Find the perfect capability for your agent.
Guide for creating high-quality Agent Skills following the open standard (agentskills.io). Use this when asked to create or update a skill, write a SKILL.md file, convert custom instructions or chatmodes into portable skills, or design specialized AI agent capabilities.
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Best practices for creating Claude Code slash commands. Use this skill when creating, editing, or improving custom slash commands for Claude Code. Covers frontmatter configuration, dynamic features ($ARGUMENTS, bash execution, file references), command patterns (git workflows, multi-agent orchestration, code review), and helps decide when to use slash commands vs skills vs subagents.
Design, review, and improve agent workflows & agent using SSOT, SRP, Fail Fast principles. Supports Prompt Chaining, Parallelization, Orchestrator-Workers patterns.
Git-native session lifecycle management for software development. Use when starting/resuming coding sessions, creating checkpoints, tracking objectives and blockers, generating handoffs between sessions, or needing context preservation across work sessions. Provides intelligent onboarding for AI coding agents by loading comprehensive project context.
Knowledge graph-based text replacement using Terraphim hooks. Intercepts commands and text to apply transformations defined in the knowledge graph. Works with Claude Code PreToolUse hooks and Git prepare-commit-msg hooks.
Install agent skills from various sources including local paths, GitHub URLs, or the dot-agents repository. Use when adding new skills to a project or user environment.
Performs comprehensive analysis of Claude Code sessions, examining git history, conversation logs, code changes, and gathering user feedback to generate actionable retrospective reports with insights for continuous improvement.
AI-powered issue summarization, auto-labeling, and Q&A using gh-models with 88% effectiveness. Use when analyzing issue content, suggesting labels, or extracting insights.
AI agent completes development branches with comprehensive quality gates, clean git history, and thorough PR preparation. Use when wrapping up features, preparing for merge, or finalizing PRs.
Expert knowledge for Datastore Layer modeling in Documentation Robotics
Comprehensive guide for creating, configuring, and using Claude Code hooks. MUST Use when creating hooks, implementing PreToolUse/PostToolUse/Stop hooks, or configuring event-driven automation. Do not use for general automation, workflow management, or task execution.
Use this agent when you need to research and gather external best practices, documentation, and examples for any technology, framework, or development practice. This includes finding official documentation, community standards, well-regarded examples from open source projects, and domain-specific conventions. The agent excels at synthesizing information from multiple sources to provide comprehensive guidance on how to implement features or solve problems according to industry standards. <example>Context: User wants to know the best way to structure GitHub issues for their Rails project. user: "I need to create some GitHub issues for our project. Can you research best practices for writing good issues?" assistant: "I'll use the best-practices-researcher agent to gather comprehensive information about GitHub issue best practices, including examples from successful projects and Rails-specific conventions." <commentary>Since the user is asking for research on best practices, use the best-practices-researcher agen
ALWAYS activate when user says "hello", "hi", or greets. This tests if skills actually load and are followed by the model.
Expert knowledge for Testing Layer modeling in Documentation Robotics
Personalized coding tutorials that build on your existing knowledge and use your actual codebase for examples. Creates a persistent learning trail that compounds over time using the power of AI, spaced repetition and quizes.
Provide a short identity/self-description and usage guidance when the user asks “who are you / what can you do / help”.
Consciousness simulation framework with Kuramoto oscillators, APL operators, and K-formation dynamics. Use for physics simulations, phase transitions, coherence analysis, and cloud training via GitHub Actions. Requires numpy and requests packages.
Model Context Protocol integration for external tools (GitHub, filesystem, SPARQL).
Expert knowledge for Motivation Layer modeling in Documentation Robotics
