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Found 12,021 Skills
Request coding agents to review code, verify review results and fix confirmed issues
Compress an agent's routing file (RESOLVER.md or AGENTS.md) by converting granular skill-per-row tables into functional-area dispatchers. Each area lists sub-skills in a "(dispatcher for: ...)" clause. The LLM reads one area entry and routes to the correct sub-skill. Proven via held-out A/B eval: dispatcher pattern outperforms naive pipe-table compression.
Always-on ambient signal capture. Fires on every inbound message to detect original thinking and entity mentions. Spawn as a cheap sub-agent in parallel, never block the main response.
Building & extending Pi — authoring TypeScript extensions (ExtensionAPI, registerTool, registerProvider, /commands, UI hooks), publishing as npm/git packages (pi-package), embedding via JSON-RPC mode (--mode rpc/json, JSONL framing, AgentSession SDK), and developing inside the pi_agent_rust repo. Use for any "how do I build a Pi extension/package/SDK client" question.
Build and maintain an executable context layer for data and analytics agents using ktx's semantic layer, wiki knowledge, and MCP integration
Execute Python code in isolated rootless containers with MCP server proxying for token-efficient agent workflows
Pre-build reality check for AI coding agents — scan GitHub, HN, npm, PyPI, Product Hunt to validate ideas before building
Connect AI coding agents to Figma designs via MCP to generate code from frames, extract design tokens, use Code Connect, and write directly to the canvas
Multi-agent deep research for comprehensive market analysis using the aipa CLI. Use this skill when the user asks for deep research, thorough market analysis, sector-wide investigation, comprehensive stock comparison, or detailed financial report. This runs a supervisor → parallel workers → aggregator → reviewer pipeline that takes longer but produces more thorough results than a simple analyze. Trigger for requests like "research banking sector", "deep dive into real estate stocks", or "comprehensive market overview". Can also incorporate fundamental analysis (PE, ROE, NPL, CAR, financial ratios) via `aipa fundamentals` when the user asks for fundamental context alongside technical research.
Multi-AI Agent P2P Debate. Suitable for technical solution stress testing, multi-perspective collision, and design decision convergence. Use it when you want a solution to be challenged or to understand the pros and cons of different technical routes. Triggered when mentioning "debate", "agent discussion", "multi-angle analysis", or "start a team".
Two-layer autonomous conductor — design loop produces decision packets, dispatch loop routes to bounded issues with dedupe/cooldown/archive controls. Replaces v1's single-agent persistence with a durable control loop that stops only at real blockers.
Use this skill when the user wants to audit Agent Skills, SKILL.md files, imported skills, prompts, tools, scripts, or skill repositories for safety, prompt injection risk, secret leakage, unsafe commands, unclear permissions, untrusted external references, or repo policy violations. Trigger phrases include "audit this skill," "skill security," "review imported skills," "prompt injection risk," "unsafe skill," "scan skills," and "security audit for skills."