LLM & Agents

Use when generating options or clarifying a build/fix request—pull constraints from the user, list varied approaches, then narrow with them to pick a plan. For code reviews, use briefly to confirm expectations, then hand off to the agent flow.

Reviews code diffs (uncommited changes written by the agent) or new files(untracked files) for Python type hinting and structural principle compliance. Use this skill when user say review code diffs or new files or want to check code quality(when file is a python file). Requires explicit user confirmation before applying any modifications to ensure code quality and safety.

LLM evaluation and testing patterns including prompt testing, hallucination detection, benchmark creation, and quality metrics. Use when testing LLM applications, validating prompt quality, implementing systematic evaluation, or measuring LLM performance.

Analyzes code to identify untested functions, low coverage areas, and missing edge cases.Use when reviewing test coverage or planning test improvements.Generates specific test suggestions with example templates following amplihack's testing pyramid (60% unit, 30% integration, 10% E2E).Can use coverage.py for Python projects.

Guides architects on when and how to use goal-seeking agents as a design pattern.This skill helps evaluate whether autonomous agents are appropriate for a givenproblem, how to structure their objectives, integrate with goal_agent_generator,and reference real amplihack examples like AKS SRE automation, CI diagnostics,pre-commit workflows, and fix-agent pattern matching.

Comprehensive guide to implementing RAG systems including vector database selection, chunking strategies, embedding models, and retrieval optimization. Use when building RAG systems, implementing semantic search, optimizing retrieval quality, or debugging RAG performance issues.

Use when building RAG systems, vector databases, or knowledge-grounded AI applications requiring semantic search, document retrieval, or context augmentation.

API authentication patterns including JWT, OAuth 2.0, API keys, and session-based auth. Covers token generation, validation, refresh strategies, security best practices, and when to use each pattern. Use when implementing API authentication, choosing auth strategy, securing endpoints, or debugging auth issues. Prevents common vulnerabilities like token theft, replay attacks, and insecure storage.

Use when designing chaos experiments, implementing failure injection frameworks, or conducting game day exercises. Invoke for chaos experiments, resilience testing, blast radius control, game days, antifragile systems.

Creates git commits following Conventional Commits format with type/scope/subject. Use when user wants to commit changes, create commit, save work, or stage and commit. Handles regular branch commits (development) and merge commits (PR closure). Enforces project-specific conventions from CLAUDE.md.

Write comprehensive, idiomatic tests following best practices and project conventions. Use this when writing unit tests, integration tests, or test fixtures. Helps ensure proper test structure, mocking, assertions, and coverage.

This skill should be used when developing Holochain hApps, setting up development environments, creating zomes, implementing hREA integration, or writing multi-agent tests with Tryorama

Guide for creating Claude Code skills following Anthropic's official best practices. Use when user wants to create a new skill, build a skill, write SKILL.md, or needs skill creation guidelines. Provides structure, naming conventions, description writing, and quality checklist.

Use when creating or developing, before writing code or implementation plans - refines rough ideas into fully-formed designs through collaborative questioning, alternative exploration, and incremental validation. Don't use during clear 'mechanical' processes

Keep CLAUDE.md and README.md documentation in sync with the actual dotfiles configuration. Use when the user wants to update documentation, sync README with changes, maintain CLAUDE.md, document new features, or ensure docs reflect current setup. Triggers include "update docs", "update README", "update CLAUDE.md", "document changes", or "sync documentation".

Use Agency CLI to run parallel AI coding tasks in isolated Git worktrees. Invoke when user mentions "agency", "ag", parallel tasks, worktrees, or wants to run multiple coding agents simultaneously.

Comprehensive framework for effective gptme agent onboarding that builds user trust, communicates capabilities clearly, and establishes productive working relationships from the first interaction.

Agent assignment matrix, blocker escalation, and TDM coordination patterns. Use when assigning work to specialists, managing blockers, or coordinating multi-agent workflows.

Agentic orchestration patterns for long-running tasks. Implements evidence-based delivery and Simon Willison's agent loop. Use when managing multi-step work, coordinating subagents, or orchestrating PR workflows.

Reference guide for code comment formatting rules and examples. The core rules are automatically applied via CLAUDE.md system instructions - this skill provides detailed examples and edge cases for reference.