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media-generation

Generate images, videos, and SVGs using x402-protected AI models at StableStudio. USE FOR: - Generating images from text prompts - Generating videos from text or images - Editing images with AI - Vectorizing images to SVG - Creating visual content TRIGGERS: - "generate image", "create image", "make a picture" - "generate video", "create video", "make a video" - "edit image", "modify image" - "vectorize", "convert to svg" - "stablestudio", "nano-banana", "sora", "veo", "grok", "flux", "seedance", "gpt-image" ALWAYS use agentcash.fetch for stablestudio.dev endpoints.

72

Quality

91%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%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 body is a dense, actionable reference with executable examples for every model and a clear polling workflow. Its main weaknesses are moderate table redundancy and two signaled reference files that do not exist in the bundle.

Suggestions

Consolidate the Quick Reference, per-model, and Model Comparison tables so cost/speed/best-for data lives in one place rather than being repeated across three sections.

Add a brief error-recovery note for job polling — what to do when a job fails or polls beyond its expected duration — to close the workflow feedback loop.

Add the referenced rules/getting-started.md and rules/uploads.md files to the bundle (or remove the links) so the signaled references resolve.

DimensionReasoningScore

Conciseness

Mostly lean and assumes Claude's competence (no concept padding), but cost/speed/best-for data is repeated across the Quick Reference tables, per-model sections, and Model Comparison tables, which could be consolidated.

4 / 5

Actionability

Fully executable mcp code blocks with real stablestudio.dev URLs and concrete body params, plus documented option enumerations — copy-paste ready and covering the common cases.

5 / 5

Workflow Clarity

Clear generate -> jobId/pollUrl -> poll sequence with explicit intervals ('Poll images every 3s, videos every 10s') and a guard ('do not resubmit pending jobs'), but no error-recovery guidance for failed or indefinitely polling jobs.

4 / 5

Progressive Disclosure

Well-organized sections with clearly signaled one-level-deep references ([rules/getting-started.md], [rules/uploads.md]); however those referenced files are not present in the bundle, so the signaled navigation does not fully resolve.

4 / 5

Total

17

/

20

Passed

Description

100%Weight 40%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 is exemplary: third-person voice, concrete capabilities, an explicit USE FOR clause, and a rich TRIGGERS list of natural phrases and model names. It clearly answers what the skill does and when to use it with minimal conflict risk.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Generate images, videos, and SVGs', 'Generating images from text prompts', 'Editing images with AI', 'Vectorizing images to SVG' — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both 'what' (generate images/videos/SVGs via x402-protected AI models at StableStudio) and 'when' (a USE FOR list plus a TRIGGERS list with concrete phrases).

5 / 5

Trigger Term Quality

Comprehensive natural terms including synonyms ('generate image', 'create image', 'make a picture') and model-name triggers users actually say ('sora', 'veo', 'grok', 'flux', 'nano-banana', 'seedance', 'gpt-image').

5 / 5

Distinctiveness Conflict Risk

Clear niche (media generation via StableStudio/x402 payments) with distinctive model-name triggers, making overlap with other skills minimal.

5 / 5

Total

20

/

20

Passed

Validation

81%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

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

relative_links

Relative link issues: 2 missing

Warning

Total

13

/

16

Passed

Repository
Merit-Systems/agentcash-skills
Reviewed

Table of Contents

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