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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.

77

1.81x
Quality

66%

Does it follow best practices?

Impact

100%

1.81x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/azure-ai-projects-dotnet/SKILL.md

The canonical home for this skill is azure-ai-projects-dotnet in sickn33/antigravity-awesome-skills

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, actionable SDK reference skill with excellent executable code examples covering all major operations. Its main weaknesses are the monolithic structure (everything inline rather than split into referenced files) and the lack of integrated validation/error recovery steps within multi-step workflows. Some minor verbosity and redundancy could be trimmed.

Suggestions

Integrate error handling and validation directly into multi-step workflows (especially the agent creation/polling workflow) rather than having a separate generic error handling section.

Split detailed workflow examples and reference tables into separate files (e.g., AGENTS.md, REFERENCE.md) and keep SKILL.md as a concise overview with links to each.

Remove the 'When to Use' section which adds no value, and deduplicate the Related SDKs table which repeats installation info from the top.

DimensionReasoningScore

Conciseness

The skill is fairly comprehensive but includes some unnecessary sections like 'When to Use' (which is a meaningless tautology), the 'Related SDKs' table that duplicates installation info, and the Best Practices section contains some advice Claude already knows (like using async for I/O). The reference tables and client hierarchy are efficient, but overall it could be tightened.

2 / 3

Actionability

All code examples are fully executable C# with proper using statements, concrete method calls, and complete workflows from client creation through cleanup. Each workflow section provides copy-paste ready code covering the full lifecycle of operations.

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 workflows. The error handling section is separate and generic rather than integrated into workflows where failures are likely (e.g., after creating resources or polling for completion).

2 / 3

Progressive Disclosure

The content is a single monolithic file with 8 detailed workflow sections plus reference tables, all inline. While it has clear section headers, the amount of content (agent tools table, key types reference, all workflow examples) could benefit from being split into separate reference files with the SKILL.md serving as an overview with links.

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 language along with concrete feature areas. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. Adding natural trigger terms and user-facing scenarios would further improve selection accuracy.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user needs to work with Azure AI Foundry projects in C#/.NET, including creating agents, managing deployments, or running evaluations.'

Include common user-facing trigger terms like 'C#', 'Azure.AI.Projects', 'NuGet', and 'AI Foundry' to improve matching against natural user queries.

DimensionReasoningScore

Specificity

Lists multiple specific concrete capabilities: agents, connections, datasets, deployments, evaluations, and indexes. Also specifies the technology stack (.NET) and the parent platform (Azure AI Foundry).

3 / 3

Completeness

Clearly answers 'what does this do' by listing capabilities, but lacks an explicit 'Use when...' clause or equivalent trigger guidance, which caps this dimension 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 task scenarios users might describe.

2 / 3

Distinctiveness Conflict Risk

Highly specific niche: Azure AI Projects SDK for .NET is a distinct technology with clear boundaries. Unlikely to conflict with other skills due to the specific platform (Azure AI Foundry) and language (.NET) scoping.

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.

Validation10 / 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
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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