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Found 141 Skills
Set up and optimize repositories for AI coding agents. Creates minimal AGENTS.md, CLAUDE.md symlink, docs/REQUIREMENTS.md, docs/BUSINESS-RULES.md, feedback loops, and deterministic enforcement (Claude Code hooks, OpenCode plugins). Use when user wants to make a repo AI-friendly, set up AGENTS.md/CLAUDE.md, document requirements/business rules for AI, add pre-commit hooks for AI workflows, or optimize codebase structure for coding agents.
Master Git hooks setup with Husky, lint-staged, pre-commit framework, and commitlint. Automate code quality gates, formatting, linting, and commit message enforcement before code reaches CI.
Use this skill when performing advanced git operations, rebase strategies, bisecting bugs, managing worktrees, configuring hooks, or handling complex merge scenarios. Triggers on interactive rebase, git bisect, worktrees, pre-commit hooks, cherry-pick, reflog recovery, stash management, and any task requiring advanced git workflows.
Use this skill when working with the UI5 Linter (@ui5/linter) for static code analysis of SAPUI5/OpenUI5 applications and libraries. Covers setup, configuring linting rules, running the linter to detect deprecated APIs, global variable usage, CSP violations, and manifest issues. Supports autofix for deprecated API usage, global references, event handlers, and manifest properties. Includes CI/CD integration, pre-commit hooks, and UI5 2.x migration preparation.
Expert quality gate decisions for iOS/tvOS: which gates matter for your project size, threshold calibration that catches bugs without blocking velocity, SwiftLint rule selection, and CI integration patterns. Use when setting up linting, configuring CI pipelines, or calibrating coverage thresholds. Trigger keywords: SwiftLint, SwiftFormat, coverage, CI, quality gate, lint, static analysis, pre-commit, threshold, warning
Code quality gatekeeper and auditor. Enforces strict quality gates, resolves the AI verification gap, and evaluates codebases across 12 critical dimensions with evidence-based scoring. Use when auditing code quality, reviewing AI-generated code, scoring codebases against industry standards, or enforcing pre-commit quality gates. Use for quality audit, code review, codebase evaluation, security assessment, technical debt analysis.
Use when prettier integration with editors, pre-commit hooks, ESLint, and CI/CD pipelines.
Analyze code changes for security vulnerabilities using LLM reasoning and threat model patterns. Use for PR reviews, pre-commit checks, or branch comparisons.
Estandariza proyectos personales y académicos con las convenciones de Jan Polanco Velasco: Python con uv/Astral (3.13+), src-layout, Ruff, pre-commit, Makefile, pytest, CONSTITUTION.md como fuente única de verdad, Conventional Commits, README con badges, licencia MIT, gobernanza GitHub (PR/issue templates, CI, Dependabot, labels), contexto para agentes (AGENTS.md, .opencode/, tgrep), identidad Git automática (includeIf; perfil Jan o perfil propio en macOS/Windows) y diagramas de arquitectura con Archify. Úsala al crear o estandarizar un repo, redactar un CONSTITUTION.md, configurar uv/Ruff/pre-commit/CI, añadir un Makefile o README, configurar la identidad Git automática, generar un diagrama con Archify, o conectar el proyecto a GitHub. Use when scaffolding a Python repository, writing a CONSTITUTION.md, setting up uv, Ruff, pre-commit or CI, configuring automatic Git identity, generating an Archify diagram, or standardizing a project.
Use when a task may benefit from a bounded subagent for implementation, large-codebase discovery at task start, independent review, requested or pre-commit code simplification, or expert work on complex decisions, modeling, automation, or repeated failures. The main agent chooses whether to delegate and accepts the result. Do not use for simple questions or short work with no meaningful review or delegation.
Guides architects on when and how to use goal-seeking agents as a design pattern. This skill helps evaluate whether autonomous agents are appropriate for a given problem, how to structure their objectives, integrate with goal_agent_generator, and reference real amplihack examples like AKS SRE automation, CI diagnostics, pre-commit workflows, and fix-agent pattern matching.
Create and execute Git commits in Conventional Commits format with a required body. Use when the user asks to commit changes, write commit messages, or prepare a clean commit. Always run a pre-commit safety guard first, abort on log files or untracked high-risk binary extensions, then stage with `git add . -A`.