journal-cover-prompter
Use when creating journal cover images, generating scientific artwork prompts, or designing graphical abstracts. Creates detailed prompts for AI image generators to produce publication-quality scientific visuals.
64
56%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/Academic Writing/journal-cover-prompter/SKILL.mdQuality
Discovery
89%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 well-structured description that clearly communicates both purpose and trigger conditions. It excels at distinctiveness and completeness with an explicit 'Use when...' clause. The main weakness is that the specificity of concrete actions could be slightly stronger—the skill essentially does one thing (generate prompts) applied to a few use cases, rather than listing multiple distinct capabilities.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (scientific visuals/publication imagery) and some actions (creating journal cover images, generating artwork prompts, designing graphical abstracts), but the core action is essentially one thing: creating prompts for AI image generators. The listed items are more use cases than distinct concrete actions. | 2 / 3 |
Completeness | Explicitly answers both 'what' (creates detailed prompts for AI image generators to produce publication-quality scientific visuals) and 'when' (Use when creating journal cover images, generating scientific artwork prompts, or designing graphical abstracts) with a clear 'Use when...' clause. | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms users would say: 'journal cover', 'scientific artwork', 'graphical abstracts', 'AI image generators', 'publication-quality'. These are terms a researcher or scientist would naturally use when requesting this kind of help. | 3 / 3 |
Distinctiveness Conflict Risk | Occupies a very clear niche at the intersection of scientific publishing and AI image generation. The specific triggers like 'journal cover', 'graphical abstracts', and 'publication-quality scientific visuals' are highly distinctive and unlikely to conflict with general image or writing skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
22%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 that adds no domain-specific value for journal cover image prompt generation. The actual useful content—API examples, style selection, journal-specific guidance—is buried under repetitive process management language. The skill would benefit enormously from stripping the generic scaffolding and focusing on concrete prompt templates, example outputs, and journal-specific visual guidelines.
Suggestions
Remove all generic boilerplate sections (Output Requirements, Response Template, Input Validation, Error Handling) that don't contain domain-specific knowledge about scientific image prompting.
Add concrete example prompts showing actual AI image generator output text for different journal styles and research topics, so Claude knows what good output looks like.
Resolve the inconsistency between scripts/main.py and scripts/cover_prompter.py references, and clarify which is the actual entry point.
Replace the abstract workflow steps with a domain-specific workflow: e.g., 1) Extract key visual concepts from research, 2) Select journal-appropriate style, 3) Compose prompt with specific structure, 4) Validate prompt covers required technical specs.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose and repetitive. The description is repeated verbatim in multiple sections ('When to Use', 'Key Features'). Generic boilerplate about error handling, input validation, output requirements, and response templates bloats the content massively. Much of this is generic project management language Claude already knows, not domain-specific knowledge about generating journal cover image prompts. | 1 / 3 |
Actionability | The Quick Start and Core Capabilities sections provide some concrete Python API examples and CLI usage, which is helpful. However, the code references modules (scripts/cover_prompter.py, CoverPrompter class) without showing what the actual prompt output looks like, and much of the 'workflow' is abstract process description rather than executable guidance for creating scientific image prompts. | 2 / 3 |
Workflow Clarity | The workflow section is entirely generic ('Confirm the user objective', 'Validate that the request matches the documented scope') with no specifics about the actual journal cover image prompting process. There are no validation checkpoints specific to prompt quality, no examples of good vs bad prompts, and no feedback loops for iterating on prompt output. The 'Example run plan' references scripts/main.py but the Quick Start references scripts/cover_prompter.py, creating confusion. | 1 / 3 |
Progressive Disclosure | There is some structure with sections and a reference to references/audit-reference.md. However, the content is largely monolithic with redundant sections (Workflow appears twice conceptually, multiple validation/error sections). The reference file mentioned is generic ('audit-reference.md') rather than domain-specific. Content that should be in separate files (style guides, journal specs) is partially inline but incomplete. | 2 / 3 |
Total | 6 / 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
0b96148
- Reviewed
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