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 pl...
Install via ClawdBot CLI:
clawdbot install skybinjf/kalshi-politics-random-buyerGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated May 20, 2026
A news organization uses the skill to quickly scan Kalshi for political markets tied to breaking headlines. The random selection and Simmer checks ensure they propose only valid trades while avoiding risky or illiquid markets, enabling rapid editorial decision-making.
Finance educators deploy the skill to demonstrate market scanning, edge calculation, and position sizing without real funds. Students learn to evaluate political event contracts and interpret Simmer context alerts in a safe environment.
A quantitative hedge fund integrates the dry-run skill as a pre-trade filter for political event exposure. The random candidate pool and Simmer checks produce manual-review plans that feed into their proprietary execution pipeline.
Political campaigns use the skill to monitor prediction market sentiment on election outcomes. The fair-probability edge rule helps them gauge market mispricing, while the manual confirmation ensures they only act on vetted signals.
A compliance team runs the skill to test new Simmer rules or strategy parameters against historical political markets. The dry-run output helps them refine risk thresholds before any real trading.
Offer subscribers daily or hourly dry-run trade plans for political markets. Users pay a monthly fee for access to curated candidate selections, Simmer context summaries, and sizing recommendations.
License the skill's logic (market scanning, edge filter, sizing) as an API for fintech apps that want to add prediction market analysis. Charge per API call or offer tiered packages.
Provide bespoke versions of the skill for institutional clients (e.g., custom query sets, position limits, or integration with their Simmer instance). Billed as project-based consulting with ongoing support retainers.
💬 Integration Tip
Start by setting SIMMER_API_KEY and the default environment variables, then run python trade_skill.py to generate demo plans. For production, customize SEARCH_QUERIES and FAIR_PROBABILITY to match your political thesis.
Scored May 20, 2026
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