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Prediction Market Watcher
作者
m-lwatcher
· GitHub ↗
· v1.0.0
· MIT-0
81
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0
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0
当前安装
1
版本数
在 OpenClaw 中安装
/install prediction-market-watcher
功能描述
Monitor, analyze, and trade on Kalshi and Polymarket prediction markets. Use when the user wants to check open positions, scan for value bets, place bets, ch...
安全使用建议
Do not install or run this skill with live credentials until you are comfortable with the code and where secrets will be stored. Specific actions to consider:
- The registry metadata does NOT list required credentials, but the code and SKILL.md require KALSHI_KEY_ID and a private key file path (KALSHI_KEY_FILE or kalshi-agent/config.json). Treat that as a red flag: ask the publisher to fix the metadata or update it yourself.
- The skill will read an RSA private key file from your workspace and persist trading state (risk_state.json). Store keys in a secure location (not in a shared repo), restrict file permissions, or use a secure secrets store. Do not commit keys to source control.
- Run first in demo mode (the code supports demo=true) and inspect network traffic (which should go only to the Kalshi API base URLs present in the code) before granting live credentials.
- Audit the code if you plan to enable auto-betting (--run). Pay attention to create_order flows and error handling. Consider throttling/limiting auto-bet behavior and keep tight daily caps.
- If you need external notifications (Telegram) or price sources (Brave API), implement and audit them explicitly rather than following the informal SKILL.md instructions.
- If you are not comfortable reviewing code: do not supply live API keys or private keys. Ask the skill publisher to correct the metadata and clarify how secrets are stored and used.
功能分析
Type: OpenClaw Skill
Name: prediction-market-watcher
Version: 1.0.0
The skill bundle is a functional trading agent for Kalshi and Polymarket prediction markets. It includes a robust API client (kalshi_client.py) with RSA-PSS signing, a market analysis engine (analyzer.py), and a dedicated risk management module (risk.py) that enforces strict betting limits ($20/day, $5/bet) and position caps. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found; the code is well-structured and aligns entirely with its stated purpose of assisting a user in monitoring and placing bets on regulated exchanges.
能力评估
Purpose & Capability
The skill claims to monitor and trade on Kalshi/Polymarket and the code implements that. However the registry metadata lists no required environment variables or credentials while both SKILL.md and the code clearly require KALSHI_KEY_ID and KALSHI_KEY_FILE (an RSA private key file) or a config with key_id/key_file. That omission is an incoherence: a trading skill legitimately needs credentials, so the registry should declare them. Also SKILL.md refers to storing keys at kalshi-agent/kalshi.key in the workspace; requesting a private key file is proportionate for the function but must be declared.
Instruction Scope
SKILL.md and the scripts are scoped to market scanning, ranking, and order placement. They instruct reading a workspace config and private key, fetching market data, and writing a local risk_state.json. The doc also suggests external actions (cron job, Telegram messages, Brave API/web search for prices) that are outside the provided code. The provided code itself only talks to Kalshi endpoints and reads/writes local state; it does not implement Telegram or Brave calls. The instructions asking the operator to message an external person (Katie) are out-of-band and not enforced by code — this is a procedural note but not inherently malicious.
Install Mechanism
There is no install spec — the skill is instruction+scripts only. That is lower install risk (no downloads from arbitrary URLs). The package contains Python scripts that will run from the workspace; nothing in the manifest downloads or extracts remote archives.
Credentials
The runtime requires sensitive artifacts (Kalshi API key ID and an RSA private key file) and will read them from env vars or a workspace config, but the registry metadata did not declare these required env vars/credentials. The code also persists trading state and open positions to risk_state.json in the script directory. Requesting Kalshi credentials is proportionate to the trading purpose, but the missing declaration plus the need to place a private key file in the workspace increases the chance a user will accidentally store secrets in an insecure place. No unrelated credentials are requested by code.
Persistence & Privilege
The skill writes and reads local persistent state (risk_state.json) and expects/stores a config.json and private key file in the workspace. It does not request 'always: true' and does not alter other skills or system-wide settings. Local persistence and requiring a private key are normal for a trading bot, but you should be aware these files contain sensitive info and trading history and will live in the workspace by default.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install prediction-market-watcher - 安装完成后，直接呼叫该 Skill 的名称或使用
/prediction-market-watcher触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial release — Kalshi portfolio tracking, market scanning, bet placement, settlement reminders. Polymarket read-only reference included.
元数据
常见问题
Prediction Market Watcher 是什么？
Monitor, analyze, and trade on Kalshi and Polymarket prediction markets. Use when the user wants to check open positions, scan for value bets, place bets, ch... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 81 次。
如何安装 Prediction Market Watcher？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install prediction-market-watcher」即可一键安装，无需额外配置。
Prediction Market Watcher 是免费的吗？
是的，Prediction Market Watcher 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Prediction Market Watcher 支持哪些平台？
Prediction Market Watcher 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Prediction Market Watcher？
由 m-lwatcher（@m-lwatcher）开发并维护，当前版本 v1.0.0。
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