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imagen

AI image generation skill powered by Google Gemini, enabling seamless visual content creation for UI placeholders, documentation, and design assets.

40

Quality

39%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./skills/imagen/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

38%Scale 1-5

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

The skill is overly verbose, spending significant tokens explaining obvious concepts (when to generate images, what image generation is) while lacking the most critical content: the actual generation script or concrete API code. The examples section provides vague natural-language descriptions instead of executable code, and there are no validation or error-handling steps for API calls and file operations.

Suggestions

Remove or drastically trim the 'When to Use This Skill', 'How It Works', and narrative 'Examples' sections—Claude already understands these concepts and triggers.

Include the actual generate_image.py script in the bundle, or inline the core API call code so the skill is self-contained and actionable.

Add validation steps: check for GEMINI_API_KEY before calling, verify the output file exists and is a valid PNG after generation, and provide error recovery guidance.

Replace the vague natural-language examples with concrete CLI commands paired with expected outputs (file paths, success messages).

DimensionReasoningScore

Conciseness

The skill over-explains concepts Claude already knows (what image generation is, when to use it, how it works at a high level). The 'When to Use This Skill' section lists obvious triggers, and the 'How It Works' section describes a trivial 4-step pipeline that adds no value. The 'Examples' section shows vague pseudo-interactions rather than concrete code.

2 / 5

Actionability

The CLI usage examples with the Python script are somewhat concrete, but the 'Examples' section provides only vague natural-language descriptions of what would happen rather than executable code or actual commands. The script itself is referenced but not provided (no bundle files), and there's no actual API code shown—just CLI invocations of a script whose contents are unknown.

3 / 5

Workflow Clarity

The 'How It Works' section provides a basic 4-step sequence, and the CLI usage is clear enough. However, there are no validation steps—no guidance on what to do if the API key is missing, if generation fails, if the output file is invalid, or how to verify the generated image meets requirements. For a skill involving external API calls and file I/O, this is a notable gap.

3 / 5

Progressive Disclosure

The skill references 'scripts/generate_image.py' but no bundle files are provided, making it impossible to verify the reference. All content is inlined in a single file with no separation of concerns. The verbose sections (When to Use, How It Works, Examples) could be trimmed rather than split out, but the missing script file is a significant gap—the skill is essentially incomplete without it.

2 / 5

Total

10

/

20

Passed

Description

39%Scale 1-5

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 identifies the domain (AI image generation via Google Gemini) and lists some use case contexts, but lacks concrete actions and has no explicit 'when to use' guidance. The language leans toward marketing fluff ('seamless visual content creation') rather than precise capability description, and it misses natural trigger terms users would actually say.

Suggestions

Add a 'Use when...' clause with trigger terms like 'generate an image', 'create a picture', 'make an illustration', 'text-to-image', or 'AI-generated image'.

Replace vague phrasing like 'enabling seamless visual content creation' with concrete actions such as 'Generates images from text prompts, creates icons, produces placeholder graphics, and designs visual assets'.

Include natural synonyms and variations users might say, such as 'picture', 'illustration', 'graphic', 'AI art', or 'text-to-image'.

DimensionReasoningScore

Specificity

Names the domain (AI image generation) and mentions use cases (UI placeholders, documentation, design assets) but doesn't describe concrete actions like 'generates images from text prompts', 'creates icons', or 'produces illustrations'. The use cases listed are more context than actions.

2 / 5

Completeness

Has a vague 'what' (AI image generation for visual content creation) but completely lacks a 'when' clause. There is no 'Use when...' or equivalent trigger guidance, which per the rubric should cap completeness at 3, and the weak 'what' brings it to 2.

2 / 5

Trigger Term Quality

Includes some relevant keywords like 'image generation', 'Gemini', 'visual content', 'UI placeholders', 'design assets', but misses natural user phrases like 'generate an image', 'create a picture', 'make an illustration', 'text-to-image', or 'AI art'.

3 / 5

Distinctiveness Conflict Risk

Specifying 'Google Gemini' as the underlying technology and 'AI image generation' as the capability makes it fairly distinct. Minor overlap risk with other image or design-related skills, but the Gemini specificity helps differentiate it.

4 / 5

Total

11

/

20

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.

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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