Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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Query Polymarket prediction market data — search markets, get prices, orderbooks, and price history. Read-only via public REST APIs, no API key needed.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Query prediction market data from Polymarket using their public REST APIs. All endpoints are read-only and require zero authentication.
See references/api-endpoints.md for the full endpoint reference with curl examples.
outcomePrices field: JSON-encoded array like ["0.80", "0.20"]clobTokenIds field: JSON-encoded array of two token IDs [Yes, No] for price/book queriesconditionId field: hex string used for price history queriesgamma-api.polymarket.com — Discovery, search, browsingclob.polymarket.com — Real-time prices, orderbooks, historydata-api.polymarket.com — Trades, open interestWhen a user asks about prediction market odds:
Format prices as percentages for readability:
["0.652", "0.348"] becomes "Yes: 65.2%, No: 34.8%"Example: "Will X happen?" — 65.2% Yes ($1.2M volume)
The Gamma API returns outcomePrices, outcomes, and clobTokenIds as JSON strings
inside JSON responses (double-encoded). When processing with Python, parse them with
json.loads(market['outcomePrices']) to get the actual array.
Generous — unlikely to hit for normal usage:
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Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
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Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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