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Found 1,658 Skills
Comprehensive guide to Harper's Model Context Protocol (MCP) interface, covering server setup, client connection, automatic and custom tools, prompts, resources, rate limiting, durable quotas, and the security model. Triggers on tasks involving MCP servers on Harper, AI-client integration, and exposing Harper data or behavior to LLM agents.
Stand up your own fastCRW API server — single binary, Docker, or docker-compose with a bundled search-backend sidecar. Use when the user wants to run crw locally or on their own infra, configure renderers/proxies/ auth/LLM extraction, or understand the embedded vs proxy MCP modes.
Ultra-compressed communication mode. Slash token usage ~75% by speaking like caveman while keeping full technical accuracy. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman-compress <filepath> or "compress memory file"
Build apps with the Claude API or Anthropic SDK. TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`/`claude_agent_sdk`, or user asks to use Claude API, Anthropic SDKs, or Agent SDK. DO NOT TRIGGER when: code imports `openai`/other AI SDK, general programming, or ML/data-science tasks.
Develop AI-powered applications using Genkit in Go. Use when the user asks to build AI features, agents, flows, or tools in Go using Genkit, or when working with Genkit Go code involving generation, prompts, streaming, tool calling, or model providers.
Run vet immediately after ANY logical unit of code changes. Do not batch your changes, do not wait to be asked to run vet, make sure you are proactive.
JavaScript/TypeScript SDK for inference.sh - run AI apps, build agents, integrate 150+ models. Package: @inferencesh/sdk (npm install). Full TypeScript support, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, human approval. Use for: JavaScript integration, TypeScript, Node.js, React, Next.js, frontend apps. Triggers: javascript sdk, typescript sdk, npm install, node.js api, js client, react ai, next.js ai, frontend sdk, @inferencesh/sdk, typescript agent, browser sdk, js integration
Add an AI agent / RAG backend (@convex-dev/agent) to the Convex app.
Modo cavernícola en español. Corta ~75% de tokens hablando como cavernícola técnico. Misma precisión técnica, menos palabrería. Niveles: lite, full (default), ultra. Usar cuando el usuario diga "modo cavernícola", "habla como cavernícola", "menos tokens", "sé breve", o invoque /caveman-es.
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra, ru-lite, ru-full, ru-ultra, ru-notes. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Russian mode: "пещерный режим", "режим пещерного", "/caveman ru", "/caveman-ru". Also auto-triggers when token efficiency is requested.
Techniques to test and bypass AI safety filters, content moderation systems, and guardrails for security assessment