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Found 1,150 Skills
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.
FORGE Autopilot — Intelligent autonomous mode. FORGE analyzes the project state, automatically decides the next action, and orchestrates all agents until completion. Configurable checkpoints for human review. Usage: /forge-auto or /forge-auto "specific objective"
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.
Safe experimentation framework for AI agents. Creates isolated sandbox environments for trying new features, testing approaches, and exploring solutions without polluting the main codebase. USE WHEN: Agent needs to try something uncertain, explore multiple approaches, test a new library, prototype a feature, or run a technical spike before committing to implementation. PRIMARY TRIGGERS: "experiment with" = Setup sandbox + run experiment "try this approach" = Quick experiment in sandbox "spike" / "POC" / "prototype" = Time-boxed technical investigation "tinker" / "tinkering mode" = Enter experimentation workflow "explore options" = Multi-approach comparison in sandbox NOT FOR: Debugging (use debugger), testing (use test runner), or committed feature work (use git branches). DIFFERENTIATOR: Unlike git branches (for committed direction), tinkering is for "I don't know if this will work" exploration. Try 5 things in sandbox before committing to a branch. Faster feedback, zero codebase pollution.
Generates iterable checklist PROMPT files for Ralph Loop from plan files or current context, and provides the /ralph-loop execution command.
Управление сессиями AI агентов через agent-deck CLI. Триггеры (RU): "запусти агента", "запусти саб-агента", "создай сессию", "проверь сессию", "проверь статус", "покажи вывод агента", "что агент ответил". Triggers (EN): "launch sub-agent", "create sub-agent", "start session", "check session", "show agent output".
Quick persona switching. Triggers: 'switch persona', 'switch to X', 'become X'. Lists personas, reads selected file, switches immediately.
Guide for creating and enhancing skills. Use when users want to create a new skill, update/improve an existing skill, or audit skill quality. Supports both creation from scratch and enhancement of existing skills with audit rubric scoring.
Build AI agents with persistent threads, tool calling, and streaming on Convex. Use when implementing chat interfaces, AI assistants, multi-agent workflows, RAG systems, or any LLM-powered features with message history.
The soul of MOOLLM — self-explanation, help, navigation, philosophy