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 suffers from excessive generic boilerplate that drowns out the actual domain-specific content about medical abstract refinement. The core value proposition—how to condense long medical texts into SCI-style bilingual abstracts—receives minimal concrete guidance, while generic sections about failure handling, safety rules, and completion checklists consume most of the token budget. The single concrete element (the CLI command) is merely a formatting script, not the actual intellectual work of abstract refinement.
Suggestions
Remove all generic boilerplate sections (Failure Handling, Deterministic Output Rules, Completion Checklist, generic Required Inputs, generic Recommended Workflow) and replace with a concrete, domain-specific workflow showing how to go from source medical text to refined abstracts.
Add a concrete before/after example: show a snippet of source medical text and the corresponding refined Chinese and English abstracts, demonstrating the expected style, length, and tone.
Provide a real Chinese abstract example instead of placeholder punctuation marks in the CLI example, and show what the generated Summary_Report.md actually looks like.
Consolidate the duplicated validation sections (Validation Shortcut at top, Quick Validation near bottom, Validation and Safety Rules) into a single concise section.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose and padded with generic boilerplate sections (Failure Handling, Validation and Safety Rules, Deterministic Output Rules, Completion Checklist) that are not specific to this skill and explain things Claude already knows. The 'When Not to Use', 'Required Inputs', and 'Recommended Workflow' sections are generic platitudes that could apply to any skill. The actual unique content (how to refine medical abstracts into bilingual SCI-style format) is buried under layers of unnecessary scaffolding. | 1 / 3 |
Actionability | There is one concrete command example (`python scripts/refine_abstract.py` with flags), but the core task—actually refining a long medical text into an abstract—has no concrete guidance. The skill assumes the agent has already produced the abstracts before running the script, but provides no examples of what a good abstract looks like, no input/output examples of the refinement process itself, and the Chinese abstract example is just punctuation marks. The script is a formatter, not the actual skill. | 2 / 3 |
Workflow Clarity | The 'Recommended Workflow' section lists 4 steps but they are entirely generic (validate, select path, produce output, validate again) with no specifics about the medical abstract refinement process. The actual multi-step process of reading source text → extracting key findings → drafting Chinese abstract → drafting English abstract → running the formatter script is never explicitly sequenced. The validation shortcut is a nice touch but the core workflow lacks specificity. | 2 / 3 |
Progressive Disclosure | The content is a monolithic wall of text with many sections that repeat similar ideas (Quick Validation appears twice, validation rules are scattered across multiple sections). There are no bundle files provided and no references to external documentation. The skill references `scripts/refine_abstract.py` but no bundle files exist to support it. The organization is poor—generic boilerplate sections dominate over the actual skill-specific content. | 1 / 3 |
Total | 6 / 12 Passed |