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Helps with commits. Use when the user mentions commits, git, version control, committing changes, commit messages, or anything about saving work to git.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | Commit_Helper |
| description | Helps with commits. Use when the user mentions commits, git, version control, committing changes, commit messages, or anything about saving work to git. |
Write a good commit message for the changes. Follow best practices and be thorough. Make sure the commit message is high quality and follows conventions.
Scaffold a new production application with the full agentic-AI guardrail canon baked in from commit #1: a uniform 7-gate interface (lint, typecheck, test, coverage, build, e2e, audit) on each stack's native runner, strict types, maximal static analysis, coverage thresholds with teeth plus seed tests, pre-commit hooks, hardened CI with optional SonarCloud, supply-chain pinning, and an agent-ready AGENTS.md — every gate verified green before the first commit. Native adapters: Next.js, NestJS, Django, Go, Rust, Spring Boot; a discovery method maps the canon to other stacks. USE FOR: creating or scaffolding a new app, service, or API from scratch; bootstrapping a greenfield repo that AI agents will build in. DO NOT USE FOR: retrofitting an existing codebase or scaffolding a new package into an existing monorepo (both assume repo-root ownership, v0.2), LLM-safety or content-moderation guardrails, or adding a single tool to an existing project.
Turn a staged diff summary into this team's Conventional Commit message.
Factory skill that creates production-grade, benchmarked, autonomously improved, and verified agent skills. Orchestrates a 5-phase pipeline: interview the user to discover purpose and gold standards, research domain materials with parallel subagents, draft the skill with a design-first approach, invoke autoresearch to iterate against gold-standard-driven LLM-as-judge evaluation, and verify quality through multi-agent consensus with a devil's advocate. Use when building a new skill, creating a skill from existing materials, or upgrading a skill to production quality with benchmarking and autonomous improvement.
Generate grounded-and-verified, engine-agnostic database documentation that reaches 100% parity with the real schema. Introspects the LIVE database as ground truth and cross-validates it against ORM models, migrations, generated types, seeds, and application queries, then proves completeness by diffing the docs back against the database. Produces ER diagrams (mermaid), per-table data dictionaries, and a machine-readable schema.json. Works with PostgreSQL, MySQL, SQL Server, and SQLite across any ORM (Prisma, TypeORM, Drizzle, Sequelize, Knex, Django, Rails) or raw SQL. Use when asked to document a database, produce an ERD or data dictionary, write db/schema docs, audit schema drift, or refresh existing DB docs.
Migrate a project from Tailwind CSS v3 to v4 safely and completely. Runs the official `@tailwindcss/upgrade` codemod, then drives the judgment the codemod can't: reconciling dependencies and PostCSS/Vite/CLI plumbing, porting JS config to CSS-first `@theme` (or keeping it via `@config`), auditing the v4 changed-defaults that silently alter appearance (border/ring/placeholder/cursor/dialog/hover) and applying compat shims, sweeping for renamed/removed utilities, and proving the migration is a visual no-op. Framework-agnostic (Next.js, Vite, Tailwind CLI, plain PostCSS; Vue/Svelte/Astro/CSS-module caveats). USE FOR: upgrading Tailwind 3 to 4, "tailwind v4 migration", `@tailwind` directives error, `@tailwindcss/postcss` setup, tailwind.config.js to CSS @theme, shadow-sm/rounded/ring/ outline-none renames, bg-gradient-to to bg-linear-to. Activate only when an existing Tailwind v3 install is being upgraded. DO NOT USE FOR: setting up Tailwind v4 in a fresh project (no v3 present), downgrading v4→v3, building a new
