Kalshi F1 Constructor Trader
/install kalshi-f1-constructor-trader
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Kalshi F1 Constructor Trader\r
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This is a template.\r The default signal uses static constructor ratings and driver skill modifiers -- remix it with live qualifying data, FP session lap times, or car development trajectory analysis.\r The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.\r \r
Strategy Overview\r
\r Constructor (team) car speed is the single strongest predictor of F1 championship outcomes. A driver in the fastest car wins the championship ~70% of the time historically. This skill rates each constructor's car performance, applies individual driver skill modifiers, and computes fair championship probabilities using a power-law model.\r \r Key advantages:\r
- Car > driver -- constructor advantage explains most championship variance\r
- Stable signal -- car performance changes slowly (major upgrades every 3-5 races)\r
- Markets overweight narratives -- retail traders overreact to single race results while ignoring underlying car pace\r
- Power-law compounding -- small car advantages compound over a 24-race season\r \r
Signal Logic\r
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Constructor Model\r
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- Rate each constructor's car performance (0-100 scale)\r
- Apply individual driver skill modifiers (teammate comparison)\r
- Compute effective driver rating = constructor_base + skill_modifier\r
- Convert to probabilities: P(win) proportional to rating^3 (power law)\r
- Compare model probability to Kalshi market price\r
- Trade when |model - market| >= entry_edge\r \r
Constructor Ratings (2025)\r
\r | Constructor | Rating | Notes |\r |-------------|--------|-------|\r | Red Bull | 95 | Top pace, dominant qualifying |\r | McLaren | 92 | Strong race pace, consistent |\r | Ferrari | 90 | Great qualifier, variable race pace |\r | Mercedes | 88 | Improving development trajectory |\r | Aston Martin | 82 | Best of the rest |\r \r
Conviction-Based Sizing\r
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conviction = min(|edge| / entry_edge, 2.0) / 2.0\rsize = max($1.00, conviction * MAX_POSITION_USD)\r- Larger edge = larger position, capped at MAX_POSITION_USD\r \r
Risk Parameters\r
\r | Parameter | Default | Notes |\r |-----------|---------|-------|\r | Entry edge | 10% | Min model-vs-market divergence to trade |\r | Exit threshold | 45% | Sell when position price reaches this |\r | Max position size | $5.00 USDC | Per market |\r | Max trades per run | 4 | Rate limiting |\r | Max slippage | 15% | Skip if slippage exceeds |\r | Min liquidity | $0 | Disabled by default |\r \r
Installation & Setup\r
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clawhub install kalshi-f1-constructor-trader\r
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Requires: `SIMMER_API_KEY` and `SOLANA_PRIVATE_KEY` environment variables.\r
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## Cron Schedule\r
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Cron is set to `null` -- the skill does not run on a schedule until you configure it in the Simmer UI.\r
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## Safety & Execution Mode\r
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**The skill defaults to dry-run mode. Real trades only execute when `--live` is passed explicitly.**\r
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| Scenario | Mode | Financial risk |\r
|----------|------|----------------|\r
| `python trader.py` | Dry run | None |\r
| Cron / automaton | Dry run | None |\r
| `python trader.py --live` | Live (Kalshi via DFlow) | Real USDC |\r
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## Required Credentials\r
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| Variable | Required | Notes |\r
|----------|----------|-------|\r
| `SIMMER_API_KEY` | Yes | Trading authority. Treat as a high-value credential. |\r
| `SOLANA_PRIVATE_KEY` | Yes | Base58-encoded Solana private key for live trading. |\r
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## Tunables (Risk Parameters)\r
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| Variable | Default | Purpose |\r
|----------|---------|---------|\r
| `SIMMER_F1_CONSTR_ENTRY_EDGE` | `0.10` | Min divergence to trigger trade |\r
| `SIMMER_F1_CONSTR_EXIT_THRESHOLD` | `0.45` | Sell position when price reaches this level |\r
| `SIMMER_F1_CONSTR_MAX_POSITION_USD` | `5.00` | Max USDC per trade |\r
| `SIMMER_F1_CONSTR_MAX_TRADES_PER_RUN` | `4` | Max trades per execution cycle |\r
| `SIMMER_F1_CONSTR_SLIPPAGE_MAX` | `0.15` | Max slippage before skipping trade |\r
| `SIMMER_F1_CONSTR_MIN_LIQUIDITY` | `0` | Min market liquidity USD (0 = disabled) |\r
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## Dependency\r
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`simmer-sdk` is published on PyPI by Simmer Markets.\r
- PyPI: https://pypi.org/project/simmer-sdk/\r
- GitHub: https://github.com/SpartanLabsXyz/simmer-sdk\r
- Publisher: [email protected]\r
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install kalshi-f1-constructor-trader - 安装完成后,直接呼叫该 Skill 的名称或使用
/kalshi-f1-constructor-trader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
Kalshi F1 Constructor Trader 是什么?
Trades F1 Drivers Championship markets on Kalshi using constructor (team) car performance ratings. Drivers in faster cars have structurally higher championsh... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 88 次。
如何安装 Kalshi F1 Constructor Trader?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install kalshi-f1-constructor-trader」即可一键安装,无需额外配置。
Kalshi F1 Constructor Trader 是免费的吗?
是的,Kalshi F1 Constructor Trader 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Kalshi F1 Constructor Trader 支持哪些平台?
Kalshi F1 Constructor Trader 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 Kalshi F1 Constructor Trader?
由 diagnostikon(@diagnostikon)开发并维护,当前版本 v1.0.0。