azure-ai-contentsafety-py
Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.
60
70%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/antigravity-azure-ai-contentsafety-py/SKILL.mdQuality
Discovery
75%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 concise and well-structured with a clear 'Use for...' clause that addresses both what the skill does and when to use it. Its main weakness is moderate specificity—it could enumerate more concrete actions—and it misses common user-facing trigger terms like 'content moderation' or 'toxicity detection' that users might naturally use.
Suggestions
Add more specific concrete actions such as 'analyze text categories, configure severity thresholds, manage blocklists, detect hate speech and violence'.
Include common natural-language trigger terms users might say, such as 'content moderation', 'toxicity detection', 'NSFW filtering', or 'hate speech detection'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Azure AI Content Safety SDK) and a key action (detecting harmful content with multi-severity classification), but doesn't list multiple specific concrete actions like configuring thresholds, analyzing categories, or handling blocklists. | 2 / 3 |
Completeness | Clearly answers both 'what' (Azure AI Content Safety SDK for Python) and 'when' ('Use for detecting harmful content in text and images with multi-severity classification'), with an explicit 'Use for...' trigger clause. | 3 / 3 |
Trigger Term Quality | Includes relevant keywords like 'Azure AI Content Safety', 'harmful content', 'text and images', and 'multi-severity classification', but misses common user variations like 'content moderation', 'toxicity detection', 'hate speech', 'NSFW', or 'content filtering'. | 2 / 3 |
Distinctiveness Conflict Risk | Very specific niche targeting the Azure AI Content Safety SDK for Python, which is unlikely to conflict with other skills. The combination of Azure, content safety, and SDK creates a distinct trigger profile. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid API reference skill with excellent actionability — all code examples are complete and executable. However, it's somewhat verbose with redundant imports, unnecessary explanatory tables for concepts Claude already understands, and generic boilerplate sections. The workflow could benefit from explicit error handling patterns and sequencing for multi-step operations like blocklist setup.
Suggestions
Remove the boilerplate 'When to Use' and 'Limitations' sections, and trim the Harm Categories description table — Claude already knows these concepts.
Add error handling examples (e.g., try/except for HttpResponseError) and explicit validation steps after API calls to improve workflow clarity.
Reduce repeated import blocks by showing full imports once and using abbreviated forms (assuming client is already created) in subsequent examples.
Consider splitting blocklist management into a separate reference file to improve progressive disclosure and reduce the main file length.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient with good code examples, but includes unnecessary content like the 'When to Use' and 'Limitations' boilerplate sections, the Harm Categories description table (Claude knows what hate speech and violence are), and some redundant import statements repeated across examples. The Best Practices section is somewhat generic. | 2 / 3 |
Actionability | All code examples are fully executable, copy-paste ready with correct imports, proper client initialization, and realistic usage patterns. Covers authentication, text analysis, image analysis, blocklist management, and severity configuration with concrete, runnable code. | 3 / 3 |
Workflow Clarity | The skill presents individual operations clearly but lacks explicit workflow sequencing for multi-step processes like blocklist creation → adding items → analyzing with blocklist. There are no validation checkpoints or error handling patterns shown, which matters for API operations that can fail. | 2 / 3 |
Progressive Disclosure | The content is reasonably well-organized with clear section headers, but it's a long monolithic file (~180 lines) with reference tables and detailed blocklist management that could be split into separate files. No bundle files exist to offload advanced content, and there are no cross-references to external documentation. | 2 / 3 |
Total | 9 / 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.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- boisenoise/skills-collections
- Commit
8ac11ab
- Reviewed
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