CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

azure-ai-formrecognizer-java

Build document analysis applications using the Azure AI Document Intelligence SDK for Java.

Quality

64%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/azure-ai-formrecognizer-java/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%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, code-dense reference that is efficient and largely executable, covering the full feature surface of the SDK with honest boundary warnings. Its main weaknesses are structural and procedural: everything lives in one long file with no progressive disclosure, and destructive/billable model operations lack validation checkpoints, both capping the mid-tier dimensions at 3.

Suggestions

Add validation checkpoints around destructive/billable operations: show checking a model exists (getDocumentModel) before deleteDocumentModel, confirming poller terminal status, and verifying a built model's field schema before using it for analysis.

Split detailed sections (Custom Models, Document Classification, Manage Models) into separate reference files (e.g., references/custom-models.md, references/classification.md) and keep SKILL.md as a lean overview with clearly signaled one-level-deep links.

Remove the verbatim repeat of the description after the H1 and replace the generic "When to Use" boilerplate with task-specific guidance, tightening token efficiency.

DimensionReasoningScore

Conciseness

The body is lean and code-first — prose is limited to a dense, useful boundaries paragraph and short section intros — but the description sentence is repeated verbatim after the H1, and "When to Use"/"Limitations" are generic boilerplate that could be trimmed. The pinned 4.2.0-beta.1 version is time-sensitive, but it is explicitly framed as a legacy/prerelease boundary with verify-first guidance, partially mitigating the penalty.

4 / 5

Actionability

Abundant concrete, near-executable Java covering client creation, prebuilt analysis, custom models, classification, and error handling, with the poller pattern shown throughout. Minor gaps keep it from anchor 5: receiptUrl/containerUrl/documentUrl are used undeclared, the Context import is never shown, and the skill itself discloses that snippets are not one compilable file.

4 / 5

Workflow Clarity

Multi-step flows (analyze, build model, build classifier) show the begin-poll-getResult sequence and error handling for initiation failures, but destructive and billable operations — deleteDocumentModel, model builds, classifier training — are presented with no validation or verification checkpoints (e.g., confirm the model exists before delete, verify the build succeeded before analyzing with it). Per the rubric, destructive/batch operations without validation cap workflow clarity at 3.

3 / 5

Progressive Disclosure

Sections are well-organized with clear headers, but ~340 lines of API-reference material (model administration, composition, classification, resource limits) is inlined entirely in SKILL.md with no external reference files at all — content that clearly belongs in separate one-level-deep files. Anchor 3 (content that should be separate is inline) fits better than anchor 4 given the complete absence of any reference split.

3 / 5

Total

14

/

20

Passed

Description

48%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 correctly names a specific niche (Azure Document Intelligence for Java) but is a single generic action sentence with no concrete capabilities, no "when to use" trigger guidance, and no natural synonyms like "Form Recognizer" or "OCR". It sits just below the midpoint: distinct enough to avoid most conflicts, but not informative enough to trigger reliably or set expectations.

Suggestions

List concrete capabilities in the description, e.g. "Extract text, tables, and key-value pairs from documents, analyze receipts/invoices/IDs, and build custom document models and classifiers" instead of the generic "build document analysis applications".

Add an explicit "Use when..." clause covering natural user phrases such as "Use when working with Azure Form Recognizer or Document Intelligence in Java, or when extracting text, tables, or invoice/receipt data from documents".

Include the synonym "Form Recognizer" (the widely-used legacy name) and terms like "OCR" in the description itself, not just in the body's Trigger Phrases section.

DimensionReasoningScore

Specificity

"Build document analysis applications" names the domain (Azure AI Document Intelligence SDK for Java) but the sole action is generic — no concrete verbs like extract text, classify documents, or train custom models, matching anchor 2 rather than anchor 3's requirement for concrete actions.

2 / 5

Completeness

The "what" is stated (build document analysis applications with this SDK) but there is no "Use when..." clause or equivalent trigger guidance anywhere in the description, capping completeness at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Includes some relevant keywords ("document analysis", "Document Intelligence", "Java") but misses common variations and synonyms users actually say — notably "Form Recognizer", "OCR", and "extract text from PDF" — which appear only in the body's Trigger Phrases section, not the description.

3 / 5

Distinctiveness Conflict Risk

Naming the specific SDK and language ("Azure AI Document Intelligence SDK for Java") makes it mostly distinct with only minor overlap risk against generic PDF or document-processing skills; it lacks the explicit trigger phrases needed to reach anchor 5's minimal conflict risk.

4 / 5

Total

12

/

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.

Validation — 15 / 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/agentic-awesome-skills

Path

skills/azure-ai-formrecognizer-java/SKILL.md

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.