azure-ai-projects-ts

High-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations.

Quality

65%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./skills/azure-ai-projects-ts/SKILL.md

Quality

Content

72%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 content is highly actionable with executable, copy-paste-ready examples across the SDK surface, but lacks validation feedback loops around destructive operations and keeps all reference material inlined rather than splitting it into separate files.

Suggestions

Add validation/verification steps (e.g. check the agent or resource exists before deleting, confirm deletion succeeded) around destructive operations to lift workflow clarity above the destructive-cap of 3.

Move the bulk API reference and per-operation-group examples into a separate references/ file, keeping SKILL.md a concise overview with clearly signaled one-level-deep links.

Add a brief getting-started sequence (install → authenticate → first agent → verify) so the common path is explicitly ordered.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's knowledge of TypeScript and Azure — no conceptual padding — but is fairly long with many inline code blocks that could be tightened into a reference file.	4 / 5
Actionability	Provides fully executable, copy-paste-ready code covering the common cases across authentication, agents with multiple tool types, connections, deployments, datasets, and indexes.	5 / 5
Workflow Clarity	Sections are organized by operation group, but destructive operations (deleteVersion, conversations.delete, datasets.delete, indexes.delete) appear without validation checkpoints or feedback loops, which the rubric caps at 3.	3 / 5
Progressive Disclosure	All content is inlined in a single ~290-line file with no bundle files in references/, scripts/, or assets/ and no one-level-deep references; section headers provide some structure, but API-reference material that could be split out remains inline.	3 / 5
	Total	15 / 20 Passed

Description

58%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 clearly names the domain and concrete capability areas but lacks any explicit "Use when..." trigger guidance, capping completeness. Trigger terms lean technical and miss natural user phrasings.

Suggestions

Add a "Use when..." clause naming concrete trigger phrases, e.g. "Use when building or managing Azure AI Foundry agents, connections, deployments, or evaluations."

Reframe capability areas as actions rather than nouns (e.g. "Create and manage AI agents, list connections, deploy models, run evaluations").

Include natural synonyms users would say (e.g. "AI agents", "model deployments", "evaluating models") alongside the SDK jargon.

Dimension	Reasoning	Score
Specificity	Enumerates concrete capability areas — "agents, connections, deployments, and evaluations" — naming the SDK domain and four specific surfaces, though these are noun-lists rather than action verbs, leaving minor coverage gaps versus the comprehensive anchor.	4 / 5
Completeness	The "what" is clear — a high-level SDK for Azure AI Foundry projects — but there is no "Use when..." clause or equivalent explicit trigger guidance, which the rubric caps at 3.	3 / 5
Trigger Term Quality	Relevant technical keywords ("Azure AI Foundry", "agents", "deployments", "evaluations") are present but lean toward SDK jargon, missing common user-phrased synonyms and natural variations a user would actually say.	3 / 5
Distinctiveness Conflict Risk	"Azure AI Foundry projects" is a clearly distinct niche with specific triggers, with only minor overlap risk against generic Azure SDK skills.	4 / 5
	Total	14 / 20 Passed

Validation

93%

Warnings & errors only

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

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: administrakt0r/AI-Agents-Safe-Coding-Skills
Path: skills/azure-ai-projects-ts/SKILL.md
Commit: debb2ec

Reviewed: 17 hours ago

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