openai-image-gen

Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.

Quality

63%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/openai-image-gen/SKILL.md

Quality

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, e.g., 'Use when the user wants to generate multiple images in batch, create an image gallery, or work with the OpenAI Images API.'

Include more natural trigger terms users would say, such as 'DALL-E', 'generate images', 'create pictures', 'AI image generation', or 'image gallery'.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions: batch-generate images, random prompt sampling, and creating 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 guidelines, 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 'generate pictures'. Users may not naturally say 'batch-generate' or 'prompt sampler'.	2 / 3
Distinctiveness Conflict Risk	Highly distinctive with a clear niche: batch image generation via OpenAI Images API with a specific gallery output format. Unlikely to conflict with other skills due to the specific combination of OpenAI API, batch generation, and HTML gallery.	3 / 3
	Total	9 / 12 Passed

Implementation

77%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a solid, actionable skill with clear executable examples and good structure. Its main weakness is the verbose model-specific parameters section that reads like API documentation rather than a concise skill guide—this could be tightened or moved to a reference file. The workflow is simple and clearly presented.

Suggestions

Move the detailed model-specific parameter tables to a separate REFERENCE.md file and link to it, keeping only the most essential defaults inline.

Remove the note about unimplemented features ('stream and moderation are available via API but not yet implemented') as it's not actionable.

Dimension	Reasoning	Score
Conciseness	The model-specific parameters section is quite detailed and reference-like, listing every valid size/quality option for each model. While useful, this level of API parameter documentation could be more concise or offloaded to a reference file. Some information like 'stream and moderation are available via API but not yet implemented' is unnecessary.	2 / 3
Actionability	Provides fully executable commands with concrete flags and examples. The usage examples cover multiple models with real flag combinations that are copy-paste ready. The output section clearly states what files are produced.	3 / 3
Workflow Clarity	This is a single-task skill (run a script, view output) with a clear two-step workflow: run the generation script, then open the gallery. The workflow is unambiguous and appropriate for the simplicity of the task.	3 / 3
Progressive Disclosure	The content is reasonably structured with clear sections, but the model-specific parameters section is quite lengthy and could be split into a separate reference file. For a skill of this size (~70 lines of content), the inline API parameter reference makes the main file heavier than necessary.	2 / 3
	Total	10 / 12 Passed

Validation

72%

Warnings & errors only

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: attilaczudor/Test
Commit: b4fc4af

Reviewed: 17 days ago

Table of Contents

Discovery Implementation Validation

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