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.
48
52%
Does it follow best practices?
Impact
—
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-crafted description that clearly defines its niche in scientific publication visuals and includes an explicit 'Use when' clause with natural trigger terms. The specificity of capabilities could be slightly improved by listing more concrete actions beyond prompt creation, but overall it effectively communicates both purpose and trigger conditions.
Suggestions
Consider listing additional specific actions beyond prompt creation, such as 'suggests composition layouts, recommends color palettes for scientific figures, adapts prompts for different AI generators' to strengthen specificity.
| 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 capability is somewhat narrow—it primarily 'creates detailed prompts' rather than listing multiple 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 keywords users would say: 'journal cover images', 'scientific artwork', 'graphical abstracts', 'AI image generators', 'publication-quality'. These are terms a researcher or scientist would naturally use when seeking this kind of help. | 3 / 3 |
Distinctiveness Conflict Risk | Occupies a very clear niche—scientific publication imagery and AI prompt generation for that domain. Unlikely to conflict with general image generation or general writing skills due to the specific scientific/academic focus and mention of journal covers and graphical abstracts. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
14%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 value for journal cover image prompt generation. While the Quick Start and Core Capabilities sections contain some useful domain-specific code examples (style selection, technical specs, prompt structure), they are buried in repetitive, template-driven content. The workflow is entirely generic and fails to describe the actual process of creating effective scientific image prompts.
Suggestions
Remove all generic boilerplate sections (Output Requirements, Response Template, Input Validation, Error Handling) and the duplicated description text—these add no domain-specific value and waste tokens.
Replace the generic 5-step Workflow with a concrete workflow specific to journal cover image creation: e.g., 1) Extract key visual concepts from the paper, 2) Select journal-appropriate style, 3) Compose prompt with required elements, 4) Validate prompt against technical specs, 5) Iterate based on feedback.
Consolidate the redundant entry points (scripts/main.py vs scripts/cover_prompter.py vs CoverPrompter class) into a single clear usage path with one executable example.
Add a concrete example showing a complete input-to-output flow: given a specific research topic, show the full generated prompt text that would be sent to an AI image generator.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose and repetitive. The description is copy-pasted into 'When to Use' and 'Key Features'. Generic boilerplate sections (Output Requirements, Response Template, Error Handling, Input Validation) dominate the file and contain no domain-specific value. Multiple redundant validation commands appear. Much of this content explains things Claude already knows. | 1 / 3 |
Actionability | The Quick Start and Core Capabilities sections provide concrete Python code examples with specific parameters (research_topic, visual_style, etc.) and CLI usage. However, it's unclear if these code examples are actually executable—they reference modules like 'scripts.cover_prompter' and 'CoverPrompter' class while also referencing 'scripts/main.py' as the entry point, creating confusion. The workflow steps are generic and not specific to journal cover image generation. | 2 / 3 |
Workflow Clarity | The 'Workflow' section is entirely generic boilerplate ('Confirm the user objective', 'Validate that the request matches documented scope') with no steps specific to generating journal cover image prompts. There's no clear sequence for how to go from a research paper to a finished image prompt, no validation of prompt quality, and no feedback loop for iterating on generated prompts. | 1 / 3 |
Progressive Disclosure | The file is a monolithic wall of text mixing generic boilerplate with domain-specific content. References point to 'references/audit-reference.md' but no bundle files are provided. Content is poorly organized with redundant sections (Example Usage vs Quick Start vs CLI Usage, Quick Check vs Audit-Ready Commands). The 'Implementation Details' section says 'See ## Workflow above' but Workflow appears below it. | 1 / 3 |
Total | 5 / 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
d3c2c0f
- Reviewed
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