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azure-ai-projects-dotnet

Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes.

57

Quality

66%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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

Quality

Content

64%Scale 1-3

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

This is a solid SDK reference skill with excellent actionability — all code examples are complete and executable C#. The main weaknesses are the monolithic structure (everything in one file with no progressive disclosure to supporting files) and missing validation/error-recovery steps in multi-step workflows like agent creation and evaluation runs. Some minor verbosity from boilerplate sections and duplicated information slightly reduces token efficiency.

Suggestions

Add explicit validation checkpoints and error recovery loops to the agent and evaluation workflows (e.g., check run.Status for failure states, handle RequestFailedException during polling)

Split detailed code examples for each workflow (agents, datasets, indexes, evaluations) into separate reference files and keep SKILL.md as a concise overview with links

Remove the boilerplate 'When to Use' and 'Limitations' sections which add no skill-specific value, and deduplicate the Related SDKs table with the Installation section

DimensionReasoningScore

Conciseness

The skill is fairly comprehensive but includes some unnecessary content like the boilerplate 'When to Use' and 'Limitations' sections that add no value, and the 'Related SDKs' table duplicates information already in the Installation section. The reference tables and best practices are useful but could be tighter. Overall mostly efficient but not maximally lean.

2 / 3

Actionability

All code examples are fully executable C# with proper using statements, concrete method calls, and complete workflows including cleanup. The examples cover authentication, agent creation, polling, connections, datasets, indexes, evaluations, and error handling — all copy-paste ready.

3 / 3

Workflow Clarity

The agent workflow includes polling and cleanup steps which is good, but there are no explicit validation checkpoints or error recovery feedback loops in the multi-step agent workflows. The evaluation workflow doesn't show how to poll for completion status. Steps are listed but validation gaps exist for operations that could fail.

2 / 3

Progressive Disclosure

The content is well-structured with clear headers and a logical hierarchy, but it's a monolithic document (~300 lines) with no bundle files to offload detailed content. The agent tools table, key types reference, and detailed code examples for all 8 workflows could be split into separate reference files. Reference links are provided but no internal file references exist.

2 / 3

Total

9

/

12

Passed

Description

67%Scale 1-3

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 strong in specificity and distinctiveness, clearly identifying the SDK, platform, and concrete capabilities. However, it lacks an explicit 'Use when...' clause, which is critical for Claude to know when to select this skill. Adding natural trigger terms and user-facing language would improve discoverability.

Suggestions

Add a 'Use when...' clause, e.g., 'Use when the user needs to work with Azure AI Foundry projects in .NET, or mentions Azure AI agents, deployments, or evaluations in C#.'

Include common user-facing trigger terms like 'C#', 'NuGet', 'Azure.AI.Projects namespace', or scenario-based phrases like 'create an Azure AI agent' or 'manage Azure AI deployments'.

DimensionReasoningScore

Specificity

Lists multiple specific concrete capabilities: agents, connections, datasets, deployments, evaluations, and indexes. Also specifies the SDK name, platform (.NET), and that it's a high-level client for Azure AI Foundry projects.

3 / 3

Completeness

Clearly answers 'what does this do' (high-level client for Azure AI Foundry projects with specific sub-capabilities), but lacks an explicit 'Use when...' clause or equivalent trigger guidance, which caps this at 2 per the rubric.

2 / 3

Trigger Term Quality

Includes relevant keywords like 'Azure AI', '.NET', 'agents', 'deployments', 'evaluations', but misses common user variations like 'C#', 'NuGet', 'Azure.AI.Projects', or mentioning specific use cases users might describe naturally.

2 / 3

Distinctiveness Conflict Risk

Very specific niche: Azure AI Projects SDK for .NET is a clearly defined, narrow domain. The combination of 'Azure AI Foundry', '.NET', and the specific feature list (agents, connections, datasets, etc.) makes it highly unlikely to conflict with other skills.

3 / 3

Total

10

/

12

Passed

Validation

90%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
popey/claude-code-skills
Reviewed

Table of Contents

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