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Kalshi Fed Temporal Mono Trader

作者 diagnostikon · GitHub ↗ · v1.0.2 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install kalshi-fed-temporal-mono-trader
功能描述
Exploits temporal monotonicity violations in Fed rate markets on Kalshi. P(rate cut by June) >= P(rate cut by April) always -- if April is priced higher than...
使用说明 (SKILL.md)

\r \r

Kalshi Fed Temporal Monotonicity Trader\r

\r

This is a template.\r The default signal detects temporal monotonicity violations in Fed rate markets -- remix it with live yield curve data, Fed funds futures, or options-implied probabilities.\r The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.\r \r

Strategy Overview\r

\r Fed rate cut/hike markets across different meeting dates must satisfy temporal monotonicity: the probability of a cut "by June" must be >= the probability of a cut "by April", since June includes April. When this invariant is violated, we have a pure structural arbitrage.\r \r Key advantages:\r

  • Mathematical certainty -- this is a logical invariant, not a statistical edge\r
  • No model risk -- the relationship P(by later) >= P(by earlier) is always true\r
  • Self-correcting -- violations are temporary mispricings that must converge\r \r

Signal Logic\r

\r

Temporal Monotonicity\r

\r

  1. Scan all Fed rate cut/hike markets on Kalshi\r
  2. Group by year and type (cut vs hike)\r
  3. Sort chronologically by FOMC meeting date\r
  4. Compare: if P(cut by April) > P(cut by June) + threshold, violation detected\r
  5. Buy YES on the later (underpriced) date market\r \r

Conviction-Based Sizing\r

\r

  • conviction = min(violation_size / violation_threshold, 2.0) / 2.0\r
  • size = max($1.00, conviction * MAX_POSITION_USD)\r
  • Larger violations = larger positions, capped at MAX_POSITION_USD\r \r

Risk Parameters\r

\r | Parameter | Default | Notes |\r |-----------|---------|-------|\r | Violation threshold | 3% | Min difference to trigger 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-fed-temporal-mono-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_FED_TEMP_VIOLATION_THRESHOLD` | `0.03` | Min violation size to trigger trade |\r
| `SIMMER_FED_TEMP_EXIT_THRESHOLD` | `0.45` | Sell position when price reaches this level |\r
| `SIMMER_FED_TEMP_MAX_POSITION_USD` | `5.00` | Max USDC per trade |\r
| `SIMMER_FED_TEMP_MAX_TRADES_PER_RUN` | `3` | Max trades per execution cycle |\r
| `SIMMER_FED_TEMP_SLIPPAGE_MAX` | `0.15` | Max slippage before skipping trade |\r
| `SIMMER_FED_TEMP_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
This skill appears internally consistent for a Kalshi/Simmer market trader. Before providing live credentials: 1) Run the skill in dry-run mode only and validate behavior. 2) Audit the simmer-sdk package (PyPI and its GitHub) to ensure it is the expected library and contains no hidden network calls. 3) Never paste your primary Solana private key into unknown code — if you must test live, use a purpose-limited test wallet with minimal funds. 4) Keep the skill in dry-run by default; only use --live after manual review. 5) Consider running the skill in an isolated environment/container and monitoring outgoing network calls to confirm it only communicates with intended Simmer/Kalshi/DFlow endpoints.
功能分析
Type: OpenClaw Skill Name: kalshi-fed-temporal-mono-trader Version: 1.0.2 The skill bundle implements a legitimate-looking arbitrage strategy for Kalshi Fed rate markets but is classified as suspicious due to its requirement for a high-value credential (SOLANA_PRIVATE_KEY) and its dependency on an external package (simmer-sdk). While trader.py does not explicitly exfiltrate the key, the script's logic delegates trade execution to the third-party SDK, which creates a significant supply-chain risk for credential theft. The SKILL.md and clawhub.json files explicitly prompt the user to provide this private key, which is a high-risk behavior in the context of unvetted agent skills.
能力标签
cryptorequires-wallet
能力评估
Purpose & Capability
Name/description (temporal monotonicity arbitrage on Kalshi) match the implementation: the skill uses a simmer-sdk client to discover/import Kalshi markets and has logic to buy/sell markets. Required items (SIMMER_API_KEY, SOLANA_PRIVATE_KEY, simmer-sdk) are appropriate for interacting with the Simmer API and executing trades on Solana/DFlow.
Instruction Scope
SKILL.md and trader.py scope are consistent: market discovery, analysis, and trade execution. The instructions reference only Simmer endpoints, the simmer SDK, and an optional trade journal. The skill does not instruct reading unrelated system files or contacting unexpected external endpoints in the provided code/instructions.
Install Mechanism
No binary install spec in the manifest (instruction-only), but the package requires the third-party pip package 'simmer-sdk' (PyPI). This is a moderate-risk install mechanism — users should review the simmer-sdk package source and PyPI publisher before installing.
Credentials
The skill requests two high-sensitivity environment variables: SIMMER_API_KEY (expected) and SOLANA_PRIVATE_KEY (expected for live Solana trading). These are proportionate to the stated purpose, but SOLANA_PRIVATE_KEY is high-value and should only be provided for live mode after auditing the code and dependencies.
Persistence & Privilege
The skill is not always-enabled and does not request system-wide privileges. It uses simmer-sdk config helpers (load_config/update_config) which appear to manage its own config. Nothing indicates it modifies other skills or system settings.
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-fed-temporal-mono-trader
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /kalshi-fed-temporal-mono-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
v1.0.2
Rescan
v1.0.1
Rescan
v1.0.0
Initial release
元数据
Slug kalshi-fed-temporal-mono-trader
版本 1.0.2
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 3
常见问题

Kalshi Fed Temporal Mono Trader 是什么?

Exploits temporal monotonicity violations in Fed rate markets on Kalshi. P(rate cut by June) >= P(rate cut by April) always -- if April is priced higher than... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 83 次。

如何安装 Kalshi Fed Temporal Mono Trader?

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

Kalshi Fed Temporal Mono Trader 是免费的吗?

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

Kalshi Fed Temporal Mono Trader 支持哪些平台?

Kalshi Fed Temporal Mono 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 Fed Temporal Mono Trader?

由 diagnostikon(@diagnostikon)开发并维护,当前版本 v1.0.2。

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