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Kalshi Crypto Monotonicity Trader

by diagnostikon · GitHub ↗ · v1.0.5 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install kalshi-crypto-monotonicity-trader
Description
Enforces monotonicity constraints on crypto price-level markets on Kalshi. P(BTC > $110k) must always >= P(BTC > $120k). Trades violations by buying underpri...
README (SKILL.md)

\r \r

Kalshi Crypto Monotonicity Trader\r

\r

This is a template. \r The default signal enforces monotonicity on crypto price-level bins -- remix it with real-time order book data, implied volatility surfaces, or cross-exchange price feeds. \r The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.\r \r

Strategy Overview\r

\r Crypto price-level markets on Kalshi price "Will BTC be above $X?" for various thresholds. By definition, P(BTC > $110k) >= P(BTC > $120k) because the first event subsumes the second. When the market violates this, we capture the arbitrage by buying the underpriced contract and selling the overpriced one.\r \r Key advantages:\r

  • Pure math arbitrage -- no model or opinion needed, just logical consistency\r
  • Works for BTC and ETH -- any asset with multiple price-level markets\r
  • Self-correcting -- violations close quickly, so early detection matters\r \r

Signal Logic\r

\r

Monotonicity Check\r

\r

  1. Fetch all crypto price-level markets (BTC above $X, ETH above $Y)\r
  2. Group by asset, sort by price level ascending\r
  3. Verify P(above lower level) >= P(above higher level) for all pairs\r
  4. When violation exceeds violation_threshold, generate paired trades\r \r

Example (with defaults)\r

\r | Market | Level | Market P | Expected | Violation |\r |--------|-------|----------|----------|-----------|\r | BTC > $100k | $100,000 | 45% | >= 35% | -- |\r | BTC > $110k | $110,000 | 35% | >= 20% | -- |\r | BTC > $120k | $120,000 | 38% | \x3C= 35% | 3% |\r \r In the last row, P(>$120k) = 38% > P(>$110k) = 35%, violating monotonicity by 3%.\r \r

Remix Ideas\r

\r

  • Order book depth: Weight violations by available liquidity at each level\r
  • Implied vol surface: Use violation patterns to infer mispriced implied volatility\r
  • Cross-exchange arb: Compare Kalshi levels to Deribit options strikes\r \r

