By fadrienne
GitHub workflow skills: code review, multi-repo coordination, project management, release management, workflow automation, repo importing, skill building, and pair programming.
This document describes all GitHub integration modes available in Claude-Flow with ruv-swarm coordination. Each mode is optimized for specific GitHub workflows and includes batch tool integration for maximum efficiency.
Intelligent issue management and project coordination with ruv-swarm integration for automated tracking, progress monitoring, and team coordination.
Comprehensive pull request management with ruv-swarm coordination for automated reviews, testing, and merge workflows.
Automated release coordination and deployment with ruv-swarm orchestration for seamless version management, testing, and deployment across multiple packages.
Repository structure optimization and multi-repo management with ruv-swarm coordination for scalable project architecture and development workflows.
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.
Comprehensive GitHub code review with AI-powered swarm coordination
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
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A repo containing a personal knowledge vault and a collection of AI-powered tools.
An AI-enhanced personal knowledge management system built on Obsidian. Open the Obsidian Mind/ folder as your vault root in Obsidian. Features lifecycle hooks, slash commands for common workflows, and multi-agent support (Claude Code, Codex, Gemini).
See CLAUDE.md for the full operating manual.
A bundle of 20 Claude Code skills for the scientific research lifecycle, plus 13 reusable prompts and a 4-agent subagent team (researcher, reviewer, writer, verifier). Skills cover the full pipeline from literature search and hypothesis generation through paper writing, peer review, and compute orchestration.
Skills include: alpha-research, autoresearch, deep-research, literature-review, paper-writing, peer-review, paper-code-audit, replication, source-comparison, ml-training-recipe, docker, modal-compute, runpod-compute, eli5, jobs, preview, session-log, session-search, contributing, watch
See feynman/AGENTS.md for agent conventions and feynman/skills/ for individual skill docs.
A design skill for AI coding assistants that makes generated UIs look made, not generated. Use for building new pages, auditing existing designs, redesigns, and extracting design patterns from URLs or screenshots.
Key features:
See hallmark/SKILL.md for usage.
A memory-centric agentic system for the full scientific research lifecycle, powered by Claude Code. Handles everything from literature ingestion and idea generation through experiment execution to paper writing and conference rebuttal.
Key features:
See autosci/README.md for setup and usage.
Python automation client for Google NotebookLM. List, create, and interact with notebooks; add URL sources; chat with content; and generate audio overviews — all from the command line or Python scripts.
See notebooklm/README.md for setup and usage.
A business dashboard for tracking key metrics and performance indicators.
See thrive-hub/ for details.
An open-source AI-powered software factory by Garry Tan (YC President & CEO) that transforms Claude Code into a virtual engineering team. Provides 23+ specialized skills covering the full product development lifecycle — from strategic planning and design through QA, security audits, and shipping.
Key features:
See gstack/README.md for setup and usage.
A curated collection of 24 Claude Code skills for scientific research, adapted from the K-Dense-AI open-source library. Covers the full research workflow from literature discovery through data analysis, molecular modeling, and publication.
Skill categories:
See scientific-agent-skills/README.md for setup and usage.
npx claudepluginhub p/fadrienne-github-devops-plugins-github-devopsClaude-flow v3 development skills: swarm orchestration, SPARC methodology, hooks automation, stream chaining, verification/quality, and the nine v3 architecture workstreams (CLI, core, DDD, integration, MCP, memory, performance, security, swarm coordination).
Audits AI instruction sets (CLAUDE.md, system prompts, skills) for over-prompting and prompt bloat.
Data collection and automation skills: Apify scraping, browser automation, and Google NotebookLM programmatic access.
AgentDB skills for vector search, memory patterns, optimization, learning plugins, and ReasoningBank adaptive-learning integration.
Research, reasoning, and writing skills: arXiv lookup, Fabric patterns, wisdom extraction, multi-agent debate, first-principles reasoning, root cause analysis, systems thinking, scientific writing, and story writing.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Develop, test, build, and deploy Godot 4.x games with Claude Code. Includes GdUnit4 testing, web/desktop exports, CI/CD pipelines, and deployment to Vercel/GitHub Pages/itch.io.
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.