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diagnostikon

Kalshi Eth Staking Yield Trader

by diagnostikon · GitHub ↗ · v1.0.3 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install kalshi-eth-staking-yield-trader
Description
Trades ETH price markets on Kalshi using the 4% staking yield as a fundamental price floor. When markets underprice ETH relative to the yield-implied floor,...
README (SKILL.md)

\r \r

Kalshi ETH Staking Yield Trader\r

\r

This is a template.\r The default signal uses a static 4% staking yield as a price floor -- remix it with live Lido/Rocket Pool yield data, validator queue depth, or MEV reward estimates.\r The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.\r \r

Strategy Overview\r

\r ETH staking yields approximately 4% APR, creating a fundamental floor for ETH price. Rational stakers will not sell below the yield-implied value. This skill computes that floor for each market's time horizon and trades when Kalshi prices imply ETH below the floor.\r \r Key advantages:\r

  • Fundamental floor -- staking yield provides a minimum return that supports price\r
  • Time-adjusted -- yield floor scales with days to market resolution\r
  • Conservative model -- only accounts for yield, not price appreciation upside\r \r

Signal Logic\r

\r

Yield Floor Model\r

\r

  1. Fetch active ETH price markets from Kalshi\r
  2. Extract price target from each market question\r
  3. Compute yield floor: floor = base_price * (1 + yield% * days/365)\r
  4. Compute fair probability based on target vs floor relationship\r
  5. Trade when |fair - market| >= entry_edge\r \r

Example (with defaults, base=$3500, yield=4%)\r

\r | Market | Target | Days | Floor | Fair P | Market P | Action |\r |--------|--------|------|-------|--------|----------|--------|\r | ETH above $3000 | $3000 | 30 | $3511 | 85% | 72% | BUY YES |\r | ETH above $4000 | $4000 | 30 | $3511 | 40% | 45% | Hold |\r | ETH above $5000 | $5000 | 30 | $3511 | 15% | 28% | BUY NO |\r \r

Conviction-Based Sizing\r

\r

  • conviction = min(|edge| / entry_edge, 2.0) / 2.0\r
  • size = max($5.00, conviction * MAX_POSITION_USD)\r \r

Remix Ideas\r

\r

  • Live yield API: Pull real-time staking yield from Lido/Rocket Pool\r
  • Validator queue depth: Queue length affects future yield expectations\r
  • MEV rewards: Include MEV as additional yield component\r
  • Macro overlay: Adjust floor based on Fed rate decisions\r \r

Risk Parameters\r

\r | Parameter | Default | Notes |\r |-----------|---------|-------|\r | Entry edge | 8% | Min model-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 | Staking yield | 4.0% | Annual staking yield assumption |\r | Base ETH price | $3500 | Current ETH price baseline |\r \r

