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.
Scanned 9/3/2026
Install to Claude Code
npx -y skills add userInner/SKILLS --skill prediction-market-oracle-research--affaan-m-ecc --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Prediction Market Oracle Research Affaan M Ecc?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/userinner-prediction-market-oracle-research-affaan-m-ecc)More formats (shields.io, HTML) on the badges page.
---
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.
metadata:
origin: ECC
---
# 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.
```
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!