Skill UI

This skill simulates a senior engineer's final, deep audit of an entire codebase before committing or pushing to a remote repository. It systematically checks for junk files, dead code, security vulnerabilities (secrets, injection flaws), and performance bottlenecks (N+1 queries). Use this pre-flight check before any major release or public deployment to ensure maximum code quality and production readiness.

A rigorous, security-focused code review process designed for Pull Requests (PRs), commits, and diffs. It moves beyond general reviews by focusing intensely on high-risk areas such as authentication, cryptography, external calls, and value transfer. The methodology is evidence-based, requiring detailed attack scenario modeling and generating comprehensive, auditable markdown reports to identify overlooked vulnerabilities and regressions.

Shows the AgentHub session status, including agent branches, commit counts, DAG frontier state, and board updates, helping operators monitor progress or check a specific session via `/hub:status`.

This skill guides users on setting up automated code quality gates directly at the Git level. It covers best practices using frameworks like Husky, lint-staged, and pre-commit. Users can enforce linting, formatting, type-checking, and standardized commit message conventions (e.g., Conventional Commits) before code is committed or pushed, significantly improving code hygiene and development workflow consistency.

Autoresearch Agent runs an autonomous optimization loop that edits a target file, invokes a provided evaluation command, keeps metric-improving commits, drops failures, and repeats indefinitely so engineers can optimize speed, bundle size, prompts, or other measurable goals overnight.

Define a Gitleaks-driven secret scanning workflow that spans repo baseline scans, pre-commit hooks, GitHub Actions CI/CD runs, custom detection rules, and remediation steps to stop hard-coded credentials from entering source control.

Vibers provides a human code review workflow for AI-generated GitHub projects; add the collaborator, GitHub Action, and commit guidance to receive spec- and security-focused feedback plus follow-up PR fixes.

This skill generates user-friendly, public-facing release notes (changelogs) for App Stores. It analyzes the raw Git history since the last tag, intelligently filtering out internal commits (like refactors, CI updates, or build scripts) and grouping visible changes into concise, benefit-focused bullet points suitable for a "What's New" section.

A comprehensive guide to professional Git version control. It covers best practices for branching strategies (GitHub Flow, GitFlow, Trunk-Based), writing standardized commit messages using Conventional Commits, managing merges vs. rebases, and defining effective Pull Request workflows. Ideal for any development team looking to improve code collaboration and maintain a clean, traceable history.

Guides disciplined git workflows for AI-assisted teams, covering branch strategies, commit hygiene, descriptive messages, and parallel workstreams to keep changes reviewable and reversible.

A comprehensive guide covering best practices for managing Go dependencies. It details module lifecycle commands, secure practices like committing go.sum, running vulnerability scans (govulncheck), resolving version conflicts, and safely upgrading packages using `go get -u=patch`. Use this when establishing robust, reproducible, and secure Go projects.

A disciplined workflow that forces you to build in thin vertical slices, test, verify, and commit each working increment before moving on, ideal for multi-file features or large refactors.