baoyu-cover-image
Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover".
72
92%
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 skill description that clearly communicates its specific purpose (article cover image generation), enumerates its capabilities with concrete details (5 dimensions, 11 palettes, 7 styles, 3 aspect ratios), and provides explicit trigger phrases. The description is concise, uses third person voice, and would be easily distinguishable from other skills in a large skill library.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and parameters: 5 dimensions (type, palette, rendering, text, mood), 11 color palettes, 7 rendering styles, and three specific aspect ratios with their exact values. | 3 / 3 |
Completeness | Clearly answers both 'what' (generates article cover images with specific dimensions, palettes, rendering styles, and aspect ratios) and 'when' (explicit 'Use when' clause with quoted trigger phrases). | 3 / 3 |
Trigger Term Quality | Includes natural trigger terms users would say: 'generate cover image', 'create article cover', 'make cover'. Also includes domain-specific terms like 'article cover images', 'cinematic', 'widescreen', and aspect ratio values that users might reference. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche: article cover image generation with specific dimensional parameters. The combination of 'cover image' + 'article' + specific palettes/rendering styles makes it very unlikely to conflict with general image generation or other creative skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-crafted, comprehensive skill with excellent workflow clarity and progressive disclosure. The multi-step process is clearly sequenced with blocking gates, validation checkpoints, and conditional flows. The main weakness is moderate verbosity—the Image Generation Tools resolution logic, User Input Tools section, and Confirmation Policy could be more concise, as some of this meta-instruction about tool selection feels over-specified for Claude's capabilities.
Suggestions
Tighten the 'Image Generation Tools' section—the 4-level priority resolution with sub-bullets is verbose; consider condensing to a simple priority list with one line per option.
The 'User Input Tools' section explains generic tool-selection behavior that Claude can infer; consider reducing to 1-2 sentences or removing entirely.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly well-organized but includes some verbose sections that could be tightened—particularly the Image Generation Tools resolution logic, the User Input Tools section, and the Confirmation Policy, which are quite lengthy and repeat concepts. The options tables and dimension tables are efficient, but the overall document is heavy for what it does. | 2 / 3 |
Actionability | The skill provides highly concrete, actionable guidance: specific CLI flags, exact file paths and naming conventions, a clear step-by-step workflow with numbered steps, explicit file structure templates, and a completion report format. The workflow steps are precise enough to execute without ambiguity. | 3 / 3 |
Workflow Clarity | The workflow is exceptionally well-structured with a progress checklist, a visual flow diagram, blocking/warning annotations on steps, explicit validation checkpoints (e.g., verify ref files exist before writing, backup before regenerating), and clear conditional logic for skipping confirmation. Feedback loops are present (auto-retry on failure, fix-and-revalidate for references). | 3 / 3 |
Progressive Disclosure | The skill excels at progressive disclosure with a clear overview in the main file and well-signaled, one-level-deep references to detailed materials organized by category (dimensions, palettes, renderings, workflow, config). The References section at the bottom provides a comprehensive navigation index. Content is appropriately split between the main skill and reference files. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
72%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 8 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
metadata_field | 'metadata' should map string keys to string values | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 8 / 11 Passed | |
- Repository
- jimliu/baoyu-skills
- Commit
bd5745f
- Reviewed
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