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nano-banana-pro-openrouter

Deterministic OpenRouter image generation adapter for Nano Banana Pro / Gemini image models. Use as skill_exec when a meta-skill needs local image files and structured IMAGE_READY records without spawning an LLM agent.

69

Quality

86%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

80%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 concise and well-structured with concrete payload and contract details, and the executable code is appropriately delegated to a one-level-deep bundle script. The main weakness is the absence of an explicit batch-image validation/retry loop, which caps workflow clarity.

Suggestions

Add an explicit per-image validation step and a validate→fix→retry loop for the batch (max-images) path so workflow clarity can exceed the batch cap of 3.

Include one short in-body invocation or output snippet (e.g. a sample IMAGE_READY: line) to make the body more directly copy-paste actionable.

Spell out what happens when an individual image in a batch fails while others succeed, so error recovery for batch generation is unambiguous.

DimensionReasoningScore

Conciseness

Lean and efficient with no padded explanation of concepts Claude already knows; every section earns its place and assumes Claude's competence.

5 / 5

Actionability

Concrete behavioral guidance (JSON payload example, slot semantics, exit codes) but no in-body copy-paste code; the executable logic lives in the bundled script referenced via the entrypoint, leaving minor gaps.

4 / 5

Workflow Clarity

The contract lists a pre-submission checkpoint (missing lease exits 78) and failure handling, but batch image generation (max-images) lacks an explicit validate→fix→retry feedback loop, capping a batch operation at 3.

3 / 5

Progressive Disclosure

Well-organized into Contract / Payload Mode / Plain Prompt Mode with the executable logic one level deep in scripts/openrouter_image.py via the entrypoint; structure is clear and easy to navigate.

5 / 5

Total

17

/

20

Passed

Description

92%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 strong, third-person, and clearly states both what the skill does and when to use it, with concrete trigger phrasing. Its only minor gap is a few natural synonyms/extensions a user might say.

DimensionReasoningScore

Specificity

Names the domain and multiple concrete actions — 'image generation adapter', 'local image files', 'structured IMAGE_READY records', 'without spawning an LLM agent' — giving comprehensive coverage of what it does.

5 / 5

Completeness

Explicitly answers both 'what' (deterministic adapter producing local image files and IMAGE_READY records) and 'when' ('Use as skill_exec when a meta-skill needs...') with a concrete trigger clause.

5 / 5

Trigger Term Quality

Good natural keyword coverage ('image generation', 'image files', 'Nano Banana Pro', 'Gemini image models') but a few synonyms or file extensions a user might say are missing, so it stops just short of comprehensive.

4 / 5

Distinctiveness Conflict Risk

A clear niche — a deterministic skill_exec adapter for specific OpenRouter image models — with distinct triggers and minimal overlap risk against generic image skills.

5 / 5

Total

19

/

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_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

13

/

16

Passed

Repository
TokenRhythm/opensquilla
Reviewed

Table of Contents

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