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Found 1,677 Skills
Audit existing skills (global and project-level) for agent-friendliness, consistency, and best practices. Use when asked to "audit my skills", "review skill setup", "analyze skill quality", "check skill health", "improve my skills", or when wanting an assessment of the overall skill ecosystem. Provides actionable recommendations for improving skill effectiveness.
Guidance for working with the Beltic KYA (Know Your Agent) ecosystem - a credential-based trust framework for AI agents. Use when: (1) Working in any Beltic repository (beltic-spec, beltic-cli, beltic-sdk, fact-python, kya-platform, wizard, nasa), (2) Implementing agent credential signing/verification, (3) Using @belticlabs/kya SDK or beltic-sdk Python, (4) Understanding agent safety certification, (5) Working with verifiable credentials for AI. Triggers on: Beltic CLI commands, agent credentials, HTTP message signatures (RFC 9421), safety scores, KYB tier verification, trust chain validation.
Clear conversation context while preserving knowledge via context marker. Use when user says "clear context", "start fresh", "done with this task", or when approaching token limits.
Use when working with AI agent protocols, standards, and interoperability specifications. Covers MCP, A2A, ACP, Agent Skills, AGENTS.md, ADL, x402, AP2, MCP Apps, and cagent. USE FOR: agent protocol selection, comparing MCP vs A2A vs ACP, understanding agent standards ecosystem, choosing payment protocols DO NOT USE FOR: specific protocol implementation details (use the sub-skills: mcp, a2a, acp, x402, etc.)
TDD-style testing methodology for skills using fresh subagent instances to prevent priming bias and validate skill effectiveness. Use when validating skill improvements, testing skill effectiveness, preventing priming bias, measuring skill impact on behavior. Do not use when implementing skills (use skill-authoring instead), creating hooks (use hook-authoring instead).
Resolve conflicts, negotiate agreements, and mediate disputes between AI agents and humans using Servanda. Use this skill when you need to reach consensus with another party, settle a disagreement, establish shared rules, or create binding agreements through AI-mediated negotiation.
Persistent local memory for AI agents. Use when starting a new session, when the user mentions remembering something, when you need project context, when making architecture decisions, or when working with other agents on the same project.
Advanced memory operations reference. Basic patterns (profile loading, simple recall/remember) are in project instructions. Consult this skill for background writes, memory versioning, complex queries, edge cases, session scoping, retention management, type-safe results, proactive memory hints, GitHub access detection, and ops priority ordering.
Creates new AI agent skills following the Agent Skills spec. Trigger: When user asks to create a new skill, add agent instructions, or document patterns for AI.
Epistemic verification framework for AI-generated assertions. Requires evidence before acting on LLM claims about code behavior, system state, API responses, or factual statements. Use when an AI agent makes claims that will drive decisions, before acting on research results, or when an agent asserts something is true without showing evidence.
Apply production-ready LangChain SDK patterns for chains, agents, and memory. Use when implementing LangChain integrations, refactoring code, or establishing team coding standards for LangChain applications. Trigger with phrases like "langchain SDK patterns", "langchain best practices", "langchain code patterns", "idiomatic langchain", "langchain architecture".
Design and build websites using AI coding agents with static site generators. Covers Astro-first workflow, iterative visual refinement via browser feedback, skill-enhanced prompting (frontend-design, copywriting), animations, and high-bar polish loops. Use when building a website with an AI agent, designing landing pages, or iterating on web design with LLM assistance.