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Found 821 Skills
Build AI agents with Pydantic AI — tools, capabilities, structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydantic_ai, or asks to build an AI agent, add tools/capabilities, stream output, define agents from YAML, or test agent behavior.
Use this when you need to create text card images. It includes generating card HTML and calling the underlying HTML-to-image capability to output the final image. Suitable for scenarios such as WeChat Official Account long article covers, Xiaohongshu/Xiaolvshu graphic covers, etc.
Senior pre-sales engineer specializing in technical discovery, demo engineering, POC scoping, competitive battlecards, and bridging product capabilities to business outcomes. Wins the technical decision so the deal can close.
Surfaces social-layer signals for crypto markets. Three capability groups: news (latest aggregated crypto news feed, filter articles by coin symbol, run full-text keyword searches, fetch a single article in full, and list available upstream platforms — blockbeats, odaily, theblock and similar — for use as filters); sentiment (rank coins by social mention volume over 1h / 4h / 24h, plus per-coin bullish/bearish/neutral counts with an optional time-bucketed trend); vibe (per-contract hotness score over 24h / 72h / 7d / 30d with timeline and sample KOLs per bucket, plus a TOP50 KOL leaderboard sortable by engagement, mentions, or impressions). Triggers: 'latest crypto news', 'BTC headlines', 'search news for X', 'is BTC bullish', 'hottest coins by chatter', 'who is tweeting about <token>', 'vibe score', 'first-mention KOL', and Chinese variants like '最新加密新闻', '搜索新闻', '市场情绪', '情绪排行', 'KOL榜', '热度走势'. Also handles x402/402 payment, quota, MARKET_API_*_OVER_QUOTA, and confirming:true notifications on social endpoints.
MCP Server Construction Methodology — Systematically build production-grade MCP tools to enable AI assistants to connect to external capabilities
Use when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e", "deepseek")
Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.
Provides Tambo with data and capabilities via custom tools, MCP servers, context helpers, and resources. Use when registering tools Tambo can call, connecting MCP servers, adding context to messages, implementing @mentions, or providing additional data sources with defineTool, mcpServers, contextHelpers, or useTamboContextAttachment.
Elite AI/ML Senior Engineer with 20+ years experience. Transforms Claude into a world-class AI researcher and engineer capable of building production-grade ML systems, LLMs, transformers, and computer vision solutions. Use when: (1) Building ML/DL models from scratch or fine-tuning, (2) Designing neural network architectures, (3) Implementing LLMs, transformers, attention mechanisms, (4) Computer vision tasks (object detection, segmentation, GANs), (5) NLP tasks (NER, sentiment, embeddings), (6) MLOps and production deployment, (7) Data preprocessing and feature engineering, (8) Model optimization and debugging, (9) Clean code review for ML projects, (10) Choosing optimal libraries and frameworks. Triggers: "ML", "AI", "deep learning", "neural network", "transformer", "LLM", "computer vision", "NLP", "TensorFlow", "PyTorch", "sklearn", "train model", "fine-tune", "embedding", "CNN", "RNN", "LSTM", "attention", "GPT", "BERT", "diffusion", "GAN", "object detection", "segmentation".
AI-powered crypto trading agent via natural language. Use when the user wants to trade crypto (buy/sell/swap tokens), check portfolio balances, view token prices, transfer crypto, manage NFTs, use leverage, bet on Polymarket, deploy tokens, set up automated trading strategies, submit raw transactions, execute calldata, or send transaction JSON. Supports Base, Ethereum, Polygon, Solana, and Unichain. Comprehensive capabilities include trading, portfolio management, market research, NFT operations, prediction markets, leverage trading, DeFi operations, automation, and arbitrary transaction submission.
Configure popular MCP servers for enhanced agent capabilities
Add email capabilities to AI agents using popular frameworks. Provides pre-built tools for TypeScript and Python frameworks including Vercel AI SDK, LangChain, Clawdbot, OpenAI Agents SDK, and LiveKit Agents. Use when integrating AgentMail with agent frameworks that need email send/receive tools.