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azure-ai-document-intelligence-ts

Extract text, tables, and structured data from documents using prebuilt and custom models.

55

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The body is highly actionable with copy-paste-ready executable code, but it is a monolithic 320-line file with repeated polling boilerplate and no progressive disclosure via reference files. Batch build operations also lack verification feedback loops.

Suggestions

Factor the repeated analyze+poll boilerplate into a single canonical pattern and have per-model examples show only the differing request body and field access.

Split advanced content (custom model build, classifier build, per-prebuilt field schemas) into reference files linked from the overview to enable one-level-deep progressive disclosure.

Add a verification step to the build workflows (e.g., test the built model against a sample document) to form a validate→fix→retry feedback loop.

DimensionReasoningScore

Conciseness

The body is lean and code-dense with no concept explanations, but the analyze→isUnexpected→getLongRunningPoller→pollUntilDone boilerplate repeats across roughly eight examples and the "When to Use"/"Limitations" sections are generic filler.

2 / 3

Actionability

Examples are fully executable TypeScript with imports, real REST path calls, concrete field access, plus installation commands and env vars — copy-paste ready per the anchor.

3 / 3

Workflow Clarity

The "Polling Pattern" section gives a clear numbered sequence with an explicit isUnexpected error-check step, but the build-model and build-classifier batch operations lack a verify→fix→retry feedback loop, which caps batch-op workflows at 2.

2 / 3

Progressive Disclosure

The 320-line file has well-organized sections but no bundle files and no external references, with advanced build/classifier and per-model content kept inline; it exceeds the under-50-line simple-skill exemption.

2 / 3

Total

9

/

12

Passed

Description

60%

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 concretely states what the skill does but omits any "when to use" trigger guidance, which caps completeness and distinctiveness. Trigger-term coverage is decent but leans technical rather than reflecting natural user phrasing.

Suggestions

Add an explicit "Use when..." clause naming natural user triggers (e.g., extracting text from PDFs, parsing invoices/receipts, or working with Azure Document Intelligence).

Include common natural keywords users would say — PDF, invoices, receipts, OCR, .pdf — rather than relying on the technical "prebuilt and custom models" phrasing.

Tie distinctiveness to the Azure Document Intelligence SDK specifically so it does not overlap with generic document-extraction skills.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "Extract text, tables, and structured data" — plus the prebuilt/custom model distinction, matching the multi-action anchor rather than the partial-action anchor at 2.

3 / 3

Completeness

The "what" is clear, but there is no "Use when..." or equivalent explicit trigger clause; per the judging guidelines a missing trigger caps completeness at 2.

2 / 3

Trigger Term Quality

Natural terms like "documents", "text", and "tables" appear, but "prebuilt and custom models" is technical jargon and common user variations (PDF, invoices, receipts, OCR) are missing, so it is not full coverage.

2 / 3

Distinctiveness Conflict Risk

"prebuilt and custom models" signals a recognizable niche, but "documents" is broad and lacks an explicit trigger, so it could still overlap with other document-extraction skills.

2 / 3

Total

9

/

12

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
boisenoise/skills-collections
Reviewed

Table of Contents

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