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azure-ai-vision-imageanalysis-java

Build image analysis applications with Azure AI Vision SDK for Java. Use when implementing image captioning, OCR text extraction, object detection, tagging, or smart cropping.

86

1.28x
Quality

80%

Does it follow best practices?

Impact

100%

1.28x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/azure-ai-vision-imageanalysis-java/SKILL.md

The canonical home for this skill is azure-ai-vision-imageanalysis-java in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

71%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 content is a well-organized, executable pattern catalog with lean code examples. Its main weaknesses are the all-inlined single-file structure with no progressive disclosure and a recurring undefined-variable gap in some snippets.

Suggestions

Move the full visual-features table and complete API pattern catalog into a separate reference file (e.g. REFERENCE.md) and link to it from SKILL.md to improve progressive disclosure.

Define or initialize the 'imageUrl' variable consistently across all code snippets (e.g. assign it from an env var or a literal) so every example is directly copy-paste runnable.

Remove the redundant 'Trigger Phrases' list and the generic 'When to Use' sentence, relying on the description's explicit trigger guidance instead.

DimensionReasoningScore

Conciseness

The body is code-dense and lean with no concept over-explanation, but the 'Trigger Phrases' list partly duplicates the description and the generic 'When to Use' sentence is fluff, so minor trimming would reach anchor 5.

4 / 5

Actionability

Extensive copy-paste Java examples cover all visual features, but several snippets (object detection, tags, people, smart crops, dense captions) reference an undefined 'imageUrl' variable, a minor gap keeping it below the fully-executable anchor 5.

4 / 5

Workflow Clarity

A clear progression from installation to client creation, analysis, and error handling is present, and the operations are non-destructive so no validation cap applies, but there are no explicit validation checkpoints, matching anchor 4.

4 / 5

Progressive Disclosure

The ~285-line body is well-sectioned but entirely inlined with no external reference files, so content that could be split (full pattern catalog, visual-features reference) lives inline, matching anchor 3 rather than 4.

3 / 5

Total

15

/

20

Passed

Description

88%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: it clearly states the capability and provides an explicit 'Use when' clause with concrete triggers. Minor improvement is possible by adding synonymous terms to widen natural-keyword coverage.

DimensionReasoningScore

Specificity

Lists five concrete actions (image captioning, OCR text extraction, object detection, tagging, smart cropping), matching the comprehensive-coverage anchor; not 4 because coverage is broad rather than having minor gaps.

5 / 5

Completeness

Explicitly states what it does ('Build image analysis applications with Azure AI Vision SDK for Java') and when to use it ('Use when implementing...') with concrete trigger phrases, matching anchor 5.

5 / 5

Trigger Term Quality

Natural terms like 'image captioning', 'OCR text extraction', and 'smart cropping' are present, but synonyms such as 'computer vision', 'Vision API', or 'image recognition' are missing, so it falls short of comprehensive anchor 5.

4 / 5

Distinctiveness Conflict Risk

The Azure AI Vision SDK for Java niche is distinct, but generic vision trigger terms (OCR, object detection, captioning) carry minor overlap risk with other vision/OCR skills, placing it at anchor 4 rather than 5.

4 / 5

Total

18

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

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

Table of Contents

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