CtrlK
BlogDocsLog inGet started
Tessl Logo

azure-ai-openai-dotnet

Azure OpenAI SDK for .NET. Client library for Azure OpenAI and OpenAI services. Use for chat completions, embeddings, image generation, audio transcription, and assistants.

57

Quality

66%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/antigravity-azure-ai-openai-dotnet/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

64%

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 API reference skill with excellent actionability — nearly every feature is demonstrated with complete, executable C# code. The main weaknesses are its monolithic length (could benefit from splitting advanced topics into separate files) and some unnecessary content like boilerplate sections and a type reference table that largely duplicates what the code examples already show. The function calling workflow is incomplete, missing the critical step of returning tool results to the model.

Suggestions

Complete the function calling workflow by showing how to send tool results back to the model (the ToolChatMessage response loop), as this is a critical multi-step process that's currently truncated.

Split advanced topics (RAG integration, structured outputs, function calling, audio) into separate bundle files and reference them from SKILL.md to reduce the monolithic size.

Remove the 'When to Use' and 'Limitations' boilerplate sections and the Key Types Reference table — the types are already demonstrated in context through the code examples.

DimensionReasoningScore

Conciseness

The skill is comprehensive with executable examples, but includes some unnecessary content like the 'When to Use' and 'Limitations' boilerplate sections, the 'Related SDKs' table (Claude knows these), and the Key Types Reference table which largely restates what's already demonstrated in the code examples. The best practices section contains some obvious advice Claude already knows.

2 / 3

Actionability

Nearly every section provides fully executable, copy-paste ready C# code with proper using statements, concrete method calls, and realistic examples covering chat completions, streaming, structured outputs, embeddings, image generation, audio, function calling, and error handling. The code is complete and specific rather than pseudocode.

3 / 3

Workflow Clarity

The skill is primarily a reference/cookbook rather than a multi-step workflow, so individual sections are clear. However, the function calling section shows the tool call detection but doesn't show the complete loop of sending tool results back to the model, which is a critical multi-step workflow gap. Error handling shows retry but lacks a proper feedback loop pattern.

2 / 3

Progressive Disclosure

The content is a monolithic ~400-line file with no bundle files to offload detailed sections. The structured outputs, function calling, and RAG integration sections could be split into separate reference files. The Reference Links table at the end provides external navigation, but the inline content is heavy for a single SKILL.md.

2 / 3

Total

9

/

12

Passed

Description

67%

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 reasonably strong with good specificity of capabilities and a clear niche identity. Its main weaknesses are the lack of an explicit 'Use when...' trigger clause describing user scenarios and missing some natural trigger terms users might use (like 'C#', 'GPT', or 'NuGet'). Adding scenario-based triggers and broader keyword coverage would improve skill selection accuracy.

Suggestions

Add an explicit 'Use when...' clause with scenario triggers, e.g., 'Use when the user needs to integrate OpenAI or Azure OpenAI into a .NET/C# application, or asks about calling GPT models from C#.'

Include additional natural trigger terms users might say: 'C#', '.NET', 'GPT', 'DALL-E', 'Whisper', 'NuGet', 'Azure AI', 'OpenAI API client'.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: chat completions, embeddings, image generation, audio transcription, and assistants. These are distinct, well-defined capabilities.

3 / 3

Completeness

The 'what' is well covered (client library for Azure OpenAI/OpenAI services with specific capabilities), and there is a 'Use for...' clause listing capabilities, but it lacks an explicit 'Use when...' trigger clause describing scenarios (e.g., 'when the user wants to integrate OpenAI into a .NET application' or 'when working with Azure AI services in C#').

2 / 3

Trigger Term Quality

Includes relevant terms like 'Azure OpenAI', 'chat completions', 'embeddings', 'image generation', 'audio transcription', and 'assistants', but misses common user variations like 'GPT', '.NET', 'C#', 'NuGet', 'OpenAI API', or 'text-to-speech'. Also missing file extensions or SDK-specific terms users might search for.

2 / 3

Distinctiveness Conflict Risk

The combination of 'Azure OpenAI SDK for .NET' creates a very clear niche. It's unlikely to conflict with other skills since it targets a specific platform (Azure), specific technology (OpenAI), and specific language ecosystem (.NET).

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
boisenoise/skills-collections
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.