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diagnostikon

Kalshi Econ Bin Sum Trader

by diagnostikon · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install kalshi-econ-bin-sum-trader
Description
Trades CPI range bin markets on Kalshi using the constraint that mutually exclusive bins must sum to ~100%. Normalizes and trades the most mispriced bin when...
README (SKILL.md)

\r \r

Kalshi Econ Bin Sum Trader\r

\r

This is a template. \r The default signal uses the fundamental constraint that mutually exclusive outcome bins must sum to 100% -- remix it with Bayesian priors, consensus forecasts, or cross-event correlation 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 range bin markets on Kalshi price each outcome bin independently. Since exactly one bin must resolve YES, the probabilities must sum to 100%. When the market sum deviates beyond tolerance, at least one bin is mispriced. This skill normalizes the distribution and trades the most mispriced bin.\r \r Key advantages:\r

  • Mathematical certainty -- bins MUST sum to 100%, any deviation is a guaranteed mispricing\r
  • No forecasting needed -- the strategy is model-free, relying purely on arbitrage math\r
  • Self-correcting -- as the sum approaches 100%, signals disappear (no stale trades)\r
  • Works across any bin-style market -- CPI, GDP, unemployment, any mutually exclusive set\r \r

Signal Logic\r

\r

Bin Sum Normalization\r

\r

  1. Group CPI bin markets by event (e.g., "March 2026 CPI")\r
  2. Sum all bin prices in the group\r
  3. If |sum - 1.0| > sum_tolerance, normalize: fair_prob = price / sum\r
  4. Compute edge per bin: edge = fair_prob - market_price\r
  5. Trade the bin with the largest absolute edge\r \r

Example\r

\r | Bin | Market Price | Fair (normalized) | Edge | Action |\r |-----|-------------|-------------------|------|--------|\r | CPI \x3C 2.0% | 5% | 4.8% | -0.2% | Hold |\r | CPI 2.0-2.5% | 25% | 23.8% | -1.2% | Hold |\r | CPI 2.5-3.0% | 35% | 33.3% | -1.7% | BUY NO |\r | CPI 3.0-3.5% | 30% | 28.6% | -1.4% | Hold |\r | CPI > 3.5% | 10% | 9.5% | -0.5% | Hold |\r | Sum | 105% | 100% | | |\r \r

Conviction-Based Sizing\r

\r

  • conviction = min(|edge| / deviation, 2.0) / 2.0\r
  • size = max($1.00, conviction * MAX_POSITION_USD)\r
  • Larger edge relative to total deviation = larger position\r \r

Remix Ideas\r

\r

  • Cross-event sum: Apply same logic to GDP, unemployment, or Fed rate bins\r
  • Consensus prior: Weight normalization toward consensus CPI forecasts\r
  • Multi-bin arbitrage: Trade multiple bins simultaneously for hedged positions\r
  • Rolling rebalance: Re-run as market moves to capture dynamic mispricing\r \r

