openai-image-gen
Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.
63
57%
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/openai-image-gen/SKILL.mdQuality
Discovery
50%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description is concise and identifies a clear, distinctive niche (batch image generation via OpenAI API with gallery output). However, it completely lacks a 'Use when...' clause, which is critical for Claude to know when to select this skill. The trigger terms are somewhat technical and miss common user phrasings like 'DALL-E' or 'create images'.
Suggestions
Add a 'Use when...' clause such as 'Use when the user wants to generate multiple images in bulk, create an image gallery, or use the OpenAI/DALL-E API for batch image creation.'
Include more natural trigger terms users would say, such as 'DALL-E', 'generate images', 'create images', 'image gallery', 'bulk image generation', or 'AI-generated images'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple concrete actions: batch-generate images, random prompt sampling, and generating an index.html gallery. These are specific, actionable capabilities. | 3 / 3 |
Completeness | Describes what it does (batch-generate images, prompt sampling, gallery creation) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric, missing 'Use when' caps completeness at 2, and the 'when' is entirely absent, warranting a 1. | 1 / 3 |
Trigger Term Quality | Includes some relevant keywords like 'images', 'OpenAI Images API', 'gallery', and 'batch-generate', but misses common user terms like 'DALL-E', 'image generation', 'create images', or 'bulk images'. Users may not naturally say 'batch-generate' or 'prompt sampler'. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of OpenAI Images API, batch generation, random prompt sampling, and HTML gallery output creates a very distinct niche that is unlikely to conflict with other skills. | 3 / 3 |
Total | 9 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides good actionable examples with concrete commands covering multiple models and parameter combinations. However, it's somewhat verbose with inline reference documentation for model-specific parameters that could be split out or condensed. The workflow is straightforward but lacks error handling guidance for API failures or validation of outputs.
Suggestions
Move the detailed model-specific parameters (sizes, quality, style) to a separate REFERENCE.md and keep only a brief summary or table in the main skill file.
Add basic error handling guidance: what to check if generation fails (API key, rate limits, invalid parameter combinations).
Condense the parameter tables into a compact markdown table format rather than nested bullet lists to save tokens.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The model-specific parameters section is quite detailed and reference-like, which could be more concisely presented as a table or moved to a separate reference file. Some information like the full size/quality matrices feels like documentation Claude could look up from the script itself. | 2 / 3 |
Actionability | Provides fully executable commands with concrete flags and examples. The usage examples cover multiple models with specific parameter combinations and are copy-paste ready. | 3 / 3 |
Workflow Clarity | The workflow is essentially a single command invocation which is clear, but there's no validation or error handling guidance. The timeout warning is helpful, but there's no mention of what to do if generation fails, API key issues, or how to verify output quality. | 2 / 3 |
Progressive Disclosure | All content is inline in a single file. The model-specific parameters section (sizes, quality, other differences) is extensive reference material that would be better placed in a separate REFERENCE.md or within the script's --help output, with the SKILL.md providing a concise overview. | 2 / 3 |
Total | 9 / 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
- qsimeon/openclaw-engaging
- Commit
4467e04
- Reviewed
Table of Contents
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