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verify-product-image

QC gate for a generated static ad image — verify the file opens, matches the requested dimensions, shows the correct product/subject (right shape, colour, label, logo), and has no garbled text or severe artifacts. Records pass/fail/needs-human in verification.md. Used as the final check in the static ad remix flow before shipping.

71

Quality

89%

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SecuritybySnyk

Passed

No findings from the security scan

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.

A concise, well-organized QC skill body that earns its tokens and is cleanly structured, but it lacks an explicit sequenced workflow with validation checkpoints and an error-recovery feedback loop, which caps its workflow clarity for a verification gate.

Suggestions

Number the checks into an explicit sequence (e.g. 1. inputs exist → 2. dimensions match → 3. product/brand/text checks → 4. write verification.md) so the workflow order is unambiguous.

Add a validation/feedback loop: on a failed check, specify how to record the failure, whether to retry or block, and when to escalate to 'needs human review'.

Spell out the verification.md record format (fields/columns for pass/fail/needs-human) so the output contract is concrete and repeatable.

DimensionReasoningScore

Conciseness

Lean body with no padding; assumes Claude's competence and never explains what an image or QC is, so every line earns its place.

5 / 5

Actionability

Checks are concrete and specific (shape, colour, label, logo, palette source, style_source branches), giving actionable QC guidance, though framed as descriptive checks rather than copy-paste-ready commands.

4 / 5

Workflow Clarity

Verification checks are listed but not sequenced into a numbered workflow with explicit validation checkpoints or a fix→re-validate feedback loop, which the rubric requires for a QC/batch skill.

3 / 5

Progressive Disclosure

A simple, well-organized skill under 50 lines with no bundle files; the single-level 'Checks' structure is appropriately self-contained 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.

A strong, specific description that clearly states both what the skill does and when to use it, with concrete verification actions and a distinct niche. The only minor gap is the absence of common file-extension synonyms in the trigger terms.

DimensionReasoningScore

Specificity

Lists multiple concrete verification actions — 'verify the file opens, matches the requested dimensions, shows the correct product/subject (right shape, colour, label, logo), and has no garbled text or severe artifacts' — covering the domain comprehensively.

5 / 5

Completeness

Explicitly answers both 'what' (QC gate verifying specific image attributes, recording pass/fail/needs-human) and 'when' ('Used as the final check in the static ad remix flow before shipping').

5 / 5

Trigger Term Quality

Includes natural domain terms ('static ad image', 'garbled text', 'artifacts', 'QC gate', 'verification.md') but omits common synonyms and file extensions (.png/.jpg), so a few natural terms are missing.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche ('static ad image', 'static ad remix flow') with distinct triggers and minimal overlap risk against general-purpose skills.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

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