← 返回 Skills 市场

Kalshi F1 Teammate Anti Trader

Name: Kalshi F1 Teammate Anti Trader
Author: diagnostikon

作者 diagnostikon · GitHub ↗ · v1.0.4 · MIT-0

cross-platform ⚠ suspicious

总下载

当前安装

版本数

在 OpenClaw 中安装

/install kalshi-f1-teammate-anti-trader

功能描述

Trades F1 Drivers Championship markets on Kalshi using teammate anti-correlation. Teammates share the same car so their probabilities are structurally linked...

使用说明 (SKILL.md)

\r \r

Kalshi F1 Teammate Anti-Correlation Trader\r

This is a template.\r The default signal uses static dominance ratios -- remix it with live head-to-head qualifying/race data for dynamic dominance estimation.\r The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.\r \r

Strategy Overview\r

\r F1 teammates share the same car, meaning their championship probabilities are structurally anti-correlated. If Verstappen's probability rises, Lawson's should fall (they share Red Bull's probability budget). Markets are slow to adjust both sides of teammate pairs simultaneously, creating exploitable relative mispricings.\r \r Key advantages:\r

Structural constraint -- teammate probabilities must sum to roughly the team's total share\r
Dominance ratios are stable -- intra-team hierarchy rarely changes mid-season\r
Markets adjust asymmetrically -- one driver's price moves but teammate's lags\r
Pairs trading -- natural hedge structure reduces directional risk\r \r

Signal Logic\r

Teammate Anti-Correlation Model\r

Define teammate pairs (same constructor)\r
Set dominance ratios (who captures what % of team total)\r
For each pair, sum their market prices = team_total\r
Compute fair split: fair_A = team_total * dominance, fair_B = team_total * (1-dominance)\r
Trade when |fair - market| >= entry_edge for either driver\r \r

Teammate Pairs (2025)\r

\r | Pair | Constructor | Dominance | Team Total |\r |------|-------------|-----------|------------|\r | Verstappen / Lawson | Red Bull | 85%/15% | ~36% |\r | Leclerc / Hamilton | Ferrari | 50%/50% | ~20% |\r | Russell / Antonelli | Mercedes | 70%/30% | ~8% |\r | Piastri / Norris | McLaren | 40%/60% | ~36% |\r \r

Conviction-Based Sizing\r

conviction = min(|edge| / entry_edge, 2.0) / 2.0\r
size = 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 | 8% | Min fair-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

