Loading...
Loading...
Found 6,494 Skills
Install MTHDS method packages from GitHub or local directories. Use when user says "install a method", "install from GitHub", "add a method package", "mthds install", "install method", "set up a method", or wants to install an MTHDS method package for use with an AI agent.
Global Agent rules, including language, response style, debugging priority, engineering quality baseline, mandatory code metric limits, security baseline, test verification standards and Skills routing table. Applicable to all programming tasks.
LLM app development with RAG, prompt engineering, vector databases, and AI agents
Provides usage instructions and best practices for the skills_sync CLI tool. Use this to understand how to manage, sync, and configure AI agent skills based on the user's config file.
(Industry standard: Sequential Agent / Agent as a Tool) Primary Use Case: Delegating a well-defined task to a worker agent, verifying its execution, and repeating if necessary. Inner/outer agent delegation pattern. Use when: work needs to be delegated from a strategic controller (Outer Loop) to a tactical executor (Inner Loop) via strategy packets, with verification and correction loops.
Tiered memory system for cognitive continuity across agent sessions. Manages hot cache (session context loaded at boot) and deep storage (loaded on demand). Use when: (1) starting a session and loading context, (2) deciding what to remember vs forget, (3) promoting/demoting knowledge between tiers, (4) user says 'remember this' or asks about project history.
Why build on Ethereum specifically. The AI agent angle — ERC-8004, x402, composability, permissionless deployment. Use when a user asks "should I build on Ethereum?", "why blockchain?", or when an agent needs to recommend a chain for a project.
Azure cloud operations orchestration and Microsoft Agent Framework integration hub.
Bootstrap, install, and operate an external task-management CLI as the source of truth for agent execution tracking (instead of built-in todos). Provides the abstraction layer between spec-management intent (implementation plans and tasks) and concrete CLI commands. MUST be invoked when any implementation-tier artifact (SPEC, STORY, BUG) comes up for implementation — create a tracked plan before writing code. Optional but recommended for complex SPIKEs. For coordination-tier artifacts (EPIC, VISION, JOURNEY), spec-management must decompose into implementable children first — this skill tracks the children, not the container. Also use for standalone tasks that require backend portability, persistent progress across agent runtimes, or external supervision. Use this skill whenever the user asks to track tasks, create an implementation plan, check what to work on next, see task status, manage dependencies between work items, or close/abandon tasks — even if they don't mention "execution tracking" explicitly.
Architect/CR agent role. Receives git diff, task spec, ADRs, design doc, and project conventions. Reviews code and returns APPROVED or CHANGES_REQUIRED. Do NOT invoke directly — dispatched by team-execute.
Automated code review for pull requests using multiple specialized agents
Integration patterns for Mapbox MCP Server in AI applications and agent frameworks. Covers runtime integration with pydantic-ai, mastra, LangChain, and custom agents. Use when building AI-powered applications that need geospatial capabilities.