CtrlK
BlogDocsLog inGet started
Tessl Logo

azure-ai-projects-py

Build AI applications on Microsoft Foundry using the azure-ai-projects SDK.

46

Quality

48%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/azure-ai-projects-py/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 SDK reference skill with strong actionability — nearly every section includes executable Python code with proper imports and configuration. The main weaknesses are the lack of validation/error-handling steps in workflows and moderate verbosity from boilerplate sections and tables that could be trimmed. The progressive disclosure structure is well-designed but cannot be fully validated without bundle files.

Suggestions

Add error handling and validation checkpoints to the Thread and Message Flow section (e.g., checking run.status for failures, handling exceptions from agent creation).

Remove the boilerplate 'When to Use' and 'Limitations' sections, and trim the 'Best Practices' to only non-obvious guidance to improve conciseness.

Provide the referenced bundle files (references/*.md, scripts/*.py) so the progressive disclosure structure is functional rather than aspirational.

DimensionReasoningScore

Conciseness

The skill is mostly efficient with executable code examples, but includes some unnecessary sections like 'When to Use' and 'Limitations' boilerplate, the SDK Comparison table explaining things Claude can infer, and the 'Best Practices' section contains fairly obvious guidance. The overview table and tools table are useful reference material though.

2 / 3

Actionability

The skill provides fully executable, copy-paste ready code examples throughout — authentication, agent creation, thread/message flow, connections, deployments, async usage, and memory stores all have concrete, runnable Python code with proper imports and environment variable references.

3 / 3

Workflow Clarity

The Thread and Message Flow section provides a clear numbered sequence, but there are no validation checkpoints or error handling steps. For operations like agent creation, deployment, and evaluation runs, there's no guidance on checking for failures, handling errors, or verifying success beyond a simple status check.

2 / 3

Progressive Disclosure

The skill references 11 separate reference files and a script, which is excellent structure in principle. However, no bundle files were provided, so these references are unverifiable. The main file itself is quite long (~250 lines) and some sections like Datasets/Indexes and Deployments are thin stubs that add little value inline — they could be omitted or consolidated. The reference file listing at the bottom is well-organized.

2 / 3

Total

9

/

12

Passed

Description

32%

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 the platform and SDK but is too terse to be effective for skill selection. It lacks specific concrete actions, natural trigger terms users would use, and critically has no 'Use when...' clause to guide Claude on when to select this skill.

Suggestions

Add a 'Use when...' clause with explicit triggers, e.g., 'Use when the user mentions Azure AI Foundry, azure-ai-projects, Azure AI agents, or building AI apps on Microsoft Foundry.'

List specific concrete actions the skill covers, e.g., 'Create and configure AI agents, manage connections, deploy models, run evaluations, and set up tracing using the azure-ai-projects SDK.'

Include common keyword variations users might naturally say, such as 'Azure AI', 'Azure Foundry', 'AI agents', 'Azure AI SDK', or 'azure.ai.projects'.

DimensionReasoningScore

Specificity

Names the domain (AI applications on Microsoft Foundry) and the SDK (azure-ai-projects), but does not list specific concrete actions like 'create agents', 'deploy models', 'manage datasets', etc.

2 / 3

Completeness

Provides a brief 'what' (build AI applications) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, missing 'Use when' caps completeness at 2, and the 'what' is also weak, so this scores a 1.

1 / 3

Trigger Term Quality

Includes relevant keywords like 'Microsoft Foundry', 'azure-ai-projects SDK', and 'AI applications', but misses common variations users might say such as 'Azure AI', 'Azure Foundry', 'AI agents', or specific task-related terms.

2 / 3

Distinctiveness Conflict Risk

The mention of 'Microsoft Foundry' and 'azure-ai-projects SDK' provides some distinctiveness, but 'Build AI applications' is broad enough to potentially overlap with other Azure or AI-related skills.

2 / 3

Total

7

/

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
sickn33/antigravity-awesome-skills
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.