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azure-ai-projects-py

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

52

Quality

60%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/azure-ai-projects-py/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

71%Weight 40%Scale 1-5

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

The body is a well-organized, code-first SDK overview with strong actionability and a clear agent thread/run workflow, though it carries some duplication and boilerplate filler. Its main defect is that every progressive-disclosure pointer references bundle files that are missing, so the promised depth cannot actually be reached.

Suggestions

Ship the referenced bundle files (references/agents.md, references/tools.md, and the other eight references plus scripts/run_batch_evaluation.py) or remove the pointers — currently all 11 referenced paths are broken.

Remove the content-free "When to Use" and "Limitations" boilerplate sections or replace them with skill-specific guidance.

Deduplicate the AIProjectClient construction (shown in both Authentication and Two Client Approaches) and complete the async example, replacing the `create_agent(...)` placeholder with real parameters.

DimensionReasoningScore

Conciseness

The body is dominated by lean, executable SDK-specific code and comparison tables, but AIProjectClient construction is duplicated (Authentication and Two Client Approaches sections), get_openai_client() appears twice, and the "When to Use"/"Limitations" sections are content-free boilerplate that could be trimmed. Not a 5 because these redundancies are real; not a 3 because the bulk of the content earns its tokens.

4 / 5

Actionability

Nearly all examples are concrete and executable (install command, env vars, auth, agent creation, tools, thread flow, connections, evaluation), covering the common cases. Not a 5 because the async example uses a `create_agent(...)` ellipsis placeholder rather than complete code.

4 / 5

Workflow Clarity

The Thread and Message Flow section gives a clear numbered 1-4 sequence with an explicit `run.status == "completed"` checkpoint, and Best Practices adds sequencing guidance. Not a 5 because there is no error-recovery guidance (what to do when a run fails or how to inspect run errors).

4 / 5

Progressive Disclosure

The in-file structure is good: each section ends with a clearly signaled "See references/X.md" pointer and a consolidated Reference Files index. However, none of the 11 referenced files (references/*.md, scripts/run_batch_evaluation.py) exist in the bundle — the references/ and scripts/ directories are absent — so every pointer dangles and the disclosed detail is unreachable. Not a 4 because broken references are more than a minor organization gap; not a 2 because the SKILL.md itself is well-organized rather than inlined or buried.

3 / 5

Total

15

/

20

Passed

Description

48%Weight 40%Scale 1-5

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 concise and correctly names the platform and SDK, giving it a clear niche, but it stops at a single generic action and omits any 'use when' trigger guidance. Users searching for agent, evaluation, or deployment work on Azure AI Foundry would not reliably match it.

Suggestions

Add an explicit trigger clause, e.g. "Use when building AI agents, evaluations, or model deployments on Azure AI Foundry with the azure-ai-projects SDK."

Enumerate 2-4 concrete capabilities (agent CRUD and versions, threads/runs, project connections, model deployments, evaluations) instead of the generic "Build AI applications".

Include the natural product name users say, "Azure AI Foundry", and synonyms like "AI agents" to improve trigger-term coverage.

DimensionReasoningScore

Specificity

"Build AI applications on Microsoft Foundry using the azure-ai-projects SDK" names the domain but offers only one generic action ("Build AI applications"), matching the 'Processes PDF files' anchor. It is not a 3 because no concrete capability (agents, threads, evaluations, connections) is enumerated.

2 / 5

Completeness

The 'what' is stated (build AI applications on Foundry with this SDK) but there is no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3. Not a 4 because 'when' is entirely absent rather than merely imprecise.

3 / 5

Trigger Term Quality

"Microsoft Foundry" and "azure-ai-projects SDK" are relevant keywords a user might say, but common variations and synonyms are missing ("Azure AI Foundry", "AI agents", "agent SDK", "Azure"). Not a 4 because the natural phrases users would actually use are largely absent.

3 / 5

Distinctiveness Conflict Risk

Naming the specific platform and SDK ("Microsoft Foundry", "azure-ai-projects SDK") carves a mostly distinct niche with only minor overlap risk against a sibling azure-ai-agents skill. Not a 5 because the description provides no explicit distinct trigger phrases.

4 / 5

Total

12

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

referenced_paths_exist

Referenced path issues: 18 missing

Warning

Total

14

/

16

Passed

Repository
sickn33/agentic-awesome-skills
Reviewed

Table of Contents

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