CtrlK
BlogDocsLog inGet started
Tessl Logo

azure-ai-textanalytics-py

Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.

64

Quality

76%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/azure-ai-textanalytics-py/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%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 thorough, highly actionable SDK reference with excellent executable examples, weakened by absent validation feedback loops for batch operations and a monolithic single-file structure with no progressive disclosure.

Suggestions

Add an explicit validate/retry loop for batch and long-running operations, e.g. check each result's is_error and re-run failed documents before proceeding.

Split the per-operation API details into a separate REFERENCE.md (one level deep) and keep SKILL.md as an overview pointing to it.

Remove or replace the filler 'When to Use' sentence with concrete, specific guidance on when to reach for this skill.

DimensionReasoningScore

Conciseness

The body is mostly lean executable code with little padding, but the vague 'When to Use' sentence ('applicable to execute the workflow or actions described in the overview') and the redundant Client Types table could be trimmed.

4 / 5

Actionability

It provides copy-paste-ready, executable examples for every common operation (sentiment with opinion mining, entities, PII, key phrases, language detection, healthcare, batch, async), covering the typical cases.

5 / 5

Workflow Clarity

This is an API reference rather than a sequenced workflow, and the long-running/batch operations (begin_analyze_actions, begin_analyze_healthcare_entities) lack explicit validation checkpoints or error-recovery feedback loops, capping the score at 3.

3 / 5

Progressive Disclosure

Content is well sectioned, but at ~230 lines everything is inlined in SKILL.md with no one-level-deep references; the per-operation API details that could live in separate reference files are all inline.

3 / 5

Total

15

/

20

Passed

Description

80%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, capability-dense description with an explicit 'Use for' trigger clause; its main weakness is a broad 'when' statement and some missing natural-term synonyms.

Suggestions

Replace the generic 'Use for natural language processing on text' with concrete triggers, e.g. 'Use when analyzing sentiment, recognizing entities, detecting PII, or extracting key phrases from text.'

Add common synonyms users actually say, such as 'NLP', 'text mining', and 'opinion mining', to broaden trigger coverage.

Include the file/library cue (e.g. 'with the Azure AI Language SDK') to further distinguish it from generic NLP skills.

DimensionReasoningScore

Specificity

The description enumerates multiple concrete capabilities ('sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP'), giving comprehensive coverage of the SDK's actions rather than vague language.

5 / 5

Completeness

Both 'what' (the listed capabilities) and 'when' ('Use for natural language processing on text') are present, but the when clause is broad and could name the concrete trigger scenarios more explicitly.

4 / 5

Trigger Term Quality

It includes natural NLP phrases users would say (sentiment analysis, entity recognition, key phrases, PII), but misses common synonyms/variants like 'NLP', 'text mining', or 'opinion mining'.

4 / 5

Distinctiveness Conflict Risk

Naming the specific Azure AI Text Analytics SDK gives it a clear niche, though the generic 'natural language processing on text' trigger could overlap with other general NLP skills.

4 / 5

Total

17

/

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

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.