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google-cloud-vision

Google Cloud Vision integration. Manage Images. Use when the user wants to interact with Google Cloud Vision data.

56

Quality

65%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./skills/google-cloud-vision/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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 with concrete CLI commands and a well-structured connection workflow including state-handling and polling loops. Its main weaknesses are an unnecessary intro paragraph re-explaining Cloud Vision and slightly inconsistent step labeling in the connection flow.

Suggestions

Trim the opening paragraph that defines what Google Cloud Vision is; Claude already knows this — start directly with what the skill does and how to use it.

Fix the step numbering: label the 'Searching for actions' section as 'Step 2' (or remove the 'skip to Step 2' forward reference) and add a '1a' counterpart to the existing '1b'.

Consider moving the detailed clientAction state-machine breakdown and the full Popular actions table into a references file, keeping SKILL.md as a tighter overview.

DimensionReasoningScore

Conciseness

The opening paragraph re-explains what Google Cloud Vision is ('a cloud-based image recognition service... powerful machine learning models') — a concept Claude already knows — and phrases like 'so you can focus on the integration logic rather than auth plumbing' pad otherwise lean command documentation, fitting 'mostly efficient but includes some unnecessary explanation'.

3 / 5

Actionability

Provides copy-paste-ready CLI commands (install, login, connection ensure, action list/run, request) with a flag table and JSON output conventions, but placeholders like CONNECTION_ID, actionId, and QUERY require substitution and input schemas are not shown inline, matching 'mostly executable guidance with minor gaps'.

4 / 5

Workflow Clarity

The install→authenticate→connect→poll→state-handling→search→run sequence includes validation checkpoints and a feedback loop ('poll again... to check if the state moved to READY'), but the 'skip to Step 2' reference points to an unlabeled step and step numbering (1b without 1a/Step 2) is inconsistent, fitting 'clear sequence with most checkpoints; minor gaps'.

4 / 5

Progressive Disclosure

Content is organized into clear, well-signaled sections (Overview, Authentication, Connecting, Searching, Popular actions, Proxy, Best practices) with no nested references and no bundle files present, but at ~165 lines the detailed clientAction state machine and 12-row actions table could arguably live in a separate reference, placing it at 'good structure; minor organization gaps'.

4 / 5

Total

15

/

20

Passed

Description

62%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 correctly identifies the product and includes a Use-when clause, but it is thin on concrete capability terms and uses a generic trigger. Adding specific triggers like image analysis, OCR, or label detection would raise both trigger quality and completeness.

Suggestions

Replace the generic 'Manage Images' with concrete capabilities, e.g. 'Annotate images, detect labels, faces, landmarks, and extract text (OCR)'.

Expand the Use-when clause with natural trigger phrases: 'Use when the user wants to analyze images, run OCR, detect objects/faces/landmarks, or moderate image content.'

Include common synonyms users say (image analysis, OCR, text extraction) to improve trigger term coverage.

DimensionReasoningScore

Specificity

Names the domain ("Google Cloud Vision integration") and a single action ("Manage Images"), but that action is generic rather than a concrete capability like annotation or OCR, matching the 'names domain and 1-2 concrete actions but not comprehensive' anchor.

3 / 5

Completeness

Provides both a 'what' ("Google Cloud Vision integration. Manage Images.") and a 'when' ("Use when the user wants to interact with Google Cloud Vision data"), but the trigger is generic rather than tied to concrete use cases, matching the 'has both what and when; when could be more specific' anchor.

4 / 5

Trigger Term Quality

Includes the natural product term "Google Cloud Vision" and "Images", but misses the capability keywords users actually say for this service (OCR, image analysis, object detection, label detection), fitting 'some relevant keywords but missing common variations'.

3 / 5

Distinctiveness Conflict Risk

The product name "Google Cloud Vision" establishes a clear niche with minimal conflict risk, though the generic "Manage Images" phrasing could overlap with other image-handling skills, placing it at 'mostly distinct; minor overlap risk'.

4 / 5

Total

14

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
membranedev/application-skills
Reviewed

Table of Contents

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