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diagnostikon

Kalshi Fed Dot Plot Trader

by diagnostikon · GitHub ↗ · v1.0.4 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install kalshi-fed-dot-plot-trader
Description
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...
README (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
Usage Guidance
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.
Capability Analysis
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.
Capability Tags
cryptorequires-wallet
Capability Assessment
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.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install kalshi-fed-dot-plot-trader
  3. After installation, invoke the skill by name or use /kalshi-fed-dot-plot-trader
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.4
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v1.0.3
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v1.0.2
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v1.0.1
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v1.0.0
Initial release
Metadata
Slug kalshi-fed-dot-plot-trader
Version 1.0.4
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 5
Frequently Asked Questions

What is Kalshi Fed Dot Plot Trader?

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... It is an AI Agent Skill for Claude Code / OpenClaw, with 89 downloads so far.

How do I install Kalshi Fed Dot Plot Trader?

Run "/install kalshi-fed-dot-plot-trader" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Kalshi Fed Dot Plot Trader free?

Yes, Kalshi Fed Dot Plot Trader is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Kalshi Fed Dot Plot Trader support?

Kalshi Fed Dot Plot Trader is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Kalshi Fed Dot Plot Trader?

It is built and maintained by diagnostikon (@diagnostikon); the current version is v1.0.4.

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