image-generation
Implement AI image generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to create images from text descriptions, generate visual content, create artwork, design assets, or build applications with AI-powered image creation. Supports multiple image sizes and returns base64 encoded images. Also includes CLI tool for quick image generation.
69
62%
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 ./skills/image-generation/SKILL.mdQuality
Discovery
82%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 reasonably well-constructed description with a clear 'Use this skill when...' clause and good trigger term coverage for image generation scenarios. Its main weaknesses are that the specific capabilities listed are somewhat redundant (multiple ways of saying 'generate images') rather than enumerating distinct features, and the broad design/artwork terms could cause overlap with other visual design skills. The SDK name helps with distinctiveness but the core actions could be more differentiated.
Suggestions
Differentiate the listed capabilities more clearly—instead of repeating variations of 'generate images', specify distinct features like 'configure image dimensions, retrieve base64-encoded output, batch generate via CLI'.
Add more specific trigger terms tied to the SDK name (e.g., 'z-ai-web-dev-sdk', 'z-ai image') to reduce conflict risk with other image generation skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (AI image generation) and some actions (create images from text descriptions, generate visual content), but the actions listed are somewhat redundant and don't enumerate truly distinct concrete capabilities beyond 'generate images'. The mention of multiple image sizes and base64 encoding adds some specificity, as does the CLI tool. | 2 / 3 |
Completeness | Clearly answers both 'what' (implement AI image generation using z-ai-web-dev-sdk, supports multiple sizes, returns base64, includes CLI tool) and 'when' (explicit 'Use this skill when...' clause listing specific trigger scenarios). | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms users would say: 'image generation', 'text descriptions', 'visual content', 'artwork', 'design assets', 'AI-powered image creation'. These cover a good range of how users might phrase requests for image generation. | 3 / 3 |
Distinctiveness Conflict Risk | The mention of the specific SDK (z-ai-web-dev-sdk) helps distinguish it, but terms like 'generate visual content', 'design assets', and 'artwork' are broad enough to potentially overlap with other image/design-related skills. The SDK name provides some niche anchoring but the general image generation framing could conflict with other image tools. | 2 / 3 |
Total | 10 / 12 Passed |
Implementation
42%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides highly actionable, executable code examples covering the SDK and CLI tool comprehensively, which is its main strength. However, it is severely bloated with duplicated information (supported sizes listed 3 times, basic patterns repeated), unnecessary explanations Claude doesn't need (prompt engineering basics, what use cases exist), and should split advanced examples into separate files. The content could deliver the same value at roughly one-third the length.
Suggestions
Reduce to a concise SKILL.md with basic SDK usage, CLI usage, and supported sizes listed once, then move the ImageGenerationService, Express.js endpoint, batch generation, and prompt engineering tips into separate referenced files (e.g., ADVANCED.md, INTEGRATION.md).
Remove the 'Common Use Cases' bullet list, 'Prompt Engineering Tips' section, and 'Remember' section entirely — Claude already knows how to write descriptive prompts and doesn't need reminders about basic concepts.
Consolidate the supported sizes into a single reference table instead of repeating them in the code example, the troubleshooting section, and the dedicated sizes section.
Add explicit validation steps to the batch generation workflow (e.g., verify output file exists and has reasonable size after each generation) to ensure correctness of batch operations.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with massive code duplication (supported sizes listed 3 times, basic generation pattern repeated in nearly every example). The 'Common Use Cases' bullet list, 'Prompt Engineering Tips', and 'Remember' section all explain things Claude already knows. The ImageGenerationService class with caching is over-engineered for a skill file. Content could be cut by 60%+ without losing actionable information. | 1 / 3 |
Actionability | All code examples are fully executable with proper imports, complete function bodies, and realistic usage examples. Both the SDK API and CLI tool are demonstrated with copy-paste ready code including error handling, batch processing, and Express.js integration. | 3 / 3 |
Workflow Clarity | Individual code examples are clear, but the batch generation section lacks explicit validation checkpoints (e.g., verifying generated images are valid PNGs, checking file sizes are reasonable). The overall document doesn't provide a clear sequential workflow for when to use SDK vs CLI, and the batch operation has error handling but no verification step for the outputs. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of text with everything inline. The ImageGenerationService class, Express.js integration, shell scripts, and prompt engineering tips should all be in separate referenced files. The document is extremely long with no references to external files for advanced content, despite mentioning a scripts directory. Information is repeated across sections rather than organized hierarchically. | 1 / 3 |
Total | 7 / 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 |
|---|---|---|
skill_md_line_count | SKILL.md is long (584 lines); consider splitting into references/ and linking | Warning |
Total | 10 / 11 Passed | |
- Repository
- jjyaoao/HelloAgents
- Commit
07048a9
- Reviewed
Table of Contents
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