Coding standards, frameworks, refactoring, and code review (17K skills)
Configure Factory board behavior and GitHub or Linear event handlers in deployment code. Adjust stage transitions, phase meanings, and tool-result handling, then check the changes with focused tests and versioned audit records.
Review open Mastra GitHub issues and trace reported defects to source code. Apply the @mastra/core label to confirmed core bugs, report uncertain ownership, and summarize whether fixes are active, stale, or unclaimed.
Re-review a pull request after new commits arrive. Check every previous finding, inspect the new changes for regressions, and review the full current change. Run relevant verification and publish a test report and review verdict within Factory.
Combine code from local directories or GitHub into one structured file for AI analysis. Examine project structure, search for related code, and check estimated tokens, the units AI models use to process text.
Write Git commit messages that preserve why changes were made. The skill keeps Conventional Commits subject lines and adds structured body entries for user intent, decisions, rejected alternatives, constraints, and lessons supported by the session context.
Develop and maintain the WXT browser extension that adds a Repomix button to GitHub repository pages. The skill covers Chrome, Firefox, and Edge compatibility, extension scripts, translation files, and commands for building, linting, and testing.
Explore local or remote repositories with Repomix CLI to understand their structure, locate related code across files, and review file counts and estimated tokens, the units AI models use to process text.
Create, configure, and troubleshoot Crush hooks, commands that run before tool execution. Use them to block or approve calls, rewrite tool input, or add context for the agent, with guidance on configuration and troubleshooting.
Configure Crush with Bash or JSON files to choose AI providers and models, connect external tools, set permissions, and adjust behavior. Understand how project and global settings combine when customizing your working environment.
Add or edit skills bundled with Crush, following guidance on file placement, required metadata, compile-time embedding, and discovery tests. It also explains how built-in skills are loaded and how user skills override them.
Add or modify commands handled inside Crush's embedded shell before they reach the operating system. The guidance covers command routing, input and output streams, exit codes, and cancellation so commands work with pipes, redirection, and hook timeouts.
Extract fields, filter records, and reshape JSON from API responses, configuration files, or logs using Crush’s built-in jq. Get help writing and debugging transformations, constructing new JSON, and formatting output for other commands.
Turns recurring workflows and proven debugging solutions into reusable skill packages. It creates SKILL.md, a readable overview, and optional supporting examples from a user description or saved project memory, with checks for completeness and portability.
Turn recurring lessons in Claude's automatic memory into concise project rules. Choose a project-wide, file-specific, or personal rule location, include concrete commands, and clean up the original memory entry after confirmation.
Generate a starting project for a subscription web app with Next.js, including sign-in, database schemas, billing routes, and a dashboard. The workflow also covers staged validation and reference documents for customization and common setup problems.
Turn a written app specification into a runnable starter project using the requested technology stack. Generate implemented features, tests, configuration files, and setup instructions, then check the project for common omissions.
Turn a Markdown code review into a single HTML file with code changes beside severity-labeled comments. Readers can jump to findings, inspect line numbers, and identify the named human reviewer.
Investigate slow Node.js, Python, and Go applications by measuring CPU use, memory, database queries, and data transfer. Identify bottlenecks, inspect frontend bundle sizes, run load tests, and compare measurements before and after changes to verify improvements.
Turn plain language requirements into SQL, investigate slow queries, document database structures, and prepare migration templates with rollback plans. Support everyday database development and ORM use, where libraries connect application code to database tables.
Track code changes in structured JSON records, including reasons, test results, progress, and approvals. Save remaining tasks and key decisions so another AI session can understand the work and continue from the recorded handoff.
Turn an OpenAPI specification into starter code for an MCP server, which connects AI agents to API tools. Support Python or TypeScript implementations, validate tool definitions, and plan changes that preserve compatibility.
Review GitHub pull requests and GitLab merge requests for security, test gaps, compatibility, and performance risks. Trace affected code and services, then produce a prioritized report with suggested fixes and a structured review checklist.
Plan features before coding by defining requirements, acceptance criteria, and scope. Validate the specification, generate starter tests from expected behaviors, and guide implementation and review so each delivered feature can be checked against its agreed requirements.
Scan a codebase for technical debt—issues that make future maintenance harder—and prioritize fixes using business impact and effort. Generate a ranked backlog, sprint allocations, and trend reports to assess cleanup work over time.