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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.

70

Quality

86%

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SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

87%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is concise, well-organized, and actionable with concrete research steps and an explicit output contract. Its one gap is the absence of an explicit validation/verification checkpoint in the workflow.

Suggestions

Add an explicit verification step in the research workflow, e.g. 'Before recommending, confirm each probability has a timestamp, source link, and assessed liquidity/spread; re-check any flagged market.'

Provide a concrete rendered output template (not just a 6-item list) so the Output Contract is copy-paste ready and the recommendation is unambiguous.

DimensionReasoningScore

Conciseness

The body is lean with no padding and no explanation of concepts Claude already knows — guardrails are terse bullets and workflow steps are crisp, so every token earns its place per the lean-and-efficient anchor.

3 / 3

Actionability

Concrete, specific guidance is given throughout: a 6-step numbered workflow with named signal-quality factors (liquidity, spread, market age, resolution authority) and an explicit Output Contract; per the code-vs-instruction note, the absence of code is not penalized because the guidance is actionable.

3 / 3

Workflow Clarity

The 6-step research workflow is clearly sequenced and ends in a usable/weak/unsuitable recommendation, but it lacks an explicit validation/verification gate or feedback loop of the kind the anchor-3 example shows ('Validate... If errors: fix and re-validate... Only when valid').

2 / 3

Progressive Disclosure

The skill is a single self-contained file with well-organized sections (Guardrails, Research Workflow, Integration Patterns, Output Contract), no nested references and no need for external bundle files, matching the anchor for clear, well-organized one-level structure.

3 / 3

Total

11

/

12

Passed

Description

85%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, complete, and distinctive, with explicit what-and-when framing and concrete actions. Its main weakness is a slightly jargon-leaning trigger vocabulary that could include more common-user phrasing.

Suggestions

Broaden trigger terms toward everyday phrasing (e.g., add 'betting odds', 'forecast markets', 'crowd forecasts') alongside the technical 'oracle signals' and 'decision intelligence'.

Consider an explicit 'Use when the user mentions prediction markets, forecasting, or market-implied odds' clause to strengthen natural trigger coverage.

DimensionReasoningScore

Specificity

Names the domain and multiple concrete actions — 'Research prediction markets as data sources or oracle signals for products, agents, dashboards, and corporate decision intelligence' and 'source-grounded analysis of market-implied probabilities, caveats, and integration patterns' — matching the anchor that lists multiple specific concrete actions.

3 / 3

Completeness

It answers both what ('Research prediction markets as data sources or oracle signals...') and when via an explicit 'Use for source-grounded analysis of market-implied probabilities, caveats, and integration patterns' trigger clause, matching the anchor for clearly answering both what AND when.

3 / 3

Trigger Term Quality

It includes relevant domain terms ('prediction markets', 'market-implied probabilities', 'oracle signals'), but leans toward internal jargon ('oracle signals', 'decision intelligence') and misses broader natural-language variations a lay user might say, fitting the anchor for some relevant keywords missing common variations.

2 / 3

Distinctiveness Conflict Risk

It carves a clear niche (prediction markets as oracle/research signals) with distinct triggers and even references a sibling skill (`llm-trading-agent-security`) for write authority, signaling clear boundary awareness and low conflict risk.

3 / 3

Total

11

/

12

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
affaan-m/ECC
Reviewed

Table of Contents

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