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azure-ai-projects-py

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

50

Quality

55%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/azure-ai-projects-py/SKILL.md

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

SKILL.md
Quality
Evals
Security

Quality

Content

57%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 highly actionable and reasonably well structured, but it is longer than necessary with redundant examples, lacks validation checkpoints for its batch/evaluation workflows, and points to reference files that are missing from the bundle.

Suggestions

Add explicit validation/verification checkpoints to the evaluation and batch-evaluation workflows (e.g., check run status, confirm eval results before acting) to lift workflow clarity above the batch cap.

Either include the referenced references/*.md and scripts/*.py files or remove the dangling 'See references/...' pointers and the Reference Files index so navigation is not broken.

Tighten redundancy — show auth once and avoid re-demonstrating create_agent — and move the version-pinned detail ('v2.0.0b4', 373 exports) into the api-reference file rather than the overview.

DimensionReasoningScore

Conciseness

The body is code- and table-forward with no concept padding, but at ~290 lines it carries notable redundancy (auth shown twice, create_agent repeated across sections, operations table overlapping later sections), which exceeds the 'minor instances' threshold of a 4.

3 / 5

Actionability

It is dense with concrete, copy-paste-ready code for auth, agents, threads/runs, evals, memory, and async, with specific env vars and imports; only minor gaps (the async block ends with '...' ellipsis and an elided create_agent call) keep it from a 5.

4 / 5

Workflow Clarity

The thread/message/run flow is numbered and sequenced, but there are no validation or error-recovery checkpoints, and the skill spans batch operations (batch evaluation script) — the rubric's batch/destructive cap therefore holds workflow clarity at 3.

3 / 5

Progressive Disclosure

Structure is well intended with section-level 'See references/X.md' pointers and a Reference Files index, but the referenced references/*.md and scripts/*.py files do not exist on disk, so the one-level-deep navigation is broken rather than merely minor-gapped.

3 / 5

Total

13

/

20

Passed

Description

53%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 specific to its platform and clearly distinct, but it states only a single generic action and omits any explicit 'Use when...' trigger guidance. Adding concrete capabilities and a trigger clause would lift specificity and completeness.

Suggestions

Add a 'Use when ...' clause naming natural triggers (e.g., 'Use when building agents or AI apps on Azure AI Foundry or working with the azure-ai-projects SDK').

Replace the single generic action 'Build AI applications' with 2-3 concrete capabilities (e.g., 'Create and version agents, manage threads and runs, run evaluations') to improve specificity.

Include a couple of natural synonyms or file/extension cues users actually say to broaden trigger-term coverage.

DimensionReasoningScore

Specificity

The description names a concrete platform and SDK ('Microsoft Foundry', 'azure-ai-projects SDK') but offers only one generic action ('Build AI applications'), so it sits between the 'names domain, minimal actions' and 'names domain plus 1-2 concrete actions' anchors.

3 / 5

Completeness

It gives a clear 'what' (build AI apps on Foundry with this SDK) but no explicit 'when/Use when...' clause, so per the guideline a missing trigger clause caps completeness at 3.

3 / 5

Trigger Term Quality

It surfaces relevant domain terms ('AI applications', 'Microsoft Foundry', 'azure-ai-projects') a user might say, but leans technical/proper-noun heavy and omits synonyms or common variations, matching the 'some relevant keywords, missing variations' anchor.

3 / 5

Distinctiveness Conflict Risk

Naming the specific azure-ai-projects SDK and Foundry platform carves a distinct niche with only minor overlap risk against a generic azure-ai-agents skill, fitting the 'mostly distinct, minor overlap' anchor rather than the fully conflict-free 5.

4 / 5

Total

13

/

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.

Validation14 / 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
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

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