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

Define the decision the signal is meant to inform.
Find relevant markets, events, tags, and venues.
Record market-implied probabilities with timestamps and source links.
Evaluate signal quality:
- liquidity
- spread
- market age
- trader/incentive concentration if known
- resolution authority
- geography or account restrictions
Compare against non-market sources such as filings, news, polls, research, customer data, or internal KPIs.
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:

decision context
market sources
signal quality
comparison sources
integration recommendation
caveats

End with:

Prediction-market signals are informational inputs, not investment advice.

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Overall Score

78/100

Grade

B

Good

Safety

88

Quality

72

Clarity

82

Completeness

65

Summary

A research skill for evaluating prediction markets as data sources and oracle signals for products, agents, and decision-making. The skill guides agents through market analysis, signal quality assessment, and integration recommendations while enforcing guardrails against treating market prices as objective truth or providing investment advice.

Detected Capabilities

web researchdata extractioncomparative analysismarket data retrieval

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

prediction market analysisoracle signal evaluationmarket-implied probabilityforecast decision intelligencemarket data source comparison

Use Cases

Inform product decisions (e.g., feature launch timing) using market-implied probabilities
Feed oracle-like signals into agent memory for time-series decision tracking
Create dashboard widgets that display market probabilities alongside internal KPIs
Set up alerting thresholds based on market liquidity or probability spreads
Scenario planning: compare outcomes across multiple prediction markets without automating trades
Validate corporate forecasts against external market consensus

Quality Notes

Comprehensive guardrails clearly separate legitimate analysis from investment advice
Research workflow is methodical and structured with 6 concrete steps
Integration patterns section provides diverse use cases with clear boundaries
Output contract is specific and repeatable, enabling consistent agent execution
Could benefit from concrete examples of 'thin liquidity' or 'manipulation' warning signs
No example market venues (e.g., Polymarket, Manifold) provided for agent reference
Missing guidance on how to handle conflicting signals across multiple markets
No structured template for recording market data (timestamps, spreads, source links) is provided

Model: claude-haiku-4-5-20251001Analyzed: Jul 14, 2026

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Version History

v1.1
Content updated
✦ AINo behavioral changes detected.
2026-07-14
Latest
v1.0
2026-05-25
View This VersionInitial version

prediction-market-oracle-research