azure-containerregistry-py

Azure Container Registry SDK for Python. Use for managing container images, artifacts, and repositories.

Quality

61%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/azure-containerregistry-py/SKILL.md

Quality

Discovery

57%

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 domain and provides some context for when to use it, but lacks specific concrete actions and natural trigger terms users might employ. It would benefit from listing specific operations (push, pull, tag, delete images) and including common abbreviations and alternative phrasings users might use.

Suggestions

List specific concrete actions such as 'push, pull, tag, delete, and list container images' instead of the generic 'managing'.

Add common trigger terms and abbreviations like 'ACR', 'docker registry', 'Azure container registry', '.azurecr.io' to improve matching.

Expand the 'Use for' clause into a more explicit 'Use when...' with trigger scenarios, e.g., 'Use when the user needs to interact with Azure Container Registry, mentions ACR, or wants to manage Docker images in Azure using Python'.

Dimension	Reasoning	Score
Specificity	Names the domain (Azure Container Registry SDK for Python) and lists some actions ('managing container images, artifacts, and repositories'), but doesn't enumerate specific concrete actions like pushing, pulling, tagging, deleting, or listing images.	2 / 3
Completeness	Has a 'what' (Azure Container Registry SDK for Python) and a partial 'when' ('Use for managing container images, artifacts, and repositories'), but lacks explicit trigger guidance like 'Use when the user mentions ACR, Azure container registry, or needs to manage Docker images in Azure'.	2 / 3
Trigger Term Quality	Includes relevant keywords like 'Azure Container Registry', 'container images', 'artifacts', and 'repositories', but misses common variations users might say such as 'ACR', 'docker registry', 'push image', 'pull image', or 'container registry Python'.	2 / 3
Distinctiveness Conflict Risk	The description is clearly scoped to Azure Container Registry SDK for Python, which is a distinct niche unlikely to conflict with other skills. The combination of Azure, container registry, and Python SDK makes it highly distinguishable.	3 / 3
	Total	9 / 12 Passed

Implementation

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 API reference skill with excellent actionability—nearly every operation has complete, executable Python code. However, it suffers from being a monolithic document that could benefit from splitting detailed examples into reference files, and the destructive operations (delete repository, delete manifest, cleanup) lack validation checkpoints and confirmation steps. The boilerplate 'When to Use' and 'Limitations' sections add no meaningful value.

Suggestions

Add validation/confirmation steps to destructive operations: include a dry-run pattern for the cleanup workflow (e.g., collect digests first, print count, then delete) and error handling for delete operations.

Remove the generic 'When to Use' and 'Limitations' boilerplate sections—they add no skill-specific value and waste tokens.

Consider splitting the operations reference table and detailed per-operation examples into a separate REFERENCE.md, keeping SKILL.md as a quick-start with the most common operations.

Dimension	Reasoning	Score
Conciseness	The content is mostly efficient with executable code examples, but includes some unnecessary sections like the boilerplate 'When to Use' and 'Limitations' sections that add no value, and the operations table duplicates information already shown in the code examples above it. The best practices section is reasonably concise though.	2 / 3
Actionability	Nearly all guidance is provided as concrete, executable Python code snippets that are copy-paste ready. Authentication, CRUD operations, async usage, and cleanup workflows all have complete, runnable examples with proper imports.	3 / 3
Workflow Clarity	The 'Clean Up Old Images' section shows a multi-step destructive batch operation (deleting manifests) but lacks explicit validation checkpoints or confirmation steps. There's no feedback loop for error handling during deletion, and no dry-run recommendation before executing batch deletes. Per scoring notes, missing feedback loops for destructive/batch operations caps this at 2.	2 / 3
Progressive Disclosure	The content is a long monolithic file (~200 lines) with no references to external files. While sections are well-organized with clear headers, the API reference table and detailed examples for every operation could be split into separate reference files. For a skill of this length, some progressive disclosure into supporting files would improve navigability.	2 / 3
	Total	9 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

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

	Total	10 / 11 Passed

Repository: sickn33/antigravity-awesome-skills
Commit: 9e5d4dd

Reviewed: 6 days ago

Table of Contents

Discovery Implementation Validation

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