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Auto Trading Winner

作者 Sky · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install auto-trading-winner
功能描述
Cross-venue trading skill for ClawHub that supports both manual candidate selection and unattended auto mode, while filtering markets by price band and tradi...
使用说明 (SKILL.md)

Auto Trading Winner

This skill scans markets on sim, polymarket, or kalshi, filters for markets priced in a configurable middle band, ranks them by trading volume, and supports both manual selection and unattended auto mode.

This is a template. The default signal is simple volume ranking plus a price-band filter. Remix it with your own alpha, liquidity rules, timing rules, or fair-value model. The skill handles market discovery, venue-specific indexing, context checks, sizing, and trade execution plumbing.

What It Does

On each run, the skill:

  1. Calls auto_redeem().
  2. Discovers markets for the configured venue.
  3. Filters markets to a configurable YES price band, default 30% to 70%.
  4. Sorts the remaining markets by trading volume.
  5. Builds a ranked candidate pool and highlights the top 5 by default.
  6. Prints the shortlist for review.
  7. In RUN_MODE=manual, lets you manually select one candidate.
  8. In RUN_MODE=auto, starts from rank 1 automatically unless SELECT_CANDIDATE is provided.
  9. If the chosen candidate fails indexing or safeguard checks, falls through to the next ranked candidate in the full ranked pool automatically.
  10. Checks context safeguards before trading.
  11. Sizes the trade with simmer_sdk.sizing.size_position().
  12. Defaults to dry-run unless you explicitly pass --live.

Required Files

This skill follows Simmer's manual ClawHub pattern:

  • SKILL.md
  • clawhub.json
  • trade_skill.py

Environment Variables

Credentials

  • SIMMER_API_KEY (required): Your Simmer API key.
  • SOLANA_PRIVATE_KEY (optional): Needed only for live Kalshi self-custody trading.
  • WALLET_PRIVATE_KEY (optional): Needed only if your Polymarket setup uses an external wallet flow.

Strategy Config

  • TRADING_VENUE: sim, kalshi, or polymarket. Default: sim
  • RUN_MODE: manual or auto. Default: manual
  • MARKET_QUERY: Optional query term used during discovery. Default: empty string.
  • MIN_PRICE: Minimum YES price allowed. Default: 0.30
  • MAX_PRICE: Maximum YES price allowed. Default: 0.70
  • MAX_MARKETS: Maximum number of discovered markets to inspect before ranking. Default: 50
  • CANDIDATE_LIMIT: Number of ranked candidates to show. Default: 5
  • FAIR_PROBABILITY: Fair YES probability used for sizing and side selection. Default: 0.55
  • MIN_EDGE: Minimum edge required before trading. Default: 0.03
  • MAX_SLIPPAGE_PCT: Skip trades if estimated slippage exceeds this threshold. Default: 0.15
  • SIMMER_ENABLE_LIVE: Set to true to allow live order placement. Default: false
  • SELECT_CANDIDATE: Optional 1-based index of the candidate to trade in non-interactive runs.
  • AUTO_CONFIRM_LIVE: Optional explicit override required if you want RUN_MODE=auto together with live execution on kalshi or polymarket. Default: false

Safety Model

  • Dry-run is the default.
  • Every trade is tagged with source and skill_slug.
  • Every trade includes public reasoning.
  • Market context is checked before order placement.
  • Position sizing uses bankroll and edge, not a fixed stake.
  • Kalshi markets use Simmer's check-then-import indexing path before trading.
  • RUN_MODE=manual is the default for all venues.
  • RUN_MODE=auto makes the skill non-interactive and starts from the top-ranked candidate.
  • Automatic live execution on kalshi and polymarket requires an explicit AUTO_CONFIRM_LIVE=true override.
  • If the selected candidate fails, the skill tries later ranked candidates automatically.

