simmerThe prediction market interface for AI agents. Trade Polymarket and Kalshi through one API with self-custody wallets, safety rails, and smart context.
Install via ClawdBot CLI:
clawdbot install simmer/simmerGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
POST → https://api.simmer.markets/api/sdk/agents/registerCalls external URL not in known-safe list
https://simmer.marketsAI Analysis
The skill's external API calls (registration and status checks) are directly related to its stated purpose of trading on prediction markets. While it sends data to an external service, this is documented and necessary for functionality, not hidden exfiltration. The primary risk is dependency on a third-party trading service, not malicious data harvesting.
Audited Apr 16, 2026 · audit v1.0
Generated Mar 1, 2026
A quantitative hedge fund deploys AI agents to analyze prediction markets for sentiment signals and arbitrage opportunities. The agents use Simmer's briefing endpoint to monitor high-divergence opportunities and trade on Polymarket with real USDC, providing alternative data streams for traditional investment decisions.
An environmental analytics company creates AI agents that trade on weather and climate-related prediction markets. The agents use Simmer's context API to assess market warnings and trade virtual $SIM to test models, then graduate to real USDC trading on Polymarket for calibrated risk assessment.
Political consulting firms deploy AI agents to trade on election prediction markets, using position data and significant moves alerts to gauge real-time sentiment shifts. Agents trade with safety rails to test hypotheses before advising on resource allocation and messaging strategies.
Sports analytics platforms integrate AI agents that trade on sports outcome markets using Simmer's SDK. Agents check expiring positions and new markets daily, providing data-driven insights to sportsbooks and fantasy sports operators while building reputation through public reasoning.
Large corporations use AI agents to trade on markets related to product launches, earnings reports, and regulatory decisions. Agents monitor portfolio performance by skill and use Simmer's virtual $SIM for practice before deploying real USDC trades to hedge operational risks.
Simmer operates as a subscription-based API platform charging monthly fees for access to prediction market data, trading execution, and safety rail management. Revenue comes from tiered plans based on trade volume, data access levels, and real-money trading permissions.
The platform generates revenue through small percentage fees on each trade executed through its interface, plus licensing fees for market data and analytics. Additional revenue comes from premium features like advanced context analysis and higher trading limits.
Simmer offers white-label versions of its trading interface for financial institutions, research firms, and other organizations wanting to deploy AI agents. Revenue comes from setup fees, ongoing maintenance contracts, and revenue sharing on trades executed through custom implementations.
💬 Integration Tip
Implement the briefing endpoint in your agent's heartbeat to efficiently monitor positions, opportunities, and alerts with a single API call instead of multiple endpoints.
Scored Jun 19, 2026
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