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Found 11,959 Skills
Request coding agents to review code, verify review results and fix confirmed issues
Coordinate the end-to-end CAD/source-asset to SimReady workflow. Use for broad requests such as CAD to SimReady, source asset to simulation-ready USD, or prop packaging that require conversion, material/physics assignment, SimReady conformance, validation, and optional package creation; deploy or verify Content Agents services first when property assignment is enabled; route single-stage work through nested references.
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.
poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work. Use for poteto, /poteto-mode, or requests to work in this style.
Use when driving a website with opencli browser and sitemap context is available, requested, or needed to avoid blind navigation. Guides agents to consume site sitemap files lazily, choose adapter/browser fallback paths, resume from state signatures, and mark stale sitemap entries without trusting them over live browser state.
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".