Risk Parameters\r

\r | Parameter | Default | Notes |\r |-----------|---------|-------|\r | Sum tolerance | 5% | Min deviation from 100% before trading |\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-bin-sum-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_BINSUM_SUM_TOLERANCE` | `0.05` | Min deviation from 100% sum before trading |\r
| `SIMMER_ECON_BINSUM_EXIT_THRESHOLD` | `0.45` | Sell position when price reaches this level |\r
| `SIMMER_ECON_BINSUM_MAX_POSITION_USD` | `5.00` | Max USDC per trade |\r
| `SIMMER_ECON_BINSUM_MAX_TRADES_PER_RUN` | `3` | Max trades per execution cycle |\r
| `SIMMER_ECON_BINSUM_SLIPPAGE_MAX` | `0.15` | Max slippage before skipping (0.15 = 15%) |\r
| `SIMMER_ECON_BINSUM_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 appears to be a reasonable trading template, but there are red flags you should address before installing or giving it real credentials: 1) Metadata mismatch — the registry summary showed no required envs, but SKILL.md and clawhub.json require SIMMER_API_KEY and SOLANA_PRIVATE_KEY; confirm which is authoritative. 2) The SOLANA_PRIVATE_KEY is highly sensitive — only provide it if you fully trust the simmer-sdk implementation and understand how the key is used and stored. 3) Review the simmer-sdk PyPI project and its GitHub source yourself (or have a developer audit it) to ensure the SDK doesn't forward keys to unexpected endpoints. 4) The included trader.py in the listing was truncated; request the full source and inspect the remaining code paths for any data exfiltration, unexpected network calls, or opaque subprocess execution before running live. 5) Test in dry-run mode only, with minimal funds, and prefer ephemeral or restricted keys if possible (e.g., an API key with only test/paper permissions). If you can't audit the remaining code, treat the skill as untrusted for live trading.
Capability Analysis
Type: OpenClaw Skill Name: kalshi-econ-bin-sum-trader Version: 1.0.1 The skill is a legitimate trading bot designed to arbitrage CPI range bin markets on Kalshi by identifying mispriced outcomes that deviate from the mathematical 100% sum constraint. It utilizes the 'simmer-sdk' for market discovery and trade execution, requiring standard API and private keys for live operation. The code in 'trader.py' includes robust safeguards such as slippage limits, liquidity requirements, and time-to-resolution checks, with no evidence of data exfiltration, malicious prompt injection, or unauthorized access.
Capability Tags
cryptorequires-wallet
Capability Assessment
Purpose & Capability
The skill's name and description claim a Kalshi/CPI bin-sum trading strategy and the code and docs call out using simmer-sdk to interact with Kalshi — that is coherent. However the registry metadata presented to the evaluator initially listed no required env vars while SKILL.md and clawhub.json explicitly require SIMMER_API_KEY and SOLANA_PRIVATE_KEY. That metadata mismatch is an inconsistency that should be resolved.
Instruction Scope
SKILL.md and trader.py instruct the agent to use the SIMMER_API_KEY and (in some sections) a SOLANA_PRIVATE_KEY for live trading. The instructions reference importing markets, executing trades, and integrating with DFlow/Solana — all networked actions. There is no instruction to read unrelated local files, but the provided trader.py is truncated in the package listing ("…[truncated]") so parts of runtime behavior are not visible; that missing code could change the assessment.
Install Mechanism
This is instruction-only from the platform perspective (no custom binary install). Dependencies are limited to simmer-sdk (PyPI) and optional tradejournal; requiring a PyPI package is expected for an SDK-based trader. There is no external arbitrary-download install step in the manifest.
Credentials
The skill requires SIMMER_API_KEY (expected for the Simmer SDK) and requests a SOLANA_PRIVATE_KEY for live trading; a Solana private key grants broad signing power and is highly sensitive. These credentials are plausible for executing live trades via a Solana-based settlement flow, but the README/metadata inconsistency and lack of an explicit explanation of why Kalshi trades require a Solana key increases risk. Ensure the Solana key scope and how it is used are audited before supplying it.
Persistence & Privilege
The skill does not request always:true, autostart is false, and automaton entrypoint is present but not started by default. Autonomous invocation is allowed (platform default), which is normal for skills; there is no evidence of the skill modifying other skills or global agent settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install kalshi-econ-bin-sum-trader
  3. After installation, invoke the skill by name or use /kalshi-econ-bin-sum-trader
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
Rescan
v1.0.0
Initial release
Metadata
Slug kalshi-econ-bin-sum-trader
Version 1.0.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Kalshi Econ Bin Sum Trader?

Trades CPI range bin markets on Kalshi using the constraint that mutually exclusive bins must sum to ~100%. Normalizes and trades the most mispriced bin when... It is an AI Agent Skill for Claude Code / OpenClaw, with 82 downloads so far.

How do I install Kalshi Econ Bin Sum Trader?

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

Is Kalshi Econ Bin Sum Trader free?

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

Which platforms does Kalshi Econ Bin Sum Trader support?

Kalshi Econ Bin Sum Trader is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Kalshi Econ Bin Sum Trader?

It is built and maintained by diagnostikon (@diagnostikon); the current version is v1.0.1.

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