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agent-framework-azure-ai-py

Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.

48

Quality

52%

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/agent-framework-azure-ai-py/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, actionable skill with excellent executable code examples covering the full range of Azure AI Agent Framework capabilities. Its main weaknesses are repetitive boilerplate across examples, lack of error handling/validation guidance for cloud service operations, and missing bundle files to support the referenced paths. Trimming duplicate setup code and adding error handling patterns would significantly improve it.

Suggestions

Reduce boilerplate repetition by establishing the credential/provider pattern once and using abbreviated setup (e.g., '# ... same provider setup as above') in subsequent examples.

Add error handling and validation checkpoints: credential verification, agent creation failure handling, and tool execution error recovery patterns.

Provide the referenced bundle files (references/tools.md, references/mcp.md, etc.) or remove the references if they don't exist.

Consider moving the complete example to a reference file since it largely duplicates the individual pattern sections.

DimensionReasoningScore

Conciseness

The skill is mostly efficient with good code examples, but there's significant repetition in the boilerplate (credential/provider setup appears in nearly every example), and the complete example at the end largely duplicates earlier sections. The conventions and limitations sections contain some filler.

2 / 3

Actionability

All code examples are fully executable, copy-paste ready with correct imports, async patterns, and concrete function definitions. The examples cover basic agents, function tools, hosted tools, streaming, threads, and structured outputs with complete, runnable code.

3 / 3

Workflow Clarity

The skill presents clear individual patterns but lacks validation checkpoints. There's no guidance on error handling, verifying agent creation succeeded, checking credential validity, or handling failures in tool execution. For a skill involving cloud service interactions and persistent agents, missing error recovery steps is a notable gap.

2 / 3

Progressive Disclosure

The skill references four reference files (tools.md, mcp.md, threads.md, advanced.md) which is good structure, but no bundle files are provided to back them up. The main file itself is quite long (~250 lines) with the complete example largely duplicating earlier sections, suggesting some content could have been moved to reference files.

2 / 3

Total

9

/

12

Passed

Description

40%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 identifies a clear and distinctive niche (Azure AI Foundry + Microsoft Agent Framework + Python SDK), which makes it unlikely to conflict with other skills. However, it lacks a 'Use when...' clause entirely and provides only a high-level action ('Build persistent agents') without listing specific concrete capabilities, significantly reducing its effectiveness for skill selection.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about building agents on Azure AI Foundry, using the azure-ai-projects SDK, or creating persistent AI agents with Microsoft Agent Framework.'

List more specific concrete actions, e.g., 'Build persistent agents, configure tool integrations (code interpreter, file search, Azure Functions), manage agent threads and conversations, and deploy agents using the azure-ai-projects Python SDK.'

Include common user-facing trigger terms and variations such as 'Azure agents', 'azure-ai-projects', 'AI Foundry agent', 'agent service' to improve matching.

DimensionReasoningScore

Specificity

Names the domain (Azure AI Foundry, Microsoft Agent Framework) and a general action ('Build persistent agents'), but does not list multiple specific concrete actions like creating tools, managing conversations, deploying endpoints, etc.

2 / 3

Completeness

Describes what the skill does ('Build persistent agents on Azure AI Foundry') but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, a missing 'Use when...' clause caps completeness at 2, and since the 'what' is also only partially described, this scores a 1.

1 / 3

Trigger Term Quality

Includes relevant keywords like 'Azure AI Foundry', 'Microsoft Agent Framework', 'Python SDK', and 'persistent agents', but misses common user variations such as 'Azure agents', 'AI agent', 'agent service', 'azure-ai-projects', or related trigger phrases users might naturally say.

2 / 3

Distinctiveness Conflict Risk

The combination of 'Azure AI Foundry', 'Microsoft Agent Framework', and 'Python SDK' creates a very specific niche that is unlikely to conflict with other skills. This is clearly distinguishable from general coding, other cloud platforms, or other agent frameworks.

3 / 3

Total

8

/

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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