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azure-ai-document-intelligence-ts

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

60

Quality

70%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/azure-ai-document-intelligence-ts/SKILL.md
SKILL.md
Quality
Evals
Security

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.

A strong, action-dense SDK reference: mostly lean executable code with a clear polling workflow and good section structure. Main improvements would be trimming the generic "When to Use"/"Limitations" boilerplate and optionally splitting the models/type reference into a bundled file.

DimensionReasoningScore

Conciseness

The body is predominantly lean, executable code with minimal prose and a useful non-obvious gotcha ("DocumentIntelligence is a function, not a class"), with only minor trimmable boilerplate in the "When to Use" and "Limitations" sections; not a 5 because those generic boilerplate lines add token weight without earning their place.

4 / 5

Actionability

Provides copy-paste-ready, fully executable TypeScript covering the common cases — URL and local-file analyze, invoice/receipt field extraction, model/classifier build, classification, listing, and service info — matching the anchor for fully executable code spanning common cases.

5 / 5

Workflow Clarity

The "Polling Pattern" section gives a clear numbered 5-step sequence with an isUnexpected() error-check checkpoint; not a 5 because there is no explicit validate-fix-retry feedback loop for the long-running build/classifier operations, leaving a minor validation gap.

4 / 5

Progressive Disclosure

Content is well organized into clearly headed sections with no nested references and no bundle files to navigate; not a 5 because at ~334 lines some reference material (the full prebuilt-models table and the bulk type/API reference) could be split into separate files for a cleaner overview.

4 / 5

Total

17

/

20

Passed

Description

58%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 states a clear "what" with several concrete actions and a reasonably distinct niche, but lacks any "Use when..." trigger guidance and natural conversational keywords. Adding explicit trigger phrases and file-format terms would raise completeness and trigger-term quality.

Suggestions

Append a "Use when..." clause naming natural triggers, e.g. "Use when extracting text or tables from PDFs/images, processing invoices/receipts, or classifying documents with Azure Document Intelligence."

Add user-natural terms and file extensions (PDFs, invoices, receipts, scanned images, .pdf/.jpg/.png) to improve trigger-term coverage.

Tighten distinctiveness by referencing the specific Azure service and SDK so it does not collide with generic OCR or document skills.

DimensionReasoningScore

Specificity

Lists several concrete actions — "Extract text, tables, and structured data" via "prebuilt and custom models" — matching the anchor for several specific actions with minor coverage gaps; not a 5 because it does not enumerate a comprehensive set of distinct actions.

4 / 5

Completeness

Clearly answers "what" (extract text/tables/structured data via prebuilt and custom models) but provides no "Use when..." trigger clause, so per the judging guidelines completeness is capped at 3; not a 4 because "when" is entirely absent rather than weakly implied.

3 / 5

Trigger Term Quality

Contains relevant keywords ("documents", "text", "tables", "structured data", "prebuilt and custom models") but misses natural user phrases and file extensions (e.g., PDFs, invoices, .pdf), fitting the anchor for some relevant keywords missing common variations; not a 4 due to the absence of conversational trigger terms.

3 / 5

Distinctiveness Conflict Risk

The "prebuilt and custom models" framing carves a fairly distinct niche tied to document-intelligence services with only minor overlap risk against generic document-processing skills; not a 5 because "documents" alone is broad enough to invite some overlap.

4 / 5

Total

14

/

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
sickn33/antigravity-awesome-skills
Reviewed

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