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azure-ai-contentsafety-java

Build content moderation applications using the Azure AI Content Safety SDK for Java.

48

Quality

52%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/antigravity-azure-ai-contentsafety-java/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

64%

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

This skill provides comprehensive, executable Java code examples for the Azure AI Content Safety SDK, covering all major operations. Its main weaknesses are the monolithic structure (everything inline with no progressive disclosure), lack of workflow sequencing for multi-step operations like blocklist management, and some unnecessary boilerplate sections (Trigger Phrases, When to Use, Limitations) that consume tokens without adding value.

Suggestions

Add an explicit workflow sequence for blocklist-based moderation: create blocklist → add items → wait 5 min → validate with test text → use in production analysis, with verification steps.

Remove the 'Trigger Phrases', 'When to Use', and 'Limitations' boilerplate sections as they add no instructional value and waste tokens.

Split blocklist management operations into a separate BLOCKLIST.md reference file, keeping only a brief overview and link in the main SKILL.md.

Remove the 'Key Concepts' harm categories table — Claude already knows what hate speech and violence categories mean; keep only the severity scale info which is SDK-specific.

DimensionReasoningScore

Conciseness

The skill is mostly efficient with executable code examples, but includes some unnecessary content: the 'Key Concepts' table explaining harm categories is basic knowledge Claude already has, the 'Trigger Phrases' and 'When to Use' sections add no instructional value, and the 'Best Practices' section could be tighter. The version-specific dependency also risks staleness.

2 / 3

Actionability

All code examples are fully executable Java with proper imports, concrete method calls, and realistic usage patterns. The examples cover client creation, text/image analysis, blocklist CRUD operations, and error handling — all copy-paste ready.

3 / 3

Workflow Clarity

The skill presents individual operations clearly but lacks a cohesive workflow sequence. For blocklist management (a multi-step process: create blocklist → add items → wait for propagation → analyze with blocklist), there's no explicit sequencing or validation checkpoints. The 5-minute delay note is buried in best practices rather than integrated into the workflow.

2 / 3

Progressive Disclosure

The content is a long monolithic document (~200+ lines) with no references to external files. The blocklist management section and detailed API patterns could be split into separate reference files. However, the sections are well-organized with clear headers, which partially compensates.

2 / 3

Total

9

/

12

Passed

Description

40%

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 a clear and distinct technology niche (Azure AI Content Safety SDK for Java) which helps with distinctiveness, but it lacks specific concrete actions and completely omits a 'Use when...' clause. Adding explicit trigger conditions and enumerating specific capabilities (e.g., text analysis, image analysis, blocklist management) would significantly improve skill selection accuracy.

Suggestions

Add a 'Use when...' clause with trigger terms like 'content moderation', 'harmful content', 'Azure Content Safety', 'text safety analysis', 'image moderation Java'.

List specific concrete actions such as 'analyze text for harmful content', 'classify image safety', 'manage custom blocklists', 'detect hate speech, violence, or self-harm content'.

Include common user-facing variations like 'content filtering', 'safety API', 'moderate user-generated content' to improve trigger term coverage.

DimensionReasoningScore

Specificity

Names the domain (content moderation) and the technology (Azure AI Content Safety SDK for Java), but doesn't list specific concrete actions like 'detect harmful text', 'classify images', 'manage blocklists', etc.

2 / 3

Completeness

Describes what (build content moderation apps with Azure AI Content Safety SDK for Java) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, missing 'Use when' caps completeness at 2, and the 'what' is also not very detailed, warranting a 1.

1 / 3

Trigger Term Quality

Includes relevant keywords like 'content moderation', 'Azure AI Content Safety', 'SDK', and 'Java', but misses common variations users might say such as 'harmful content detection', 'text moderation', 'image moderation', 'blocklist', or 'safety API'.

2 / 3

Distinctiveness Conflict Risk

The combination of 'Azure AI Content Safety SDK' and 'Java' creates a very specific niche that is unlikely to conflict with other skills. This is a clearly distinct technology and language pairing.

3 / 3

Total

8

/

12

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
boisenoise/skills-collections
Reviewed

Table of Contents

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