Agent skill · research science · affaan-m
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.
Why this skill is useful
Provides domain-specific knowledge on evaluating prediction markets and their integration patterns for decision intelligence.
What it needs
About 1k tokens when loaded. Last updated 2026-08-06. 238,342 stars on the source repository.
What this skill does
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:
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills affaan-m/prediction-market-oracle-research