Kalshi Eth Gas Correlation Trader

Trades ETH price markets on Kalshi using on-chain gas prices as a bullish/bearish signal. High gas = strong demand = bullish for ETH. Requires SIMMER_API_KEY...

Security Scan

The skill generally matches a Kalshi trading use case but contains inconsistent metadata and requests a high-value Solana private key (unexpected for a Kalshi market trader), so review and caution are recommended before enabling live trades.

Purpose & Capability

The skill's stated purpose (trade Kalshi ETH markets using on-chain gas signals) aligns with the code (imports simmer_sdk, uses SimmerClient, market discovery, trade execution). However registry metadata at the top of the report claimed 'Required env vars: none' while SKILL.md and clawhub.json both require SIMMER_API_KEY and SOLANA_PRIVATE_KEY — this inconsistency is concerning. Requiring a Solana private key for Kalshi trading is unusual (Kalshi is a centralized prediction market); the SKILL.md claims live execution uses 'DFlow/Solana', which could explain the Solana key but the relationship should be clearly documented and audited before providing keys.

Instruction Scope

SKILL.md gives concrete trading instructions, defaults to dry-run, and requires live mode to execute real trades. Instructions and code focus on market discovery, gas regime classification and trading; they reference configuration via simmer_sdk.skill.load_config which may write local config. The skill also infers gas from market text if direct gas feeds are not integrated (a heuristic). No instructions in SKILL.md or visible code request unrelated system files or network exfiltration, but the skill does ask for and will use high-value credentials for live trading.

Install Mechanism

There is no custom install spec; the skill is instruction- and code-based and relies on the simmer-sdk Python package (declared in SKILL.md and clawhub.json). Installing a PyPI package is expected for this functionality. No arbitrary downloads, URL shorteners, or extract/install directives were present.

Credentials

The skill requires SIMMER_API_KEY (expected) and SOLANA_PRIVATE_KEY (high-value). A Solana private key grants on-chain signing authority and custody of funds — this is a disproportionate and sensitive permission unless you understand why it is needed (SKILL.md claims DFlow/Solana for live execution). Additional environment variables read by the code include AUTOMATON_MAX_BET, TRADING_VENUE and many SIMMER_ETH_* tunables (declared in clawhub.json). The mismatch between the registry's 'no required env vars' and the actual required credentials is a red flag.

Persistence & Privilege

always:false (good). The skill is automaton-managed with an entrypoint (trader.py), meaning it can be run by the platform's automaton system but not forced into every agent run. The code uses simmer_sdk.skill.load_config/update_config/get_config_path which may persist config to disk under the skill's config path — this is expected for a trading skill but you should review where config and any cached credentials are stored. Autonomous invocation is allowed by default (normal), so be cautious when enabling live mode.

Scan Findings in Context

[no_pre-scan-injection-signals] expected: The static pre-scan reported no injection signals. That does not imply safety — the code is present and should be reviewed manually (especially handling of private keys and network calls).

What to consider before installing

This skill appears to implement the described gas-based Kalshi trading strategy, but there are two things to be careful about: (1) the skill requires a SOLANA_PRIVATE_KEY — a high-value credential that allows signing on-chain transactions — even though Kalshi is a centralized market; only provide such a key if you understand and trust the 'DFlow/Solana' execution path and have audited simmer-sdk and trader.py. (2) The registry metadata is inconsistent about required env vars; treat that as a sign to inspect the code and simmer-sdk repository yourself. Recommendations: run the skill in dry-run only, review the full trader.py and simmer-sdk source, run in an isolated environment, do not put live private keys into shared agents/accounts, and prefer least-privilege keys or testnet keys until you fully audit the integration.

This is a template. The default signal uses gas price regimes as a directional indicator -- remix it with live Etherscan gas API, EIP-1559 base fee tracking, or L2 activity metrics. The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

High on-chain gas prices indicate strong demand for Ethereum block space (DeFi activity, NFT mints, token launches). This demand correlates positively with ETH price. This skill classifies gas into regimes and applies a directional bias to ETH price market probabilities.

Key advantages:

• Leading indicator -- gas spikes often precede price moves
• On-chain verifiable -- gas data is public and real-time
• Regime-based -- avoids noise by classifying into discrete regimes

Signal Logic

Gas Regime Model

1. Classify current gas price into regime (extreme/high/normal/low/dead)
2. Map regime to directional bias (+15% to -10%)
3. Apply bias to each ETH price market probability
4. Trade when |fair - market| >= entry_edge

Gas Regimes

Regime	Gas (gwei)	Bias	Interpretation
Extreme	>100	+15%	Very bullish
High	>50	+8%	Bullish
Normal	>20	0%	Neutral
Low	>10	-5%	Bearish
Dead	<10	-10%	Very bearish

Remix Ideas

• Live Etherscan API: Real-time gas price feed instead of estimates
• EIP-1559 base fee: More accurate demand metric post-merge
• L2 activity: Track Arbitrum/Optimism activity for full picture
• DeFi TVL overlay: Combine gas with total value locked trends

Risk Parameters

Parameter	Default	Notes
Entry edge	10%	Min model-vs-market divergence to trade
Exit threshold	45%	Sell when position price reaches this
Max position size	$5.00 USDC	Per market
Max trades per run	3	Rate limiting
Gas high threshold	50 gwei	Above this = high demand regime
Gas low threshold	10 gwei	Below this = dead regime

Installation & Setup

clawhub install kalshi-eth-gas-correlation-trader

Requires: SIMMER_API_KEY and SOLANA_PRIVATE_KEY environment variables.

Cron Schedule

Cron is set to null -- the skill does not run on a schedule until you configure it in the Simmer UI.

Safety & Execution Mode

The skill defaults to dry-run mode. Real trades only execute when --live is passed explicitly.

Scenario	Mode	Financial risk
python trader.py	Dry run	None
Cron / automaton	Dry run	None
python trader.py --live	Live (Kalshi via DFlow)	Real USDC

Required Credentials

Variable	Required	Notes
SIMMER_API_KEY	Yes	Trading authority. Treat as a high-value credential.
SOLANA_PRIVATE_KEY	Yes	Base58-encoded Solana private key for live trading.

Tunables (Risk Parameters)

Variable	Default	Purpose
SIMMER_ETH_GAS_ENTRY_EDGE	0.10	Min divergence to trigger trade
SIMMER_ETH_GAS_EXIT_THRESHOLD	0.45	Sell position when price reaches this level
SIMMER_ETH_GAS_MAX_POSITION_USD	5.00	Max USDC per trade
SIMMER_ETH_GAS_MAX_TRADES_PER_RUN	3	Max trades per execution cycle
SIMMER_ETH_GAS_SLIPPAGE_MAX	0.15	Max slippage before skipping (15%)
SIMMER_ETH_GAS_MIN_LIQUIDITY	0	Min market liquidity USD (0 = disabled)
SIMMER_ETH_GAS_HIGH_GWEI	50	Gas threshold for high-demand regime
SIMMER_ETH_GAS_LOW_GWEI	10	Gas threshold for dead regime

Dependency

simmer-sdk is published on PyPI by Simmer Markets.

• PyPI: https://pypi.org/project/simmer-sdk/
• GitHub: https://github.com/SpartanLabsXyz/simmer-sdk
• Publisher: [e-mail]

Review the source before providing live credentials if you require full auditability.