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The official Agent Skills spec (agentskills.io/specification) whitelists exactly 6 top-level frontmatter keys (name/description/license/compatibility/metadata/ allowed-tools). A top-level `origin` key fails the official validator (anthropics/skills quick_validate.py ALLOWED_PROPERTIES; skills-ref validate). This moves `origin: X` -> `metadata.origin: X` across the canonical skills/ tree, preserving each value verbatim. Frontmatter-only, minimal diff. - 251 SKILL.md updated (242 new metadata block, 9 appended to existing metadata) - origin values preserved verbatim (verified 251/251) - YAML validated on all changed files - scoped to canonical skills/ only (docs/<lang> translations + tool mirrors .cursor/.kiro/.agents left untouched; presumably regenerated from canonical) Addresses #2233
65 lines
2.1 KiB
Markdown
65 lines
2.1 KiB
Markdown
---
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name: prediction-market-oracle-research
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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.
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metadata:
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origin: ECC
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---
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# Prediction Market Oracle Research
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Use this skill when prediction markets are being considered as a data source,
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forecasting input, oracle-like signal, or decision-intelligence layer.
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## Guardrails
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- Do not treat market prices as objective truth.
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- Do not provide investment advice or trading recommendations.
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- Separate venue mechanics, liquidity, incentives, and resolution rules from the
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implied signal.
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- Call out manipulation, thin liquidity, stale markets, and ambiguous outcomes.
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- For on-chain or execution-linked systems, run `llm-trading-agent-security`
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before granting any write authority.
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## Research Workflow
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1. Define the decision the signal is meant to inform.
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2. Find relevant markets, events, tags, and venues.
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3. Record market-implied probabilities with timestamps and source links.
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4. Evaluate signal quality:
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- liquidity
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- spread
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- market age
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- trader/incentive concentration if known
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- resolution authority
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- geography or account restrictions
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5. Compare against non-market sources such as filings, news, polls, research,
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customer data, or internal KPIs.
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6. Recommend whether the signal is usable, weak, or unsuitable for the stated
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decision.
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## Integration Patterns
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- Research assistant: source-grounded context for a human analyst.
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- Dashboard signal: market-implied probability alongside internal metrics.
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- Agent memory input: a time-stamped signal that can be retrieved later.
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- Alerting input: notify when probabilities, spreads, or liquidity cross a
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threshold.
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- Scenario planning: compare multiple event outcomes without automating trades.
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## Output Contract
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Use:
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1. decision context
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2. market sources
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3. signal quality
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4. comparison sources
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5. integration recommendation
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6. caveats
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End with:
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```text
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Prediction-market signals are informational inputs, not investment advice.
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```
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