Prediction Market Oracle Research
SkillAI & modelsPrediction Market Oracle Research is a skill that guides an agent through researching prediction markets as forecasting data sources. It covers finding relevant markets, recording market-implied probabilities with sources, judging signal quality, and comparing those signals against other inputs before recommending whether they suit a given decision.
Available today. Use it from your connected AI after setup.
No other account needed.
Have an agent environment that can load skills.
Then ask your AI: use the Prediction Market Oracle Research skill
What your AI can do with it
- Finds relevant prediction markets, events, tags, and venues for a stated decision
- Records market-implied probabilities with timestamps and source links
- Evaluates signal quality via liquidity, spread, market age, incentives, and resolution rul
- Compares market signals against news, polls, filings, research, and internal KPIs
- Recommends whether a signal is usable, weak, or unsuitable for the decision at hand
- Suggests integration patterns such as dashboards, alerting, agent memory, and scenario pla
Getting started
- Have an agent environment that can load skills.
- Add the prediction-market-oracle-research skill to the agent's available skills.
- State the decision the market signal is meant to inform when invoking the agent.
- Review the output covering decision context, market sources, signal quality, comparison sources, integration recommendation, and caveats.
- For on-chain or execution-linked systems, run the llm-trading-agent-security skill before granting any write authority.
What this skill tells your AI
The instructions your AI receives, as published by affaan-m/ecc in skills/prediction-market-oracle-research/SKILL.md and read by ahel’s review.
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-securitybefore 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.
Signals
- GitHub stars
- 268k
- Forks
- 40k
- Last commit
- Sep 2026
Questions
- Does this skill give investment advice?
- No. It treats market prices as informational inputs, not objective truth, and its output ends with a disclaimer that prediction-market signals are not investment advice.
- What integration patterns does it cover?
- Research assistant for analysts, dashboard signals alongside internal metrics, agent memory inputs, alerting on probability or liquidity thresholds, and scenario planning without automated trades.
Advanced
- Item type
- skill
- Key
prediction-market-oracle-research- Source
- github.com/affaan-m/ecc