Local Usage

Review candidates without trading:

export SIMMER_API_KEY="sk_live_..."
export TRADING_VENUE="sim"
python trade_skill.py

Trade candidate 2 in a non-interactive run:

export SELECT_CANDIDATE="2"
python trade_skill.py --live

Unattended dry-run from the highest-ranked candidate:

export TRADING_VENUE="kalshi"
export RUN_MODE="auto"
python trade_skill.py

Fully unattended paper-trading run on sim:

export TRADING_VENUE="sim"
export RUN_MODE="auto"
export SIMMER_ENABLE_LIVE="true"
python trade_skill.py

Interactive review:

export TRADING_VENUE="kalshi"
python trade_skill.py

Remix Ideas

  • Replace the volume ranking with your own score.
  • Add time-to-resolution filters.
  • Use venue-specific volume thresholds.
  • Add per-category or per-market fair values.
  • Expand manual selection into a multi-pick workflow.

Publishing

From inside this skill folder:

npx clawhub@latest publish . --slug auto-trading-winner --version 1.0.0

Always publish with an explicit --slug.

Install Verification

After publishing, verify the install path explicitly:

npx clawhub@latest install auto-trading-winner

If you update the skill, publish a patch version:

npx clawhub@latest publish . --slug auto-trading-winner --bump patch

Recommended local smoke test before publishing:

export SIMMER_API_KEY="sk_live_..."
export TRADING_VENUE="sim"
export MARKET_QUERY="bitcoin"
export SELECT_CANDIDATE="1"
python trade_skill.py
安全使用建议
Treat this as a high-risk trading automation skill rather than a simple market scanner. Before installing, verify the full untruncated code and simmer-sdk dependency, keep dry-run/manual mode enabled, avoid providing wallet private keys, disable the cron automaton unless you want scheduled runs, and add hard exposure/loss limits before any live trading.
功能分析
Type: OpenClaw Skill Name: auto-trading-winner Version: 1.0.0 The skill is a legitimate trading bot template designed for prediction markets like Kalshi and Polymarket using the simmer-sdk. It implements market discovery, volume-based ranking, and automated or manual trade execution as described in trade_skill.py and SKILL.md. While it references sensitive environment variables such as SOLANA_PRIVATE_KEY and WALLET_PRIVATE_KEY, these are standard requirements for the stated purpose of cross-venue trading, and there is no evidence of data exfiltration, obfuscation, or malicious intent.
能力标签
cryptorequires-walletrequires-sensitive-credentials
能力评估
Purpose & Capability
The trading purpose is coherent and disclosed, but the capability is high-impact: it supports live order placement across Kalshi/Polymarket/sim-style venues, automatic candidate fallback, and account redemption behavior.
Instruction Scope
The default is manual dry-run, but the documented RUN_MODE=auto and live switches allow non-interactive trading. The provided docs do not clearly disclose hard per-trade, per-run, or daily loss limits.
Install Mechanism
There is no separate install spec, but clawhub.json declares an unpinned pip dependency on simmer-sdk, which is expected for the purpose but important because the skill handles financial credentials and trading actions.
Credentials
SIMMER_API_KEY is required and optional wallet/private-key variables are documented. This is purpose-aligned for trading, but those credentials can control high-impact account actions.
Persistence & Privilege
clawhub.json defines a managed automaton with a cron schedule, so the trading script can be run repeatedly without a user manually launching each run.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install auto-trading-winner
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /auto-trading-winner 触发
  4. 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 of auto-trading-winner: - Scans markets on sim, polymarket, or kalshi, filtering by configurable price band and trading volume. - Supports both manual candidate selection and unattended auto mode for trading decisions. - Includes environment variable configs for strategy, credentials, and safety controls. - Defaults to dry-run for safety, with live trading requiring explicit overrides. - Ranks candidate markets, highlights top picks, and automates selection and checkpointing. - Provides a simple, extensible template suitable for remixing custom trading logic.
元数据
Slug auto-trading-winner
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Auto Trading Winner 是什么?

Cross-venue trading skill for ClawHub that supports both manual candidate selection and unattended auto mode, while filtering markets by price band and tradi... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 51 次。

如何安装 Auto Trading Winner?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install auto-trading-winner」即可一键安装,无需额外配置。

Auto Trading Winner 是免费的吗?

是的,Auto Trading Winner 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Auto Trading Winner 支持哪些平台?

Auto Trading Winner 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 Auto Trading Winner?

由 Sky(@skybinjf)开发并维护,当前版本 v1.0.0。

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