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Found 229 Skills
Produce a token-bounded context pack from the Obsidian wiki — a compact, structured slice of the most relevant pages for a topic or recent activity, designed for downstream consumption by another agent or skill. Use when the user says "/wiki-context-pack", "make a context pack", "give me a context slice for X", "pack the wiki for my agent", or "bounded context for Y". Different from wiki-query (which answers a question) — this produces reusable input material for a downstream task.
Execute Python code in isolated rootless containers with MCP server proxying for token-efficient agent workflows
Shared orchestration engine for the orch-* skill family. Defines the gated Research-Plan-TDD-Review-Commit pipeline, the size classifier, the agent map, and the two human gates that the orch-* operation skills delegate to. Not usually invoked directly.
Guides the agent through building LLM-powered applications with LangChain and stateful agent workflows with LangGraph. Triggered when the user asks to "create an AI agent", "build a LangChain chain", "create a LangGraph workflow", "implement tool calling", "build RAG pipeline", "create a multi-agent system", "define agent state", "add human-in-the-loop", "implement streaming", or mentions LangChain, LangGraph, chains, agents, tools, retrieval augmented generation, state graphs, or LLM orchestration.
Execute complete FPF cycle from hypothesis generation to decision
Turn any record into a shared workspace where agents and humans collaborate. Attach a simple workspace schema to any entity — contacts, companies, deals, projects, tickets — and let any participant contribute updates, tasks, notes, and issues. The record becomes the coordination. No orchestrator, no message bus — just read the workspace, do your work, record what you did. Intelligence accumulates. Use when multiple agents, humans, or systems need to work on the same entity together.
Use this when you are exploring the codebase. It lets you ask the AI who wrote code questions about how things work and why they chose to build things the way they did. Think of it as asking the engineer who wrote the code for help understanding it.
EMIT phase. Pre-emit debug, write files, post-emit verify from disk. Any new unknown triggers immediate snake back to planning — restart chain.
AI design workflow with DESIGN.md, anti-patterns, and optional Stitch MCP
Generate per-asset visual specifications and AI generation prompts from GDDs, level docs, or character profiles. Produces structured spec files and updates the master asset manifest. Run after art bible and GDD/level design are approved, before production begins.
Guidelines for creating well-structured AI agent skills. Use when building a new skill, reviewing skill quality, or unsure how to organize a skill.
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions