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Kalshi Econ Fed Link Trader

作者 diagnostikon · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install kalshi-econ-fed-link-trader
功能描述
Cross-market strategy that uses CPI bin prices to estimate CPI level, then adjusts Fed rate market positions via a sensitivity model. High CPI means Fed less...
使用说明 (SKILL.md)

\r \r

Kalshi Econ Fed Link Trader\r

\r

This is a template. \r The default signal uses a static CPI-to-Fed sensitivity table -- remix it with live CME FedWatch data, yield curve signals, or Taylor Rule models. \r The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.\r \r

Strategy Overview\r

\r CPI data and Fed rate decisions are deeply linked. This skill reads CPI bin market prices to estimate the current CPI level, then uses a DATA_SENSITIVITY table to compute fair probabilities for Fed rate cut/hold/hike markets. When the Fed market price diverges from the model, trade the edge.\r \r Key advantages:\r

  • Cross-market signal -- uses information from one market type to trade another\r
  • Fundamental economic linkage -- CPI-to-Fed is the most documented macro relationship\r
  • DATA_SENSITIVITY table -- calibrated from historical Fed reaction function\r
  • No external data needed -- all inputs come from Kalshi market prices\r \r

Signal Logic\r

\r

CPI-to-Fed Linkage Model\r

\r

  1. Scan CPI bin markets and extract probability-weighted expected CPI level\r
  2. Look up model Fed probabilities from DATA_SENSITIVITY table\r
  3. Interpolate between table entries for precise CPI levels\r
  4. Compare model probability to Fed market price\r
  5. Trade when |model - market| >= entry_edge\r \r

DATA_SENSITIVITY Table\r

\r | CPI Level | P(Cut) | P(Hold) | P(Hike) |\r |-----------|--------|---------|---------|\r | 1.0% | 85% | 12% | 3% |\r | 2.0% | 55% | 38% | 7% |\r | 2.5% | 20% | 65% | 15% |\r | 3.0% | 5% | 55% | 40% |\r | 4.0% | 1% | 24% | 75% |\r | 5.0% | 0% | 10% | 90% |\r \r

Conviction-Based Sizing\r

\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

Remix Ideas\r

\r

  • CME FedWatch: Compare model to CME futures-implied Fed probabilities\r
  • Yield curve signal: Add 2y-10y spread as additional Fed predictor\r
  • Taylor Rule: Replace sensitivity table with formal Taylor Rule computation\r
  • Real-time CPI nowcast: Use Cleveland Fed nowcast instead of bin prices\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 | 3 | Rate limiting |\r | Max slippage | 15% | Skip if slippage exceeds |\r | Min liquidity | $0 | Disabled by default |\r \r

Installation & Setup\r

\r

clawhub install kalshi-econ-fed-link-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
The automaton cron is set to `null` -- it does not run on a schedule until you configure it in the Simmer UI. `autostart: false` means it won't start automatically on install.\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
All risk parameters are declared in `clawhub.json` as `tunables` and adjustable from the Simmer UI without code changes.\r
\r
| Variable | Default | Purpose |\r
|----------|---------|---------|\r
| `SIMMER_ECON_FEDLINK_ENTRY_EDGE` | `0.10` | Min divergence between model and market to trigger trade |\r
| `SIMMER_ECON_FEDLINK_EXIT_THRESHOLD` | `0.45` | Sell position when price reaches this level |\r
| `SIMMER_ECON_FEDLINK_MAX_POSITION_USD` | `5.00` | Max USDC per trade |\r
| `SIMMER_ECON_FEDLINK_MAX_TRADES_PER_RUN` | `3` | Max trades per execution cycle |\r
| `SIMMER_ECON_FEDLINK_SLIPPAGE_MAX` | `0.15` | Max slippage before skipping (0.15 = 15%) |\r
| `SIMMER_ECON_FEDLINK_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
\r
Review the source before providing live credentials if you require full auditability.\r
安全使用建议
What to consider before installing: - Do not provide your real SOLANA_PRIVATE_KEY or SIMMER_API_KEY until you audit the full code and the simmer-sdk dependency. The Solana private key is high-value and can transfer funds. - The prompt-provided trader.py was truncated; ensure you (or someone you trust) review the entire trader.py and any code in simmer-sdk for network endpoints, telemetry, or credential exfiltration before enabling live trading. - Use the default dry-run mode first (the skill states live trades only run with --live). Test thoroughly with paper/dry-run and small sandbox credentials or accounts. - If you decide to go live: limit financial exposure (set MAX_POSITION_USD small, low max trades, and conservative slippage), use a dedicated account with minimal funds, and rotate keys if you later remove the skill. - Confirm what optional integrations do (e.g., tradejournal or skills.tradejournal) — they may call external services or read local files; disable or inspect them if you don't need them. - Verify clawhub.json/ SKILL.md inconsistencies (SKILL.md front-matter omits SOLANA_PRIVATE_KEY) are resolved so required credentials are clear. If you want, I can: (a) scan the remainder of trader.py (provide full file), (b) fetch and summarize the simmer-sdk package source, or (c) identify exact code locations where credentials are read/used.
功能分析
Type: OpenClaw Skill Name: kalshi-econ-fed-link-trader Version: 1.0.1 The skill is a functional trading bot for Kalshi markets that requires high-risk credentials, specifically a 'SOLANA_PRIVATE_KEY' and 'SIMMER_API_KEY' as seen in SKILL.md and clawhub.json. While the logic in trader.py is consistent with the stated economic strategy (CPI-to-Fed linkage), the requirement for a raw Solana private key in environment variables is a high-risk pattern. The code itself does not show overt signs of exfiltration or malice, but the combination of financial execution capabilities and sensitive credential access fits the criteria for a suspicious classification.
能力标签
cryptorequires-wallet
能力评估
Purpose & Capability
The skill's name/description (cross-market trading using CPI bin prices to trade Fed markets) align with its declared requirements: a Simmer API key and a Solana private key for live execution. The pip dependency (simmer-sdk) is expected for a Simmer-integrated trader.
Instruction Scope
SKILL.md and trader.py describe CPI bin parsing, sensitivity modeling, and trade execution; instructions are scoped to trading. However, front-matter in SKILL.md lists only SIMMER_API_KEY while other sections and clawhub.json require both SIMMER_API_KEY and SOLANA_PRIVATE_KEY (minor inconsistency). The code attempts to import an optional 'tradejournal' from either an external package or a local skills.tradejournal module — importing a 'skills' package could access other skill modules if present, so confirm what that module does. Also, the runtime file provided in the prompt was truncated; I could not inspect the remainder of trader.py to verify there are no network calls or hidden endpoints beyond expected trading APIs.
Install Mechanism
There is no external arbitrary download/install spec. clawhub.json declares a pip dependency on 'simmer-sdk', which matches the SKILL.md and code import. This is a normal install pattern for a Python SDK; review the simmer-sdk package source before using live credentials.
Credentials
Requested environment variables (SIMMER_API_KEY and SOLANA_PRIVATE_KEY) are proportionate to a trading skill and are explicitly documented. Both are high-value credentials (especially the Solana private key). The skill also reads AUTOMATON_MAX optionally; no unrelated secrets or broad platform credentials are requested. The documentation inconsistency about required envs is worth fixing before install.
Persistence & Privilege
The skill is not marked 'always: true' and automaton.autostart is false. It declares an entrypoint for managed automaton execution but won't autostart on install. Autonomous invocation by the agent is allowed (platform default) but not elevated here.
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 kalshi-econ-fed-link-trader
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /kalshi-econ-fed-link-trader 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
v1.0.1
Rescan
v1.0.0
Initial release
元数据
Slug kalshi-econ-fed-link-trader
版本 1.0.1
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

Kalshi Econ Fed Link Trader 是什么?

Cross-market strategy that uses CPI bin prices to estimate CPI level, then adjusts Fed rate market positions via a sensitivity model. High CPI means Fed less... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 87 次。

如何安装 Kalshi Econ Fed Link Trader?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install kalshi-econ-fed-link-trader」即可一键安装,无需额外配置。

Kalshi Econ Fed Link Trader 是免费的吗?

是的,Kalshi Econ Fed Link Trader 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Kalshi Econ Fed Link Trader 支持哪些平台?

Kalshi Econ Fed Link 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 Econ Fed Link Trader?

由 diagnostikon(@diagnostikon)开发并维护,当前版本 v1.0.1。

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