Search Skills

Automates updating CLAUDE.md documentation and skill lists for new patterns or conventions.

Generates step-by-step plans to resolve GitHub issues through contextual analysis and actionable task breakdowns.

Automates code review suggestions for current Git branch changes, identifying improvements and potential issues.

Generates comprehensive design documents for Video.js 10, including architectural decisions and component specifications.

Guides users through creating new Claude agent skills with structure, frontmatter, and conventions for specialized workflows.

Configures an autonomous AI system to continuously build, test, and deploy code features without manual intervention.

Provides a structured workflow for software development tasks using the APEX methodology (Analyze-Plan-Execute-Validate) with parallel agents and self-validation.

Automates correction of ESLint and TypeScript errors across codebases using parallel processing for efficient code quality improvement.

Provides structured guidance for creating and optimizing CLAUDE.md memory files and .claude/rules modular rules to improve context awareness in Claude Code projects.

Automates fetching pull request review comments and applying the requested code changes.

Enables ultra-fast feature implementation via an optimized Explore → Code → Test workflow for focused development tasks.

Automates grammar and spelling correction across multiple text files while preserving original formatting and structure.

Automates creating and pushing pull requests with AI-generated titles and descriptions for streamlined code reviews.

Provides a structured APEX workflow (Analyze-Plan-Execute-eXamine) for code implementation with parallel agents and self-validation.

Comprehensive guide for creating Claude Code skills, covering SKILL.md structure, XML configuration, and resource bundling requirements.

Guides creation, configuration, and utilization of Claude Code subagents and Task tool for specialized AI agent workflows.

Creates optimized prompts for LLMs to enhance output quality and task performance in system prompts, user prompts, and few-shot examples.

Intelligently resolves merge conflicts in version control by analyzing code context, reducing manual intervention during branch integration.

Automates semantic commit message generation and ensures safe commits through pre-commit verification.

Automates Git commit and push with concise, clean commit messages for efficient version control.

Provides development patterns for building and debugging TabzChrome, including Terminal.tsx, xterm.js integration, and WebSocket I/O handling.

Automates test execution across multiple frameworks (Jest, pytest, etc.), providing structured pass/fail results and detailed failure reports.

Crafts optimized AI worker prompts using Claude 4 best practices to enhance clarity and task execution effectiveness.

Automates code reviews via CLI, delivering structured pass/fail results and issue details for quality checks.