Install
openclaw skills install kalshi-politics-random-buyerDry-run Kalshi skill that finds politics-related markets, picks a valid candidate at random, runs Simmer context checks, and proposes a trade plan without placing a real order.
openclaw skills install kalshi-politics-random-buyerThis skill scans Kalshi for politics-related markets, randomizes the candidate pool, checks Simmer context safeguards, and prints a manual-confirmation trade plan for one valid candidate.
This is a template. The default signal is intentionally simple: find a politics market at random, then only keep it if context and edge checks still pass. Remix the query set, side logic, price filters, and sizing model with your own thesis.
On each run, the skill:
simmer_sdk.sizing.size_position().This template is intentionally non-executing.
--live is rejected.SKILL.mdclawhub.jsontrade_skill.pySIMMER_API_KEY (required): Your Simmer API key.SEARCH_QUERIES: Comma-separated politics search terms. Default: election,president,presidency,senate,house,governor,politics,campaign,ballot,nominee,partyMAX_MARKETS_PER_QUERY: Maximum Kalshi results to inspect per query. Default: 50MIN_PRICE: Minimum YES price allowed. Default: 0.02MAX_PRICE: Maximum YES price allowed. Default: 0.98FAIR_PROBABILITY: Fair YES probability for edge checks. Default: 0.55MIN_EDGE: Minimum edge required to produce a plan. Default: 0.02MAX_SLIPPAGE_PCT: Skip candidates with excessive slippage. Default: 0.15RANDOM_SEED: Optional integer seed for reproducible selection.Default planning run:
export SIMMER_API_KEY="sk_live_..."
python trade_skill.py
Deterministic planning run:
export RANDOM_SEED="7"
python trade_skill.py
Custom politics search:
export SEARCH_QUERIES="president,election,governor"
export FAIR_PROBABILITY="0.60"
python trade_skill.py