Knowledge comic creator supporting multiple art styles and tones. Creates original educational comics with detailed panel layouts and sequential image generation. Use when user asks to create "知识漫画", "教育漫画", "biography comic", "tutorial comic", or "Logicomix-style comic".
60
73%
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 ./skills/baoyu-comic/SKILL.mdQuality
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 defines a specific niche (educational comic creation), lists concrete capabilities (panel layouts, sequential image generation, multiple art styles), and provides explicit trigger terms in both Chinese and English. The 'Use when' clause with specific quoted phrases makes it easy for Claude to match user requests to this skill.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'supporting multiple art styles and tones', 'creates original educational comics', 'detailed panel layouts', and 'sequential image generation'. These are concrete, specific capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (creates educational comics with detailed panel layouts and sequential image generation, supporting multiple art styles) and 'when' (explicit 'Use when' clause with specific trigger phrases). | 3 / 3 |
Trigger Term Quality | Includes excellent natural trigger terms in multiple languages: '知识漫画', '教育漫画', 'biography comic', 'tutorial comic', 'Logicomix-style comic'. These cover both Chinese and English user queries and represent terms users would naturally say. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche combining educational content with comic creation. The specific trigger terms like '知识漫画', 'Logicomix-style comic', and 'tutorial comic' are unlikely to conflict with generic image generation or general education skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
47%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a comprehensive and well-structured skill with excellent workflow clarity including blocking gates, recovery patterns, and validation checkpoints. However, it suffers significantly from verbosity — the main SKILL.md tries to be both an overview and a detailed reference, embedding complex conditional logic (image backend resolution, reference image handling) that should be offloaded to reference files. The actionability is moderate since most concrete implementation is deferred to unreviewable reference files.
Suggestions
Move the Image Generation Tools backend resolution logic (steps 1-4, ~40 lines) to a reference file like `references/image-backend-resolution.md` and replace with a 3-line summary in the main skill.
Move the Reference Images section (~40 lines of intake/usage/generation-time details) to a reference file and keep only a brief mention with link in the main skill.
Consolidate the three representations of the workflow (checklist, flow diagram, step summary table) into one — the step summary table is the most actionable; the others are redundant.
Add at least one complete executable example showing a typical invocation end-to-end (e.g., a sample prompt file content, a sample backend invocation) rather than only describing the pattern abstractly.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~350+ lines with significant redundancy. The Image Generation Tools section alone is a wall of conditional logic that could be a referenced file. Multiple sections repeat information (e.g., character sheet generation is described in the workflow summary, step 7 details, and notes). The Reference Images section, option tables, and backend resolution rules add substantial token cost that could be offloaded to reference files. | 1 / 3 |
Actionability | The skill provides concrete file paths, naming conventions, and structured workflows with specific commands (e.g., sips compression, script paths). However, most critical implementation details are deferred to reference files (workflow.md, first-time-setup.md, etc.) which aren't provided, and there are no complete executable code examples — just references to scripts and conceptual steps. | 2 / 3 |
Workflow Clarity | The workflow is exceptionally well-structured with a progress checklist, flow diagram, step summary table, blocking gates (⛔), conditional steps, and explicit validation/recovery patterns (e.g., --ref failure recovery: compress → retry → fallback). The backup rule for existing files and the prompt-file-first requirement provide clear validation checkpoints. | 3 / 3 |
Progressive Disclosure | The skill has a well-organized References section with clear one-level-deep links to art styles, tones, presets, config, and workflow files. However, the main SKILL.md itself is overloaded — the Image Generation Tools resolution logic, Reference Images section, and detailed Step 7 breakdown should be in referenced files rather than inline, undermining the progressive disclosure pattern. Without bundle files to verify, the extensive reference structure cannot be validated. | 2 / 3 |
Total | 8 / 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 | |
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Table of Contents
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