Skill UI

A comprehensive guide on embedding before-and-after screenshots directly into pull request descriptions. This skill helps reviewers visualize UI changes, layout adjustments, and data visualizations instantly, without needing to check out the branch. Includes best practices for image sizing, structured Markdown patterns, and specific API/upload guidance for Azure DevOps and GitHub.

Transforms an exported JSON list of open pull requests into a structured, blockers-first digest. Ideal for standup meetings or triage sessions, this tool identifies which PRs are blocked (due to failing checks, required changes, or staleness) and which are ready to merge, providing a concise summary count for quick status updates.

This tool automates complex Git workflows to save time and reduce manual overhead. It intelligently detects and groups related code changes, automatically generates descriptive branch names (e.g., fix/auth-bug), and streamlines the entire cycle: staging, committing, pushing, and creating Pull Requests (PRs). Use it to maintain clean, consistent commit histories efficiently.

This tool helps users manage and address review comments on open GitHub Pull Requests (PRs). It interacts with the GitHub CLI (gh) to fetch comments, guides the user through selecting which comments need fixes, and then applies the necessary changes, ensuring a structured approach to PR review.

A comprehensive guide to using the GitHub CLI (`gh`) for programmatic interaction with repositories. This tool allows users to list, manage, and review Pull Requests (PRs), create and triage issues, check CI/workflow status, and execute advanced API queries directly from the terminal, making it essential for scripting and automated DevOps workflows.

This meta-skill automatically inspects open GitHub Pull Requests, failing CI runs, and new issues. It utilizes the GitHub API to gather critical updates and summarizes the findings into three actionable buckets (To Review, Awaiting Me, CI Red). Finally, it persists follow-up tasks to long-term memory, helping developers efficiently prioritize their daily workflow.

This meta-skill automates the process of handling a GitHub issue by fetching context, delegating the fix to a sub-agent, summarizing the resolution, and finally opening a pull request (PR). It is best suited for small, well-scoped issues with clear acceptance criteria. This pipeline simulates a complete development workflow.

Use the Composio CLI to automate the entire Pull Request review and Continuous Integration (CI) triage process for GitHub and GitLab. This tool fetches code diffs, analyzes failure logs, posts detailed inline review comments, and iteratively patches and re-runs CI checks until the code passes, significantly enhancing code quality and developer efficiency.

This skill provides deep security review for GitHub Actions workflow files. It focuses on the unique Actions threat model—identifying vulnerabilities like script injection via ${{ }} interpolation, privilege escalation from triggers (e.g., pull_request_target), and ensuring least-privilege permissions for CI/CD pipelines. Use it to audit, secure, or harden existing workflows, preventing attacks from untrusted inputs and supply chain risks.

A comprehensive playbook for optimizing the entire lifecycle of pull requests. It guides developers through systematic pre-flight cleanup, critical self-audits, local test verification, and structuring high-signal PR descriptions to ensure code quality and fast maintainer approval.

This skill generates a highly customized code review checklist for any pull request. Instead of using a generic template, it adapts the review depth and specific checks based on the target language (e.g., Python, TypeScript), the nature of the change (e.g., bug fix, refactor), and the associated risk level (low, medium, high, critical). It ensures comprehensive coverage, guiding reviewers to focus on critical areas like security, correctness, and architectural integrity.

This skill automates the creation of high-quality, structured pull request descriptions. By analyzing git diffs, commit lists, or raw changes, it generates comprehensive sections covering the summary, motivation, specific changes, detailed testing procedures, and crucial reviewer guidance. Use it to ensure every code change is fully documented for effective peer review.