github-code-review
Comprehensive GitHub code review with AI-powered swarm coordination
github-multi-repo
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
github-project-management
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
github-release-management
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
github-workflow-automation
Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
hive-mind-advanced
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
Hooks Automation
Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development workflows.
market-analyst
Synthesize multiple sentiment analyses to identify market trends, gaps, opportunities, and predict likely hits. Cross-analyzes patterns to find underserved markets and highlight unique innovations.
monetization-analyzer
Analyze game concepts for monetization potential, willingness-to-pay, viral mechanics, and revenue generation. Ranks concepts by total monetization score and identifies top revenue opportunities.
Pair Programming
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
performance-analysis
Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms
ReasoningBank with AgentDB
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
ReasoningBank Intelligence
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
reddit-sentiment-analysis
Conduct comprehensive sentiment analysis of Reddit discussions for any product, brand, company, or topic. Analyzes what people like, dislike, and wish were different with structured output summaries.
Skill Builder
Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.
sparc-methodology
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
stream-chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
swarm-advanced
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
Swarm Orchestration
Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.
threejs-game
Three.js game development. Use for 3D web games, WebGL rendering, game mechanics, physics integration, character controllers, camera systems, lighting, animations, and interactive 3D experiences in the browser.
Verification & Quality Assurance
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
cli-skills
CLI best practices for LlamaFarm. Covers Cobra, Bubbletea, Lipgloss patterns for Go CLI development.
code-review
Comprehensive code review for diffs. Analyzes changed code for security vulnerabilities, anti-patterns, and quality issues. Auto-detects domain (frontend/backend) from file paths.
commit-push-pr
Commit changes, push to GitHub, and open a PR. Includes quality checks (security, patterns, simplification). Use --quick to skip checks.
common-skills
Best practices for the Common utilities package in LlamaFarm. Covers HuggingFace Hub integration, GGUF model management, and shared utilities.
config-skills
Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation.
designer-skills
Designer subsystem patterns for LlamaFarm. Covers React 18, TanStack Query, TailwindCSS, and Radix UI.
electron-skills
Electron patterns for LlamaFarm Desktop. Covers main/renderer processes, IPC, security, and packaging.
fix-ci
Fetch GitHub CI failure information, analyze root causes, reproduce locally, and propose a fix plan. Use `/fix-ci` for current branch or `/fix-ci <run-id>` for a specific run.
generate-subsystem-skills
Generate specialized skills for each subsystem in the monorepo. Creates shared language skills and subsystem-specific checklists for high-quality AI code generation.
go-skills
Shared Go best practices for LlamaFarm CLI. Covers idiomatic patterns, error handling, and testing.
python-skills
Shared Python best practices for LlamaFarm. Covers patterns, async, typing, testing, error handling, and security.
rag-skills
RAG-specific best practices for LlamaIndex, ChromaDB, and Celery workers. Covers ingestion, retrieval, embeddings, and performance.
react-skills
React 18 patterns for LlamaFarm Designer. Covers components, hooks, TanStack Query, and testing.
reflect
Analyze the current session and propose improvements to skills. **Proactively invoke this skill** when you notice user corrections after skill usage, or at the end of skill-heavy sessions. Also use when user says "reflect", "improve skill", or "learn from this".
runtime-skills
Universal Runtime best practices for PyTorch inference, Transformers models, and FastAPI serving. Covers device management, model loading, memory optimization, and performance tuning.
server-skills
Server-specific best practices for FastAPI, Celery, and Pydantic. Extends python-skills with framework-specific patterns.
temp-files
Guidelines for creating temporary files in system temp directory. Use when agents need to create reports, logs, or progress files without cluttering the repository.
typescript-skills
Shared TypeScript best practices for Designer and Electron subsystems.
wt
Manage LlamaFarm worktrees for isolated parallel development. Create, start, stop, and clean up worktrees.
async-io-model
Explanations of common asynchronous patterns used in tursodb. Involves IOResult, state machines, re-entrancy pitfalls, CompletionGroup. Always use these patterns in `core` when doing anything IO
cdc
Change Data Capture - architecture, entrypoints, bytecode emission, sync engine integration, tests
code-quality
General Correctness rules, Rust patterns, comments, avoiding over-engineering. When writing code always take these into account
debugging
How to debug tursodb using Bytecode comparison, logging, ThreadSanitizer, deterministic simulation, and corruption analysis tools
differential-fuzzer
Information about the differential fuzzer tool, how to run it and use it catch bugs in Turso. Always load this skill when running this tool
index-knowledge
Generate hierarchical AGENTS.md knowledge base for a codebase. Creates root + complexity-scored subdirectory documentation.
mvcc
Overview of Experimental MVCC feature - snapshot isolation, versioning, limitations
pr-workflow
General guidelines for Commits, formatting, CI, dependencies, security
storage-format
SQLite file format, B-trees, pages, cells, overflow, freelist that is used in tursodb
testing
How to write tests, when to use each type of test, and how to run them. Contains information about conversion of `.test` to `.sqltest`, and how to write `.sqltest` and rust tests
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