azure-ai-contentunderstanding-py

Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video.

Quality

72%

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Securityby

Low

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Quality

Content

82%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 strong, code-heavy SDK reference with executable examples across sync/async and all modalities plus a clear core workflow. The main gaps are minor repetition across modalities and the absence of explicit validation/error-handling checkpoints for the async and destructive operations.

Suggestions

Add an error-handling/validation example for the async poller (e.g. checking poller.status() and handling failed analysis).

Consolidate the repeated begin_analyze pattern across image/audio/video into one parameterized example to reduce redundancy.

Add a brief warning/validation step before the destructive delete_analyzer call.

Dimension	Reasoning	Score
Conciseness	The body is mostly code with minimal concept explanation and no padding about what PDFs/libraries are. It is efficient, though the image/audio/video analyze sections repeat the same begin_analyze+poller pattern with minor variation, which could be trimmed. This fits 4 ('efficient; minor instances that could be trimmed') rather than 5's 'every token earns its place'.	4 / 5
Actionability	Provides copy-paste-ready, executable code covering sync and async clients, all four prebuilt analyzers, custom analyzer creation, and analyzer management. Specific examples cover the common cases, matching the 5 anchor 'fully executable; copy-paste ready code'.	5 / 5
Workflow Clarity	The Core Workflow lays out a clear 3-step sequence (begin_analyze -> poller.result() -> process AnalysisResult.contents) and the async section reinforces the poller pattern. It earns 4 rather than 5 because there are no explicit validation/error-handling checkpoints (e.g. for failed analysis or the destructive delete_analyzer), and rather than 3 because the sequence and completion checkpoint are clearly stated.	4 / 5
Progressive Disclosure	The body is well-organized with clear section headers, tables for analyzers/content types/clients, and cohesive inline SDK reference. No bundle files exist and no external references are used, but the structure is good and content is appropriately placed for a single-file SDK overview, fitting 4 ('good structure; most content appropriately placed') rather than 3.	4 / 5
	Total	17 / 20 Passed

Description

62%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 well-formed, third-person, and answers both 'what' and 'when' with an explicit trigger clause. Its main weakness is that it names only one action (content extraction) and lacks synonyms/file extensions that users would naturally say.

Suggestions

Expand specificity by listing concrete actions beyond extraction (e.g. transcribe audio, extract invoice fields, generate markdown for RAG).

Add natural trigger terms and file extensions users say (e.g. 'PDFs, .mp4, .mp3, invoices, transcripts').

Tighten the 'Use for' clause with a clearer 'Use when the user wants to extract content from ...' phrasing.

Dimension	Reasoning	Score
Specificity	Names the domain ('Azure AI Content Understanding SDK for Python') and one concrete action ('multimodal content extraction from documents, images, audio, and video'), but only a single action is described rather than a comprehensive list. It matches the 'names domain and 1-2 concrete actions, but not comprehensive' anchor rather than 4, which requires several specific actions.	3 / 5
Completeness	Clearly states what it does ('multimodal content extraction from documents, images, audio, and video') and provides an explicit 'Use for...' trigger clause with concrete content types. It earns 4 rather than 5 because the 'when' trigger, while present, could be more specific with natural user phrasing; it exceeds 3 because explicit trigger guidance is present.	4 / 5
Trigger Term Quality	Includes relevant terms ('multimodal content extraction', 'documents, images, audio, and video', the SDK name) but lacks common synonyms and file extensions users might naturally say (e.g. 'PDF', 'mp4', 'transcription'). This fits 'some relevant keywords but missing common variations or synonyms' rather than 4's 'good keyword coverage'.	3 / 5
Distinctiveness Conflict Risk	The 'Azure AI Content Understanding SDK for Python' framing carves a clear, product-specific niche with minimal conflict risk. It is mostly distinct with only minor overlap risk against other generic document/AI extraction skills, fitting 4 rather than 5's 'clear niche with distinct triggers'.	4 / 5
	Total	14 / 20 Passed

Validation

93%

Warnings & errors only

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

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
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
Path: skills/azure-ai-contentunderstanding-py/SKILL.md
Commit: 7520423

Reviewed: ~10 hours ago

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