跳到正文
cccskills
免费在 GitHub 公开

polymarket

Search Polymarket prediction markets, where prices express market estimates of event probabilities. Retrieve current prices, trading volume, buy and sell orders, and price history to examine expectations and market movements.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Query Polymarket: markets, prices, orderbooks, history.

查看安装方法

适用场景

  • Check market estimates of an event's probability
  • Find prediction markets about a topic
  • Review current prices and buy and sell orders
  • Track price changes over time

包含的文件(3)

  • SKILL.md2.9 KB
  • references/api-endpoints.md4.4 KB
  • scripts/polymarket.py10.0 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Polymarket — Prediction Market Data

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.

When to Use

  • User asks about prediction markets, betting odds, or event probabilities
  • User wants to know "what are the odds of X happening?"
  • User asks about Polymarket specifically
  • User wants market prices, orderbook data, or price history
  • User asks to monitor or track prediction market movements

Key Concepts

  • Events contain one or more Markets (1:many relationship)
  • Markets are binary outcomes with Yes/No prices between 0.00 and 1.00
  • Prices ARE probabilities: price 0.65 means the market thinks 65% likely
  • outcomePrices field: JSON-encoded array like ["0.80", "0.20"]
  • clobTokenIds field: JSON-encoded array of two token IDs [Yes, No] for price/book queries
  • conditionId field: hex string used for price history queries
  • Volume is in USDC (US dollars)

Three Public APIs

  1. Gamma API at gamma-api.polymarket.com — Discovery, search, browsing
  2. CLOB API at clob.polymarket.com — Real-time prices, orderbooks, history
  3. Data API at data-api.polymarket.com — Trades, open interest

Typical Workflow

When a user asks about prediction market odds:

  1. Search using the Gamma API public-search endpoint with their query
  2. Parse the response — extract events and their nested markets
  3. Present market question, current prices as percentages, and volume
  4. Deep dive if asked — use clobTokenIds for orderbook, conditionId for history

Presenting Results

Format prices as percentages for readability:

  • outcomePrices ["0.652", "0.348"] becomes "Yes: 65.2%, No: 34.8%"
  • Always show the market question and probability
  • Include volume when available

Example: "Will X happen?" — 65.2% Yes ($1.2M volume)

Parsing Double-Encoded Fields

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.

Rate Limits

Generous — unlikely to hit for normal usage:

  • Gamma: 4,000 requests per 10 seconds (general)
  • CLOB: 9,000 requests per 10 seconds (general)
  • Data: 1,000 requests per 10 seconds (general)

Limitations

  • This skill is read-only — it does not support placing trades
  • Trading requires wallet-based crypto authentication (EIP-712 signatures)
  • Some new markets may have empty price history
  • Geographic restrictions apply to trading but read-only data is globally accessible

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

1password

免费

Set up the 1Password CLI and use stored passwords or API keys in commands and configuration templates. Choose an authentication method, retrieve secret references, and pass credentials to processes through environment variables.

中文简介正在准备中。当前显示英语简介。

  • Installing and configuring the 1Password CLI
  • Running commands with stored API keys
  • Filling configuration templates with stored secrets
NousResearch/hermes-agent25.5万2026年10月18日 更新

Build an Excel workbook linking the income statement, balance sheet, and cash flow statement. Populate historical figures, create formula-based forecasts, compare scenarios, and check that balances and cash totals agree across all three statements.

中文简介正在准备中。当前显示英语简介。

  • Populating a financial model template with historical data
  • Building linked forecasts across three financial statements
  • Comparing base, upside, and downside scenarios
NousResearch/hermes-agent25.5万2026年10月18日 更新

Adapt existing PyTorch training scripts to use multiple GPUs or machines with limited code changes. The skill guides configuration, launch commands, mixed precision, which uses lower-precision numbers, and DeepSpeed or FSDP settings for distributing training work and memory.

中文简介正在准备中。当前显示英语简介。

  • Move a single-GPU training script to multiple GPUs
  • Configure mixed precision training
  • Set up DeepSpeed or FSDP to reduce memory use
NousResearch/hermes-agent25.5万2026年10月18日 更新

Configure Hermes to run AI models through Actual Computer on your own hardware. Set up either the hosted relay or a local connection, select models, verify responses, and troubleshoot request errors or empty output.

中文简介正在准备中。当前显示英语简介。

  • Connecting Hermes with an Actual inference key
  • Running models through a local Actual daemon
  • Downloading and loading local models
NousResearch/hermes-agent25.5万2026年10月18日 更新

Test an app from the perspective of a frustrated, less technical user. Find confusing steps and barriers, separate actionable usability problems from personal complaints, and produce screenshots, suggested fixes, and prioritized tickets.

中文简介正在准备中。当前显示英语简介。

  • Reviewing usability before a launch or demo
  • Checking the experience of a new user
  • Finding friction in signup and subscription flows
NousResearch/hermes-agent25.5万2026年10月18日 更新

Resolve Git merge conflicts between two agents by comparing both changes and their stated goals. Combine compatible work, explain choices where designs differ, and verify the merged result with project builds or tests.

中文简介正在准备中。当前显示英语简介。

  • Resolving conflicts between branches edited by two agents
  • Integrating changes from parallel worktrees
  • Reviewing reasons for conflicting design choices
NousResearch/hermes-agent25.5万2026年10月18日 更新

查看 NousResearch 的全部技能

报告此技能的问题