Risk Parameters\r

\r | Parameter | Default | Notes |\r |-----------|---------|-------|\r | Violation threshold | 3% | Min probability gap 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-crypto-monotonicity-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_CRYPTO_MONO_VIOLATION_THRESHOLD` | `0.03` | Min probability gap between adjacent levels to trigger trade |\r
| `SIMMER_CRYPTO_MONO_EXIT_THRESHOLD` | `0.45` | Sell position when price reaches this level |\r
| `SIMMER_CRYPTO_MONO_MAX_POSITION_USD` | `5.00` | Max USDC per trade |\r
| `SIMMER_CRYPTO_MONO_MAX_TRADES_PER_RUN` | `3` | Max trades per execution cycle |\r
| `SIMMER_CRYPTO_MONO_SLIPPAGE_MAX` | `0.15` | Max slippage before skipping (0.15 = 15%) |\r
| `SIMMER_CRYPTO_MONO_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
This skill mostly looks like a legitimate trading helper, but you should NOT provide high-value credentials (especially SOLANA_PRIVATE_KEY) without auditing the Simmer SDK and the skill's full code path for how the key is used. Actions to take before installing or running live: 1) Inspect the simmer-sdk source and confirm why a Solana private key is required (ask the publisher or review docs). 2) Run the skill in dry-run with no live credentials to validate discovery and logic. 3) If you must test live, create restricted API keys or use a dedicated low-value Solana account with minimal funds and rotate keys afterward. 4) Verify clawhub.json / SKILL.md inconsistencies (declared required envs) are resolved by the publisher. 5) Because part of trader.py was truncated in the listing, provide the full file for a final audit — that could change the assessment.
Capability Tags
cryptorequires-wallet
Capability Assessment
Purpose & Capability
Name/description claim Kalshi/crypto monotonicity trading using the Simmer SDK, and the code (trader.py) calls SimmerClient and market-discovery APIs which is coherent. However registry metadata at the top reported 'no required env vars' while SKILL.md and clawhub.json require SIMMER_API_KEY and SOLANA_PRIVATE_KEY — that mismatch is an incoherence. Requiring a SOLANA_PRIVATE_KEY for a Kalshi-targeted strategy is plausible if Simmer settles via Solana/DFlow, but that relationship is not explained in the README; the need for a blockchain private key versus a trading API key should be explicitly justified.
Instruction Scope
SKILL.md instructions focus on discovery, checking monotonicity, and optionally executing trades; trader.py implements market discovery, violation detection and (presumably) order execution. The SKILL.md and code reference other env vars (TRADING_VENUE, AUTOMATON_MAX_BET) and optional integrations (tradejournal) that are not listed in the top-level 'requires' section — the agent will read those env vars if present. The skill performs network I/O to the Simmer API and may import/introduce markets into Simmer; it does not appear to read arbitrary user files, but the code is truncated in the listing so full behavior (e.g., where private keys are used) is not completely visible.
Install Mechanism
This is an instruction/code bundle with no download-from-URL installer. Dependencies are a PyPI package 'simmer-sdk' (declared in SKILL.md and clawhub.json). That is a standard mechanism; the user should still review the simmer-sdk package source before giving live credentials.
Credentials
The skill requires SIMMER_API_KEY (expected for an SDK-based trading skill) and requests SOLANA_PRIVATE_KEY (highly sensitive). The SOLANA_PRIVATE_KEY request is proportionate only if Simmer executes trades on Solana/DFlow and requires a signing key — but that relationship is not demonstrated or audited here. The code also reads optional env vars (AUTOMATON_MAX_BET, TRADING_VENUE) that are not listed in SKILL.md's declared 'required' table, creating an incomplete credential picture.
Persistence & Privilege
The skill is not 'always:true', autostart is false, and it defaults to dry-run. clawhub.json indicates the automaton is 'managed' and an entrypoint exists, so the platform can run it when you enable it, which is expected for a trading skill. No evidence of it modifying other skills or requesting elevated platform-wide privileges.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install kalshi-crypto-monotonicity-trader
  3. After installation, invoke the skill by name or use /kalshi-crypto-monotonicity-trader
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.5
Rescan attempt 5
v1.0.4
Rescan attempt 4
v1.0.3
Rescan attempt 3
v1.0.2
Rescan attempt 2
v1.0.1
Trigger rescan — all metadata consistent
v1.0.0
Kalshi Crypto Monotonicity Trader 1.0.0 — initial release: - Enforces monotonicity constraints between adjacent crypto price-level "above $X" markets on Kalshi. - Automatically detects and trades on violations by buying undervalued lower thresholds and selling overvalued higher thresholds. - Risk parameters, trade limits, and thresholds fully adjustable via Simmer UI. - Supports BTC and ETH markets; requires SIMMER_API_KEY and simmer-sdk. - Runs in paper trading mode by default; live trading requires explicit --live flag.
Metadata
Slug kalshi-crypto-monotonicity-trader
Version 1.0.5
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 6
Frequently Asked Questions

What is Kalshi Crypto Monotonicity Trader?

Enforces monotonicity constraints on crypto price-level markets on Kalshi. P(BTC > $110k) must always >= P(BTC > $120k). Trades violations by buying underpri... It is an AI Agent Skill for Claude Code / OpenClaw, with 120 downloads so far.

How do I install Kalshi Crypto Monotonicity Trader?

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

Is Kalshi Crypto Monotonicity Trader free?

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

Which platforms does Kalshi Crypto Monotonicity Trader support?

Kalshi Crypto Monotonicity Trader is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Kalshi Crypto Monotonicity Trader?

It is built and maintained by diagnostikon (@diagnostikon); the current version is v1.0.5.

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