Content
27%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is heavily padded with generic boilerplate (risk assessment, security checklist, lifecycle status, evaluation criteria) that consumes significant token budget without adding value for the core task of predicting Q&A questions. The actual domain-specific content—question types, response frameworks, and preparation methodology—is minimal and underdeveloped. The circular section references and duplicated workflows further reduce clarity and usability.
Suggestions
Remove all generic boilerplate sections (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria, Response Template) that don't contribute to the Q&A preparation task, cutting the file by ~60%.
Expand the 'Question Types' section with concrete examples of each question type and example response frameworks, since this is the core value of the skill.
Eliminate circular references ('See ## Prerequisites above', 'See ## Usage above') and consolidate the duplicated workflow/run-plan into a single clear sequence.
Add a concrete example showing input (e.g., a sample abstract) and expected output (e.g., generated questions with structured responses) so Claude knows exactly what to produce.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose and repetitive. Multiple sections reference each other circularly ('See ## Prerequisites above', 'See ## Usage above', 'See ## Workflow above'). Contains extensive boilerplate (Risk Assessment table, Security Checklist, Lifecycle Status, Evaluation Criteria) that adds no actionable value for the skill's purpose. The core task—predicting Q&A questions—is buried under layers of generic project management scaffolding that Claude doesn't need. | 1 / 3 |
Actionability | The CLI parameters and usage examples are concrete and helpful (e.g., `python scripts/main.py --abstract abstract.txt --field oncology`). However, there's no actual guidance on *how* to predict challenging questions or structure responses—the core intellectual task. The skill relies entirely on an opaque `scripts/main.py` without explaining the methodology, question generation logic, or response framework structure. | 2 / 3 |
Workflow Clarity | There is a numbered workflow (steps 1-5) and an example run plan (steps 1-4), but they are generic and duplicative. The workflow lacks specific validation checkpoints tied to the actual Q&A preparation task. The error handling section mentions fallback paths but doesn't specify what those fallbacks actually look like for this particular skill. | 2 / 3 |
Progressive Disclosure | The document is a monolithic wall of text with 15+ sections, many of which are boilerplate. It references `references/audit-reference.md` but no bundle files are provided to verify. Circular internal references ('See ## Prerequisites above') create confusion rather than navigation. Content that could be separate (security checklist, risk assessment, evaluation criteria) is inlined, while the actual core content (question types, response frameworks) is underdeveloped. | 1 / 3 |
Total | 6 / 12 Passed |