Research evidence
- decision context
- market sources
- signal quality
affaan-m/ECC
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.
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See how to use itView GitHub source
npx skills add https://github.com/affaan-m/ECC --skill "skills/prediction-market-oracle-research"Automated source guideResearchStandard source
Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
Source-grounded research guide: 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.
npx skills add https://github.com/affaan-m/ECC --skill "skills/prediction-market-oracle-research"The pinned source supports a structured brief, but not an expanded tutorial. Only detected inputs, outputs, and sections are shown.
232 source words · 4 usable sections
Research method
Read prediction-market-oracle-research through these 4 source sections
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
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 kn…
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.
Guardrails
Do not treat market prices as objective truth.
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
Integration Patterns
Research assistant: source-grounded context for a human analyst.
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.
Output Contract
1. decision context 2. market sources 3. signal quality 4. comparison sources 5. integration recommendation 6. caveats
decision contextmarket sourcessignal quality
Research checklist
Verify each item before delivery
The source section “Research Workflow” has been checked.
The source section “Guardrails” has been checked.
The source section “Integration Patterns” has been checked.
The source section “Output Contract” has been checked.
Source output checked: decision context
Source output checked: market sources
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Open source detailFAQ
What does the prediction-market-oracle-research source document cover?
Use this skill when prediction markets are being considered as a data source, forecasting input, oracle-like signal, or decision-intelligence layer.
How do I install prediction-market-oracle-research?
The source record exposes this install command: npx skills add https://github.com/affaan-m/ECC --skill "skills/prediction-market-oracle-research". Inspect the command and pinned source before running it.
Repository stars
234,327
Repository forks
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Quality
70/100
Source repository last pushed
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Documentation22/30
Specificity11/25
Maintenance20/20
Trust signals17/25
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View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 2 min
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-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.
- Source repo
- affaan-m/ECC
- Skill path
- skills/prediction-market-oracle-research/SKILL.md
- Commit SHA
- 4e973d3eaf92
- Repository license
- MIT
- Data collected