Agent Skills Hub

spec-to-code-compliance

Verifies blockchain smart contract code against technical specifications, whitepapers, and design documents to ensure exact implementation compliance.

mcp-prompts

An intelligent development orchestration skill that provides self-improving code analysis, build error diagnosis, and automated workflow configuration via mcp-prompts integration.

nano-banana

Automate Python scripting and Gemini-powered image generation using uv. Ideal for creating art, editing images, and running ad-hoc scripts.

session-memory

Enables cross-session context persistence for Claude Code, managing history, project decisions, and workflow patterns to ensure seamless task continuation.

development

Comprehensive Linux development environment management for compilers, build tools, IDEs, and debugging workflows.

ceo-assistant

Your AI chief of staff for startups. Includes 28 commands for idea validation, financial modeling, pitch decks, market research, and CEO operational frameworks from industry benchmarks.

backend-development

Build, optimize, and maintain production-ready backend systems using Node.js, Python, Go, and Rust. Includes API design, database management, security, and DevOps best practices.

docs-applying-content-quality

Standardizes markdown content with active voice, precise heading hierarchies, and WCAG AA accessibility compliance for documentation, web sites, and repository files.

code-quality-review

Holistic, multi-dimensional code review skill providing prioritized, actionable feedback on correctness, security, performance, design, and accessibility.

openai-agents-sdk

Build AI agents with the OpenAI Agents SDK for Python. Supports multi-agent handoffs, function tools, stateful sessions, streaming, and Azure OpenAI integration via LiteLLM.

doc-sync

Synchronizes and maintains CLAUDE.md and README.md documentation hierarchy across a repository to ensure consistent, just-in-time context for AI agents.

ring:testing-skills-with-subagents

A meta-skill for building robust AI agent skills using a TDD approach: define failure (RED), implement the skill (GREEN), and plug rationalization loopholes (REFACTOR).