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Kalshi Fed Dot Plot Trader

作者 diagnostikon · GitHub ↗ · v1.0.4 · MIT-0
cross-platform ⚠ suspicious
89
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0
收藏
0
当前安装
5
版本数
在 OpenClaw 中安装
/install kalshi-fed-dot-plot-trader
功能描述
Trades Fed rate markets on Kalshi using FOMC dot plot median implied rate path. Computes fair probability of cut/hike per meeting and trades when market dive...
使用说明 (SKILL.md)

\r \r

Kalshi Fed Dot Plot Trader\r

\r

This is a template.\r The default signal uses a static dot plot to compute fair probabilities -- remix it with live SEP data, Fed funds futures, or OIS-implied rates.\r The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.\r \r

Strategy Overview\r

\r The FOMC dot plot median implies a rate path for 2026. This skill computes fair probability of at least one rate cut (or hike) by each meeting date from the implied path, then trades when Kalshi market prices diverge from these fair values.\r \r Key advantages:\r

  • Dot plot is the Fed's own forecast -- strongest available signal for rate expectations\r
  • Updated quarterly -- each SEP release provides fresh data\r
  • Mean-reverting -- market prices tend to converge to dot-plot-implied probabilities between meetings\r \r

Signal Logic\r

\r

Dot Plot to Fair Probability\r

\r

  1. Load FOMC dot plot median rate path (updated after each SEP)\r
  2. Compute implied cuts from current rate to each quarterly endpoint\r
  3. Map cut count to probability of "at least one cut" by each meeting\r
  4. Compare fair probability to Kalshi market price\r
  5. Trade when |fair - market| >= entry_edge\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

Risk Parameters\r

\r | Parameter | Default | Notes |\r |-----------|---------|-------|\r | Entry edge | 10% | 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 | 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-dot-plot-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_DOT_ENTRY_EDGE` | `0.10` | Min divergence to trigger trade |\r
| `SIMMER_FED_DOT_EXIT_THRESHOLD` | `0.45` | Sell position when price reaches this level |\r
| `SIMMER_FED_DOT_MAX_POSITION_USD` | `5.00` | Max USDC per trade |\r
| `SIMMER_FED_DOT_MAX_TRADES_PER_RUN` | `3` | Max trades per execution cycle |\r
| `SIMMER_FED_DOT_SLIPPAGE_MAX` | `0.15` | Max slippage before skipping trade |\r
| `SIMMER_FED_DOT_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
Before installing or providing credentials, do the following: - Do not export your SOLANA_PRIVATE_KEY or SIMMER_API_KEY until you have audited the code and the simmer-sdk dependency. These are high-value secrets that can execute real trades. - The registry metadata omitted required env vars; treat that as a red flag and ask the publisher why the metadata and SKILL.md disagree. - Review the included trader.py and the simmer-sdk source (GitHub/PyPI) to confirm how the private key is used and whether keys are transmitted or only used locally for signing. - Test in dry-run/paper mode only. Only pass '--live' after you are confident and, preferably, with a minimal-balance account to limit potential loss. - Consider providing credentials via a secure secrets store (not raw environment variables) and restrict the API key's permissions if possible. - If you allow autonomous agent invocation, add a policy that prevents automatic live-mode trades (require manual confirmation for '--live'). If you want, I can: (1) scan the rest of trader.py for any code paths that send data to unexpected endpoints, (2) summarize where SOLANA_PRIVATE_KEY is used in the code, or (3) draft questions to ask the publisher about the metadata mismatch.
功能分析
Type: OpenClaw Skill Name: kalshi-fed-dot-plot-trader Version: 1.0.4 The skill is a specialized trading bot designed to trade Federal Reserve rate markets on Kalshi based on FOMC dot plot projections. It utilizes the 'simmer-sdk' to interact with the Simmer Markets platform and requires sensitive credentials (SIMMER_API_KEY and SOLANA_PRIVATE_KEY) for live trading via the DFlow protocol. The code in trader.py implements legitimate trading logic, including market discovery, fair value calculation, and risk-managed execution, with no evidence of malicious intent, data exfiltration, or unauthorized access.
能力标签
cryptorequires-wallet
能力评估
Purpose & Capability
The skill name/description (Kalshi Fed Dot Plot Trader) matches the observed behavior: it discovers Kalshi markets and uses a Simmer SDK client to execute trades. Requiring SIMMER_API_KEY and a SOLANA_PRIVATE_KEY is consistent with a trading agent that must authenticate to Simmer and sign Solana transactions. However, the registry metadata at the top of the report lists 'Required env vars: none' and 'Primary credential: none' while both SKILL.md and clawhub.json declare SIMMER_API_KEY and SOLANA_PRIVATE_KEY. That inconsistency is notable and unexplained.
Instruction Scope
SKILL.md and trader.py's instructions focus on discovering markets, computing fair probabilities from the Fed dot plot, and executing trades. The runtime instructions and code only reference trading-related environment variables (SIMMER_API_KEY, SOLANA_PRIVATE_KEY, optional TRADING_VENUE, AUTOMATON_MAX_BET) and do not instruct reading unrelated system files or exfiltrating data to unknown endpoints. The skill defaults to dry-run and only performs live trades when '--live' is passed.
Install Mechanism
There is no install spec that downloads arbitrary code; the dependency is a named PyPI package (simmer-sdk) and the SKILL.md / clawhub.json point to a public GitHub repo. This is a normal install surface, but you should review the simmer-sdk source before supplying live credentials, as recommended in SKILL.md.
Credentials
The skill requires two high-value secrets: SIMMER_API_KEY (trading authority) and SOLANA_PRIVATE_KEY (private key used to sign live Solana trades). Those are proportionate to the stated purpose of executing live trades, but they are sensitive and should only be provided after auditing both trader.py and the simmer-sdk. The bigger concern is the mismatch with the registry metadata (which claims no env vars required) — that discrepancy could lead a user to supply credentials without realizing they are needed. The skill also references optional env vars (TRADING_VENUE, AUTOMATON_MAX_BET) not listed in the top-level registry, which is minor but worth noting.
Persistence & Privilege
The skill is not marked always:true and autostart is false. The clawhub.json marks the script as an automaton-managed entrypoint, meaning it can be run by the agent, but default behavior is dry-run. Normal autonomous invocation is allowed by platform settings (disable-model-invocation: false). This combination is expected for a trading skill, but be aware that an agent could potentially invoke the skill with the '--live' flag if given permission, causing real trades.
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-dot-plot-trader
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /kalshi-fed-dot-plot-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
v1.0.4
Rescan
v1.0.3
Rescan
v1.0.2
Rescan
v1.0.1
Rescan
v1.0.0
Initial release
元数据
Slug kalshi-fed-dot-plot-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

Kalshi Fed Dot Plot Trader 是什么?

Trades Fed rate markets on Kalshi using FOMC dot plot median implied rate path. Computes fair probability of cut/hike per meeting and trades when market dive... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 89 次。

如何安装 Kalshi Fed Dot Plot Trader?

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

Kalshi Fed Dot Plot Trader 是免费的吗?

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

Kalshi Fed Dot Plot Trader 支持哪些平台?

Kalshi Fed Dot Plot 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 Dot Plot Trader?

由 diagnostikon(@diagnostikon)开发并维护,当前版本 v1.0.4。

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