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.
Install
$ agentstack add skill-affaan-m-ecc-prediction-market-oracle-research ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-affaan-m-ecc-prediction-market-oracle-research) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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.Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: affaan-m
- Source: affaan-m/ECC
- License: MIT
- Homepage: https://ecc.tools
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.