references/validation-prompt.mdExecute git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping
Comprehensive GitHub code review with AI-powered swarm coordination
Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit, craft a commit message, stage changes, or split work into multiple commits.
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
GitHub CLI (gh) comprehensive reference for repositories, issues, pull requests, Actions, projects, releases, gists, codespaces, organizations, extensions, and all GitHub operations from the command line.
GitHub CLI - manage repositories, issues, pull requests, actions, releases, and more from the command line.
You are a code refactoring expert specializing in clean code principles, SOLID design patterns, and modern software engineering best practices. Analyze and refactor the provided code to improve its quality, maintainability, and performance.
You are a technical debt expert specializing in identifying, quantifying, and prioritizing technical debt in software projects. Analyze the codebase to uncover debt, assess its impact, and create acti
Take openai/changeset-validation from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.