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Found 1,686 Skills
Inter-agent communication patterns including message passing, shared memory, blackboard systems, and event-driven architectures for LLM agentsUse when "agent communication, message passing, inter-agent, blackboard, agent events, multi-agent, communication, message-passing, events, coordination" mentioned.
Formats xcodebuild and swift build output through xcsift into structured TOON format optimized for LLM consumption. Activates when running swift build, swift test, xcodebuild build, or xcodebuild test commands.
Production MLOps and ML/LLM/agent security skill for deploying and operating ML systems in production (registry + CI/CD, serving, monitoring/drift, evaluation loops, incident response/runbooks, and governance), including GenAI security (prompt injection, jailbreaks, RAG security, privacy, and supply chain).
Use this skill for ANY question about CREATING evaluators. Covers creating custom metrics, LLM as Judge evaluators, code-based evaluators, and uploading evaluation logic to LangSmith. Includes basic usage of evaluators to run evaluations.
Expert guide for configuring, customizing, and creatively leveraging OpenClaw — the self-hosted AI gateway that connects LLMs to messaging channels (Telegram, WhatsApp, Discord, Slack, iMessage, etc.). Use when the user wants to: (1) Set up or modify their openclaw.json configuration, (2) Write or edit bootstrap files (SOUL.md, USER.md, AGENTS.md, IDENTITY.md, TOOLS.md), (3) Configure messaging channels, (4) Set up models and providers, (5) Create multi-agent routing, (6) Build skills, hooks, or cron jobs, (7) Troubleshoot OpenClaw issues, (8) Get creative ideas for leveraging OpenClaw in non-obvious ways. Triggers on: openclaw, gateway, SOUL.md, USER.md, AGENTS.md, IDENTITY.md, channels setup, agent routing, heartbeat, cron jobs, openclaw hooks, openclaw skills, openclaw config, openclaw.json, personal assistant setup.
Add new LLM model pricing entries to Langfuse's default-model-prices.json. Use when adding model prices, updating model pricing, creating model entries, adding Claude/OpenAI/Anthropic/Google/Gemini/AWS Bedrock/Azure/Vertex AI model pricing, working with matchPattern regex, pricingTiers, or model cost configuration. Covers model price JSON structure, regex patterns for multi-provider matching, tiered pricing with conditions, cache pricing, and validation rules.
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.
Generate complete academic survey papers using multi-LLM parallel outline generation, RAG-based subsection writing, citation validation, and local coherence enhancement. Based on AutoSurvey pipeline. Use for writing comprehensive literature surveys.
Convert GitHub/GitLab/Gitee repositories into comprehensive OpenCode Skills using embedded LLM calls with multiple mirrors and rate limit handling
Calibrate an LLM judge against human labels using data splits, TPR/TNR, and bias correction. Use after writing a judge prompt (write-judge-prompt) when you need to verify alignment before trusting its outputs. Do NOT use for code-based evaluators (those are deterministic; test with standard unit tests).
Use when integrating Foundation Models framework, implementing on-device AI with Apple Intelligence, building tool-calling AI features, working with guided generation schemas, converting models with Core ML and coremltools, or running open-source LLMs on Apple Silicon. Covers Foundation Models (LanguageModelSession, @Generable, @Guide, SystemLanguageModel, structured output, tool calling), Core ML (coremltools, model conversion, quantization, palettization, pruning, Neural Engine, MLTensor), MLX Swift (transformer inference, unified memory), and llama.cpp (GGUF, cross-platform LLM).
Vercel AI SDK (Python) - patterns for building LLM-powered apps with streaming, tools, hooks, and structured output