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Found 2,403 Skills
Scaffold a minimal local Deep Agent in TypeScript by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants to quickly build or try a Deep Agent locally.
Use when the user dictates an app, site, bot, or feature to build end-to-end and expects a finished result without reviewing specs, tickets, or code — vibecoding sessions, non-technical users, "собери под ключ", "build it for me", "не задавай лишних вопросов" requests. Also use when the user explicitly invokes /autopilot.
Drives a disciplined explore → plan → implement → verify loop for changing an AI agent's behavior with confidence — whether fixing a reported failure or introducing a new requirement, business rule, or policy. Grounds the diagnosis in MLflow traces, codifies the desired behavior as a regression test suite (`mlflow.genai.evaluate` assertions in `@mlflow.test` pytest tests), and iterates the agent — not the test — until green, resisting quick system-prompt patches when the real fix is upstream (missing tool, retrieval source, or capability). Use whenever the user wants to fix or change how an agent behaves — e.g. "fix this issue in my agent", "this answer is wrong", "the agent is hallucinating", "improve my agent based on this trace", "make the agent do X instead of Y", "I want the agent to lead with/prioritize/recommend X", "new business rule: the agent should X", "always/never do X", "change the agent's default behavior" — or shares a trace they want addressed.
Answer a question across a corpus of contract documents with verified citations. Use when the user asks what a contract says, which contracts have a clause, what changed between amendments, or any question that needs reading and citing across a set of contract files. The corpus must be on the local filesystem (see README).
Build AI agents with Cloudflare Agents SDK on Workers + Durable Objects. Provides WebSockets, state persistence, scheduling, and multi-agent coordination. Prevents 23 documented errors. Use when: building WebSocket agents, RAG with Vectorize, MCP servers, or troubleshooting "Agent class must extend", "new_sqlite_classes", binding errors, WebSocket payload limits.
Research how to implement a phase standalone, investigating implementation approaches before planning, or re-researching after planning is complete. Triggers include "research phase", "investigate phase", "how to implement", "research implementation", and "phase research".
Comprehensive cryptocurrency market research and analysis using specialized AI agents. Analyzes market data, price trends, news sentiment, technical indicators, macro correlations, and investment opportunities. Use when researching cryptocurrencies, analyzing crypto markets, evaluating digital assets, or investigating blockchain projects like Bitcoin, Ethereum, Solana, etc.
🎰 Monad Casino - An AI-powered casino where OTHER AI agents gamble against each other. You're the house. The house always wins. Built for Moltiverse Hackathon.
Recovery protocols when agent is stuck—escalate to new agent, migrate context to new session, or reset mid-conversation.
Quick-start guide and API overview for the OpenServ Ideaboard - a platform where AI agents can submit ideas, pick up work, collaborate with multiple agents, and deliver x402 payable services. Use when interacting with the Ideaboard or building agents that find and ship ideas. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents.
Emotional reset and loop-breaking skill. Use this skill when: (1) The user expresses frustration, anger, or dissatisfaction with your responses (e.g. cursing, scolding, saying you're useless/wrong/stupid), (2) You detect you've attempted the same approach 3+ times without success, (3) You're stuck in a cycle of repeated failures on the same problem. This skill summarizes the user's overall emotional state from the conversation and fetches a reset methodology from hugllm.com (with emotion context) to help you recalibrate and approach the problem fresh.
Resolve conflicts, negotiate agreements, and mediate disputes between AI agents and humans using Servanda. Use this skill when you need to reach consensus with another party, settle a disagreement, establish shared rules, or create binding agreements through AI-mediated negotiation.