Content
86%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-organized, token-efficient skill body that provides concrete research guidance and a defined output contract. It could push actionability to 5 with one or two executable examples of fetching/normalizing market-implied probabilities.
Suggestions
Add a brief executable snippet or named tool/API for retrieving and timestamping market-implied probabilities to lift actionability.
Make the signal-quality validation explicit as a checkpoint (e.g. 'halt and downgrade the signal if liquidity/spread fail thresholds') to strengthen the workflow's feedback loop.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient throughout; assumes Claude's competence, never explains what prediction markets are, and every section (Guardrails, Workflow, Integration Patterns, Output Contract) earns its place. | 5 / 5 |
Actionability | Concrete, specific guidance (a 6-step workflow with named signal-quality dimensions, defined integration patterns, and a fixed output contract), but as an instruction-only research skill it lacks copy-paste executable commands or data-fetch examples. | 4 / 5 |
Workflow Clarity | A clearly sequenced 6-step research workflow with implicit checkpoints via the Guardrails and a synthesis/recommendation step; no explicit validate→fix→retry loop, though the research context is non-destructive so that cap does not apply. | 4 / 5 |
Progressive Disclosure | A single-purpose skill organized into well-signaled sections with no need for external references and no bundle files; structure is clear and easy to navigate. | 5 / 5 |
Total | 18 / 20 Passed |