biomed-outline-generator
Generates structured biomedical outlines for review articles, discussion sections, and thesis proposals. Use when a user provides biomedical keywords, results/discussion text, or a proposal title plus background and needs a directly usable academic writing scaffold.
67
81%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong description that clearly defines a specific niche (biomedical academic outline generation), lists concrete output types, and provides explicit trigger conditions including the types of inputs a user would provide. It uses proper third-person voice and is concise without being vague.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'structured biomedical outlines for review articles, discussion sections, and thesis proposals.' These are distinct, well-defined output types rather than vague language. | 3 / 3 |
Completeness | Clearly answers both what ('Generates structured biomedical outlines for review articles, discussion sections, and thesis proposals') and when ('Use when a user provides biomedical keywords, results/discussion text, or a proposal title plus background and needs a directly usable academic writing scaffold'). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'biomedical keywords', 'review articles', 'discussion sections', 'thesis proposals', 'proposal title', 'background', 'academic writing scaffold'. These cover the domain well and match how researchers would describe their needs. | 3 / 3 |
Distinctiveness Conflict Risk | Highly specific niche combining biomedical domain + outline generation + specific academic document types. Unlikely to conflict with general writing skills or non-biomedical academic skills due to the precise scope and input/output descriptions. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
62%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a well-structured workflow with clear type classification logic and deterministic output contracts for three biomedical outline types. Its main weaknesses are the lack of a concrete full output example (reducing actionability) and moderate verbosity with some redundancy between sections. The workflow clarity is strong with validation checkpoints and a clear refusal contract.
Suggestions
Add at least one complete example output showing a full outline for one of the three types, so Claude has a concrete template to follow rather than just section lists.
Consolidate the 'When to Use' and 'Type Recognition Rules' sections to eliminate redundancy—the type signals are stated twice in slightly different forms.
Either provide the referenced `scripts/validate_skill.py` as a bundle file or remove the 'Optional Validation Shortcut' section, since it references a non-existent asset.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably structured but includes some unnecessary verbosity. Sections like 'When Not to Use' and 'Required Inputs' contain information Claude could infer. The type recognition rules partially duplicate the 'When to Use' section. The overall length (~180 lines) could be tightened without losing clarity. | 2 / 3 |
Actionability | The skill provides clear type classification rules and output contracts with specific required sections, which is good. However, it lacks a concrete example of a complete output for any of the three types. The guidance is instructional rather than demonstrative—showing one full example outline would make it much more actionable and copy-paste ready. | 2 / 3 |
Workflow Clarity | The 5-step workflow is clearly sequenced with explicit validation at step 1 (domain/sufficiency check) and step 5 (safety/writing pass). The fallback/refusal contract provides a clear error recovery path. The completion checklist at the end serves as a final verification checkpoint. This is well-structured for a non-destructive generation task. | 3 / 3 |
Progressive Disclosure | The content is organized with clear headings and logical sections, but it's monolithic—everything is in one file with no references to supporting documents. The output contracts, type recognition rules, and examples could be split into separate files for better navigation. The optional validation script reference (`scripts/validate_skill.py`) has no bundle file to back it up. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- aipoch/medical-research-skills
- Commit
73f6514
- Reviewed
Table of Contents
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