clawhub install kalshi-f1-teammate-anti-trader\r
```\r
\r
Requires: `SIMMER_API_KEY` and `SOLANA_PRIVATE_KEY` environment variables.\r
\r
## Cron Schedule\r
\r
Cron is set to `null` -- the skill does not run on a schedule until you configure it in the Simmer UI.\r
\r
## Safety & Execution Mode\r
\r
**The skill defaults to dry-run mode. Real trades only execute when `--live` is passed explicitly.**\r
\r
| 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
\r
## Required Credentials\r
\r
| 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
\r
## Tunables (Risk Parameters)\r
\r
| Variable | Default | Purpose |\r
|----------|---------|---------|\r
| `SIMMER_F1_TEAM_ENTRY_EDGE` | `0.08` | Min divergence to trigger trade |\r
| `SIMMER_F1_TEAM_EXIT_THRESHOLD` | `0.45` | Sell position when price reaches this level |\r
| `SIMMER_F1_TEAM_MAX_POSITION_USD` | `5.00` | Max USDC per trade |\r
| `SIMMER_F1_TEAM_MAX_TRADES_PER_RUN` | `4` | Max trades per execution cycle |\r
| `SIMMER_F1_TEAM_SLIPPAGE_MAX` | `0.15` | Max slippage before skipping trade |\r
| `SIMMER_F1_TEAM_MIN_LIQUIDITY` | `0` | Min market liquidity USD (0 = disabled) |\r
\r
## Dependency\r
\r
`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

安全使用建议

This skill is plausibly a real trading bot and requires two high-value secrets (SIMMER_API_KEY and SOLANA_PRIVATE_KEY) to execute live trades. Before installing or providing credentials: 1) Confirm you trust the publisher and the simmer-sdk package (review its PyPI page and GitHub repo referenced in SKILL.md). 2) Fix or ask the publisher to fix the registry metadata so required envs and pip dependency are declared consistently (current top-level metadata omitted them). 3) Only run in dry-run mode initially (default) and never pass --live until you have tested behavior and audited simmer-sdk. 4) If you must provide a private key, prefer using a dedicated/truncated test account with minimal funds and revoke/regenerate keys if anything seems off. 5) Optionally inspect simmer-sdk source and run trader.py in an isolated environment to observe network activity. The main red flag here is the inconsistency between the registry summary and the included files (environment and install requirements); that should be resolved before trusting sensitive credentials.

功能分析

Type: OpenClaw Skill Name: kalshi-f1-teammate-anti-trader Version: 1.0.4 The skill implements an automated trading strategy for Kalshi F1 markets, which is a high-risk financial activity. It requires the user to provide highly sensitive credentials, specifically a 'SOLANA_PRIVATE_KEY' and 'SIMMER_API_KEY', via environment variables (trader.py, SKILL.md). While the code logic appears consistent with its stated purpose and includes basic safeguards like a dry-run mode and slippage limits, the handling of raw private keys and the reliance on an external dependency (simmer-sdk) for trade execution constitute significant security and financial risks.

能力标签

cryptorequires-wallet

能力评估

ℹ Purpose & Capability

The skill's stated purpose (automated trading on Kalshi using teammate anti-correlation) aligns with the code and SKILL.md: the script calls into simmer_sdk, constructs trade signals, and can execute live trades via Solana/DFlow. However the registry metadata at the top of the report lists no required environment variables or primary credential, while SKILL.md and clawhub.json both require SIMMER_API_KEY and SOLANA_PRIVATE_KEY. That metadata omission is an inconsistency (likely an authoring error) but it is material: a trading skill legitimately needs those secrets.

✓ Instruction Scope

SKILL.md and trader.py limit actions to market discovery, signal generation, and (optionally) executing trades. The README emphasizes dry-run by default and requires an explicit --live flag to perform real trades. The instructions do not request unrelated system files or credentials beyond the trading API key and Solana private key, nor do they instruct exfiltration to unexpected endpoints.

ℹ Install Mechanism

There is no formal 'install spec' in the top-level registry, but SKILL.md and clawhub.json both declare a pip dependency on 'simmer-sdk' and the code imports simmer_sdk. Using pip to install simmer-sdk is a reasonable mechanism. The inconsistency is that the registry initially reported 'No install spec' and 'Required env vars: none' while the included files do declare pip and env requirements — this mismatch should be fixed. No downloads from unknown URLs or archive extraction are present.

⚠ Credentials

The skill requires SIMMER_API_KEY and SOLANA_PRIVATE_KEY (base58 private key) for live trading, which is proportionate to its purpose but represents high-value secrets. The registry metadata failing to advertise these required variables is concerning because a user could install the skill without realizing it requests private keys. The script also reads optional envs like TRADING_VENUE and AUTOMATON_MAX_BET; those are plausible but should be documented consistently. Treat the SOLANA_PRIVATE_KEY as highly sensitive.

✓ Persistence & Privilege

The skill is not marked always:true and autostart is false in clawhub.json. It can be invoked autonomously (model invocation is not disabled), which is normal for skills. The skill does not request to modify other skills' configurations or system-wide settings. The automaton entrypoint is trader.py (managed), which is expected for an agent-run trading skill.

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 kalshi-f1-teammate-anti-trader
安装完成后，直接呼叫该 Skill 的名称或使用 /kalshi-f1-teammate-anti-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

版本历史

v1.0.4

Rescan

v1.0.3

Rescan

v1.0.2

Rescan

v1.0.1

Rescan

v1.0.0

Initial release

元数据

Slug kalshi-f1-teammate-anti-trader

版本 1.0.4

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 5

常见问题