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Found 347 Skills
Build Retrieval-Augmented Generation (RAG) Q&A systems with Claude or OpenAI. Use for creating AI assistants that answer questions from document collections, technical libraries, or knowledge bases.
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
Stay current with how OpenCode, OpenAI Codex, and Claude Code implement extensibility features (skills, slash commands, subagents, custom prompts). Use when comparing implementations across AI coding assistants, researching how a specific tool implements a feature, or syncing knowledge about agent extensibility patterns. Triggers include questions like "how does X implement skills?", "compare slash commands across tools", "what's the latest on Claude Code sub-agents?", or requests to understand agent extensibility approaches.
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.
Build AI agents with Subconscious platform. Use when user wants to: build an agent, create an AI agent, use Subconscious, build with TIM, create agent with tools, research agent, search agent, tool-calling agent, subconscious.dev, TIMRUN, tim, tim-edge, timini, tim-gpt, tim-gpt-heavy. Do NOT use for generic OpenAI/Anthropic/LLM tasks without Subconscious.
Implement OpenAI Harness Engineering practices in any repository. Use when setting up or refactoring agent-first workflows, writing or upgrading AGENTS.md and PLANS.md, creating deterministic smoke/test/lint/typecheck harness commands, defining strict architecture boundaries and data-shape contracts, wiring observability from day 1, and adding entropy-control checks plus CI automation for reliable autonomous runs.
AI image generation with OpenAI, Google, OpenRouter, DashScope, Jimeng, Seedream and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
Backend AI functionality with Vercel AI SDK v5 - text generation, structured output with Zod, tool calling, and agents. Multi-provider support for OpenAI, Anthropic, Google, and Cloudflare Workers AI. Use when: implementing server-side AI features, generating text/chat completions, creating structured AI outputs with Zod schemas, building AI agents with tools, streaming AI responses, integrating OpenAI/Anthropic/Google/Cloudflare providers, or encountering AI SDK errors like AI_APICallError, AI_NoObjectGeneratedError, streaming failures, or worker startup limits. Keywords: ai sdk core, vercel ai sdk, generateText, streamText, generateObject, streamObject, ai sdk node, ai sdk server, zod ai schema, ai tools calling, ai agent class, openai sdk, anthropic sdk, google gemini sdk, workers-ai-provider, ai streaming backend, multi-provider ai, ai sdk errors, AI_APICallError, AI_NoObjectGeneratedError, streamText fails, worker startup limit ai
Smart LLM router — save 78% on inference costs. Routes every request to the cheapest capable model across 30+ models from OpenAI, Anthropic, Google, DeepSeek, and xAI.
Integrate TheSys C1 Generative UI API to stream interactive React components (forms, charts, tables) from LLM responses. Supports Vite+React, Next.js, and Cloudflare Workers with OpenAI, Anthropic Claude, and Workers AI. Use when building conversational UIs, AI assistants with rich interactions, or troubleshooting empty responses, theme application failures, streaming issues, or tool calling errors.
Instruments Python and TypeScript code with MLflow Tracing for observability. Triggers on questions about adding tracing, instrumenting agents/LLM apps, getting started with MLflow tracing, or tracing specific frameworks (LangGraph, LangChain, OpenAI, DSPy, CrewAI, AutoGen). Examples - "How do I add tracing?", "How to instrument my agent?", "How to trace my LangChain app?", "Getting started with MLflow tracing", "Trace my TypeScript app"
Interactive tutorial that guides engineers through building their own coding agent (agentic loop) from scratch using raw HTTP calls to an LLM API. Supports Gemini, OpenAI (and compatible endpoints), and Anthropic. Supports TypeScript, Python, Go, and Ruby. Detects progress automatically. Use when someone says "build an agent", "teach me agents", or "/build-agent".