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azure-ai-projects-java

Azure AI Projects SDK for Java. High-level SDK for Azure AI Foundry project management including connections, datasets, indexes, and evaluations.

57

Quality

66%

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

Quality

Content

67%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 body is a well-structured, largely executable SDK reference with good section organization, working code samples, and useful error-handling guidance. Its main weaknesses are filler sections ('When to Use', generic 'Limitations') and a pinned beta version that will age, plus small execution gaps in two code examples. Tightening the boilerplate and completing the stub snippets would move it toward the top of the scale.

Suggestions

Delete or replace the boilerplate 'When to Use' and 'Limitations' sections with skill-specific guidance (e.g., which operations are read-only vs. billable, rate limits on evaluations).

Remove or contextualize the pinned '1.0.0-beta.1' version (e.g., 'use the latest beta from Maven Central') so the content does not age, per the time-sensitive-information guideline.

Fix the incomplete examples: define `version` in the error-handling snippet, replace the `getOpenAIClient()` stub with a runnable evaluation call, and add a DatasetsClient upload example since it is promised in the client table.

DimensionReasoningScore

Conciseness

The body is mostly efficient — tables and terse code blocks with little explanatory prose — but includes unnecessary filler: the 'When to Use' section is contentless boilerplate ('This skill is applicable to execute the workflow or actions described in the overview.'), the 'Limitations' section is generic disclaimer text, and the pinned version '1.0.0-beta.1' is time-sensitive information not placed in a deprecation/old-patterns section. These are exactly the 'some unnecessary explanation or could be tightened' cases of anchor 3; it is well above the verbose anchor 2 but not the clean anchor 4.

3 / 5

Actionability

Nearly all guidance is executable: complete Maven coordinates, a working auth snippet with imports, sub-client construction, and runnable list/create examples. Minor gaps keep it from anchor 5: the error-handling example references an undefined `version` variable, the OpenAI evaluations snippet ('evaluationsClient.getOpenAIClient()') is a stub without a usable follow-on call, and DatasetsClient is listed in the table but has no example.

4 / 5

Workflow Clarity

The reference-style content follows a coherent install → environment → authentication → clients → operations → errors sequence, and the Error Handling section provides catch-and-branch recovery for get operations. However, there is no explicit multi-step workflow narrative (the sequence is implied by section order only) and no validation checkpoints on write operations like createOrUpdate — matching anchor 4 ('clear sequence with most checkpoints present; minor validation gaps') rather than anchor 5.

4 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are absent) and the body references none, so scoring rests on structure: sections are well-organized with a clear overview table, one-level-deep external links in a Reference Links table, and no buried or nested references. At ~150 lines, some reference material (e.g., the full client table plus per-operation examples) could be split into a separate file, which is the minor organization gap of anchor 4 rather than the fully split structure of anchor 5.

4 / 5

Total

15

/

20

Passed

Description

65%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 distinctive and keyword-rich for its narrow niche, and clearly states what the SDK covers, but it reads as a product blurb rather than a skill description: it contains no action verbs and no 'Use when...' trigger clause, the latter capping completeness at 3 per the rubric guidelines. Adding an explicit trigger clause and concrete verbs ('Enumerate connections, upload datasets, create search indexes, run evaluations. Use when working with the Azure AI Projects SDK for Java or Azure AI Foundry in Java.') would lift it substantially.

Suggestions

Add an explicit 'Use when...' clause naming the trigger scenarios, e.g., 'Use when writing Java code against Azure AI Foundry or the azure-ai-projects Maven artifact.'

Replace the static product sentence with concrete action verbs: 'Enumerate connections, upload datasets, create and manage search indexes, and run model evaluations with the Azure AI Projects SDK for Java.'

Include a couple of natural synonyms users might say (e.g., 'Azure AI Foundry', 'AI hub', 'azure-ai-projects Maven package') to broaden trigger-term coverage.

DimensionReasoningScore

Specificity

The description names the domain ('Azure AI Projects SDK for Java', 'Azure AI Foundry project management') and enumerates four concrete coverage areas ('connections, datasets, indexes, and evaluations'), but uses no action verbs — 'project management including' describes scope, not what the skill does. It sits between the anchor-2 example ('names the domain but actions are minimal') and anchor-3 ('1-2 concrete actions'); the enumerated areas give it more concreteness than anchor 2, but the absence of any concrete actions keeps it below anchor 4.

3 / 5

Completeness

The 'what' is clearly stated ('High-level SDK for Azure AI Foundry project management including connections, datasets, indexes, and evaluations') but there is no 'Use when...' clause or equivalent trigger guidance — the rubric explicitly caps completeness at 3 in that case. It is clearly above anchor 2 (which tolerates only a vague 'what') because the 'what' is specific, and below anchor 4, which requires an explicit 'when'.

3 / 5

Trigger Term Quality

It includes the natural phrases a user needing this skill would say: 'Azure AI Projects', 'Java', 'Azure AI Foundry'. A few natural variations are missing (e.g., 'Foundry SDK', 'Maven', 'AI hub'), and there are no file-extension or synonym variants, which keeps it below the comprehensive anchor 5.

4 / 5

Distinctiveness Conflict Risk

The niche is unambiguous: a Java SDK for Azure AI Projects / Azure AI Foundry. The combination of language ('Java'), product ('Azure AI Projects SDK'), and platform ('Azure AI Foundry') creates clear, distinct triggers with minimal overlap risk against generic Azure, AI, or Java skills.

5 / 5

Total

15

/

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
boisenoise/skills-collections
Reviewed

Table of Contents

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