cm
The cm command stages all modified files in the current branch, reviews changes for sensitive information, generates descriptive commit messages following conventional commit conventions, and creates separate commits for new files versus modifications. Use this command to prepare local commits with professional messaging without pushing to remote repositories.
mkdir -p ~/.claude/commands && curl -fsSL https://raw.githubusercontent.com/mrgoonie/claudekit-skills/HEAD/.claude/commands/git/cm.md -o ~/.claude/commands/cm.mdcm.md
Stage, commit and push all code in the current branch:
1. Review all modified files and their changes
**DO NOT** commit and push any confidential information (such as dotenv files, API keys, database credentials, etc.) to git repository!
2. Generate a clear, descriptive commit message summarizing the changes.
Follow convention commit rules (eg. `fix`, `feat`, `perf`, `refactor`, `docs`, `style`, `ci`, `chore`, `build`, `test`)
Any changes related to Markdown files in `.claude/` should be using `perf:` (instead of `docs:`)
New files in `.claude/` directory should be using `feat:` (instead of `docs:` or `perf:`)
Commit title should be less than 70 characters.
If there are new files and file changes at the same time, split them into separate commits.
Commit body should be a summarized list of key changes.
NEVER automatically add AI attribution signatures like:
- "🤖 Generated with [Claude Code]"
- "Co-Authored-By: Claude noreply@anthropic.com"
- Any AI tool attribution or signature
- Create clean, professional commit messages without AI references.
3. Stage all modified files using git add & commit the changes using: git commit -m "commit_message".
- Split files into separate commits to reflect the changes.
5. Confirm the commit was successful and display the resulting commit hash and message.
**IMPORTANT: DO NOT push the changes to remote repository**Manage MCP (Model Context Protocol) server integrations - discover tools/prompts/resources, analyze relevance for tasks, and execute MCP capabilities. Use when need to work with MCP servers, discover available MCP tools, filter MCP capabilities for specific tasks, execute MCP tools programmatically, or implement MCP client functionality. Keeps main context clean by handling MCP discovery in subagent context.
Stage, commit and push all code in the current branch
Create a pull request
Create a new agent skill
Utilize tools of Model Context Protocol (MCP) servers
Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.