prediction-market-oracle-research
Research prediction markets as data sources or oracle signals for products, agents, dashboards, and corporate decision intelligence. Use for source-grounded analysis of market-implied probabilities, caveats, and integration patterns without investment advice. Use when evaluating prediction markets as a data source or oracle signal for a product, agent, or dashboard.
Works with
--- name: prediction-market-oracle-research description: Research prediction markets as data sources or oracle signals for products, agents, dashboards, and corporate decision intelligence. Use for source-grounded analysis of market-implied probabilities, caveats, and integration patterns without investment advice. Use when evaluating prediction markets as a data source or oracle signal for a product, agent, or dashboard. license: MIT --- # Prediction Market Oracle Research Use this skill when prediction markets are being considered as a data source, forecasting input, oracle-like signal, or decision-intelligence layer. ## Guardrails - Do not treat market prices as objective truth. - Do not provide investment advice or trading recommendations. - Separate venue mechanics, liquidity, incentives, and resolution rules from the implied signal. - Call out manipulation, thin liquidity, stale markets, and ambiguous outcomes. - For on-chain or execution-linked systems, run `llm-trading-agent-security` before granting any write authority. ## Research Workflow 1. Define the decision the signal is meant to inform. 2. Find relevant markets, events, tags, and venues. 3. Record market-implied probabilities with timestamps and source links. 4. Evaluate signal quality: - liquidity - spread - market age - trader/incentive concentration if known - resolution authority - geography or account restrictions 5. Compare against non-market sources such as filings, news, polls, research, customer data, or internal KPIs. 6. Recommend whether the signal is usable, weak, or unsuitable for the stated decision. ## Integration Patterns - Research assistant: source-grounded context for a human analyst. - Dashboard signal: market-implied probability alongside internal metrics. - Agent memory input: a time-stamped signal that can be retrieved later. - Alerting input: notify when probabilities, spreads, or liquidity cross a threshold. - Scenario planning: compare multiple event outcomes without automating trades. ## Output Contract Use: 1. decision context 2. market sources 3. signal quality 4. comparison sources 5. integration recommendation 6. caveats End with: ```text Prediction-market signals are informational inputs, not investment advice. ```
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