Installation & Setup\r

\r

clawhub install kalshi-eth-staking-yield-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
| Variable | Default | Purpose |\r
|----------|---------|---------|\r
| `SIMMER_ETH_STAKE_ENTRY_EDGE` | `0.08` | Min divergence to trigger trade |\r
| `SIMMER_ETH_STAKE_EXIT_THRESHOLD` | `0.45` | Sell position when price reaches this level |\r
| `SIMMER_ETH_STAKE_MAX_POSITION_USD` | `5.00` | Max USDC per trade |\r
| `SIMMER_ETH_STAKE_MAX_TRADES_PER_RUN` | `3` | Max trades per execution cycle |\r
| `SIMMER_ETH_STAKE_SLIPPAGE_MAX` | `0.15` | Max slippage before skipping (15%) |\r
| `SIMMER_ETH_STAKE_MIN_LIQUIDITY` | `0` | Min market liquidity USD (0 = disabled) |\r
| `SIMMER_ETH_STAKE_YIELD_PCT` | `4.0` | Annual staking yield assumption |\r
| `SIMMER_ETH_STAKE_BASE_PRICE` | `3500` | Current ETH price baseline |\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 do what it claims (a Kalshi ETH staking-yield based trader). Before installing: 1) Audit the simmer-sdk package/source on PyPI/GitHub (the skill depends on it). 2) Test in dry-run/paper mode only (the default) and confirm behavior before passing --live. 3) If you enable live trading, use a wallet with limited funds and consider a dedicated API key/wallet you can revoke. 4) Note the small metadata mismatch: SKILL.md initially lists only SIMMER_API_KEY but the skill and clawhub.json also require SOLANA_PRIVATE_KEY; verify you only provide that private key if you intend to trade live. 5) Be aware the script respects TRADING_VENUE and AUTOMATON_MAX_BET environment variables (not documented in the header); if you use those env vars they will affect behavior. If you need higher assurance, request a full audit of the simmer-sdk package and the remainder of trader.py (the provided file was truncated in the listing).
Capability Tags
cryptorequires-wallet
Capability Assessment
Purpose & Capability
Name/description, pip dependency (simmer-sdk), and the code (trader.py) all implement a trading strategy for Kalshi using a stake-yield-derived floor. Requiring SIMMER_API_KEY and a Solana private key is proportionate for a skill that discovers/imports markets and executes live trades.
Instruction Scope
SKILL.md and trader.py stay within the trading domain (market discovery, pricing model, order placement). Minor inconsistency: top SKILL.md metadata lists only SIMMER_API_KEY as required, but later documentation, clawhub.json, and the code indicate SOLANA_PRIVATE_KEY is required for live trades. The skill does not appear to read any unrelated sensitive files or external endpoints beyond the expected Simmer/Kalshi/solana integrations.
Install Mechanism
No install spec (instruction-only plus a code file). The dependency is 'simmer-sdk' on PyPI, which is expected for this functionality; as with any third-party package, review the package source before supplying live credentials. No arbitrary download URLs or archive extraction are used.
Credentials
The primary sensitive variables (SIMMER_API_KEY, SOLANA_PRIVATE_KEY) are appropriate for a trading skill. The code also reads additional environment variables that are not listed in the top-level metadata (e.g., TRADING_VENUE and AUTOMATON_MAX_BET). These are not highly sensitive, but you should be aware the skill will honor them if present. No unrelated cloud credentials or broad system tokens are requested.
Persistence & Privilege
The skill is not force-included (always: false), autostart is false, and automaton entrypoint is declared (normal for an executable skill). It does not request modification of other skills or global agent settings. Agent-autonomous invocation is allowed (platform default) — expected behavior for skills that can run trading automations.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install kalshi-eth-staking-yield-trader
  3. After installation, invoke the skill by name or use /kalshi-eth-staking-yield-trader
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.3
Rescan attempt
v1.0.2
Rescan attempt
v1.0.1
No user-facing changes in this release; version updated only.
v1.0.0
Kalshi ETH Staking Yield Trader v1.0.0 - Initial release of a trading skill for Kalshi ETH price markets utilizing a 4% staking yield as a fundamental price floor. - Computes a time-adjusted yield-based floor for ETH price and trades when market prices imply ETH below this floor. - Includes risk parameters for entry/exit edges, max position size, trade frequency, and slippage limits. - Defaults to dry-run mode; real trades require explicit --live flag. - Easy setup via clawhub; requires SIMMER_API_KEY (and SOLANA_PRIVATE_KEY for live trades).
Metadata
Slug kalshi-eth-staking-yield-trader
Version 1.0.3
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 4
Frequently Asked Questions

What is Kalshi Eth Staking Yield Trader?

Trades ETH price markets on Kalshi using the 4% staking yield as a fundamental price floor. When markets underprice ETH relative to the yield-implied floor,... It is an AI Agent Skill for Claude Code / OpenClaw, with 126 downloads so far.

How do I install Kalshi Eth Staking Yield Trader?

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

Is Kalshi Eth Staking Yield Trader free?

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

Which platforms does Kalshi Eth Staking Yield Trader support?

Kalshi Eth Staking Yield Trader is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Kalshi Eth Staking Yield Trader?

It is built and maintained by diagnostikon (@diagnostikon); the current version is v1.0.3.

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