Conciseness

The body is mostly efficient code with minimal prose, but it could be tightened: the start-poll-wait boilerplate (path().post, isUnexpected, getLongRunningPoller, pollUntilDone) repeats nearly verbatim in at least five sections even though the "Polling Pattern" section already abstracts it, and the "When to Use" ("This skill is applicable to execute the workflow or actions described in the overview") and "Limitations" sections are generic filler that add no information. Matches anchor 3; not 4 because the redundancy and boilerplate sections are more than minor.

Actionability

Code is concrete and executable: real npm install commands, both DefaultAzureCredential and API-key auth, URL and base64 source variants, per-model field access (invoice.fields?.VendorName?.content), and a prebuilt-model table. Not 5 because of minor gaps — the heading "## Analyze Document https://example.com" carries a stray URL fragment, and several snippets reference undefined variables (invoiceUrl, receiptUrl, urlSource) without a complete runnable context.

Workflow Clarity

The "Polling Pattern" section gives a clear numbered 5-step sequence (start → check isUnexpected → create poller → onProgress → pollUntilDone) and every snippet includes the isUnexpected error checkpoint. Not 5 because there is no validation of the final result state (e.g., checking the operation status or analyzeResult for failed/skipped operations) and no error-recovery guidance; not 3 because the sequence and main checkpoints are explicit. The destructive/batch cap does not apply since these are read and async-training operations.

Progressive Disclosure

Sections are well-labeled, but everything lives inline in a single ~330-line SKILL.md with no references/ directory: the prebuilt-model field reference, classifier build, and per-model extraction examples are content that would suit one-level-deep reference files. Matches anchor 3 (some structure but content that should be separate is inline); not 4 because no external organization exists at all for a skill of this size.

Specificity

"Extract text, tables, and structured data from documents using prebuilt and custom models" lists several concrete actions (text extraction, table extraction, structured data extraction) with the prebuilt/custom model distinction. Not 5 because coverage has gaps — classification, invoice/receipt field extraction, and model building are not mentioned; not 3 because it goes beyond 1-2 actions.

Completeness

The "what" is clearly stated (extract text, tables, structured data with prebuilt/custom models), but there is no "Use when..." clause or equivalent trigger guidance, capping completeness at 3 per the judging guidelines. Not 4 because the "when" is entirely absent rather than merely imprecise.

Trigger Term Quality

Relevant keywords like "documents", "tables", "prebuilt", and "custom models" are present, but common natural variations users would say are missing: invoice, receipt, OCR, PDF, and notably "Azure" itself. Matches anchor 3 (some relevant keywords but missing common variations or synonyms); not 4 because the keyword set is thin for a domain this rich.

Distinctiveness Conflict Risk

"Extract text and tables from documents" could plausibly overlap with generic PDF-processing or document-parsing skills, and the omission of "Azure" or "Document Intelligence" removes the clearest distinguishing brand trigger. Not 4 because the overlap risk extends beyond just closely related skills.