vertex-ai-media-master

Execute automatic activation for all google vertex ai multimodal operations operations. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.

Quality

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Quality

Content

50%

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 clean, well-structured overview with a sequenced workflow, concrete model/parameter specifics, and a useful error table, but it lacks any executable code, its validation step is generic rather than a real feedback loop, and several bundle reference files go unsignaled. These gaps hold every dimension at 2.

Suggestions

Add a minimal executable snippet for the canonical request (e.g. a vertexai GenerativeModel call with the model ID, prompt, and parameters) so the core flow is copy-paste ready rather than prose.

Make the validation step a concrete checkpoint with a retry loop, e.g. 'After generation, verify output schema/brand rules; if violations found, revise the prompt and regenerate before delivery.'

Link the existing bundle files (examples.md, errors.md) from the body instead of inlining their content, or remove the unused files so signaled references match the actual bundle.

Dimension	Reasoning	Score
Conciseness	The body is well-organized and avoids explaining concepts Claude already knows, but the prose-heavy Instructions and Output sections describe rather than instruct and could be tightened, fitting the mostly-efficient-but-could-be-tightened anchor at 2.	2 / 3
Actionability	Concrete details exist (model names, aspect ratios, quota numbers, error table), but the core steps ('Construct the generation request with explicit parameters', 'Execute the request') provide no executable SDK code or commands and the examples are prose, matching the some-guidance-but-incomplete/missing-key-details anchor at 2.	2 / 3
Workflow Clarity	A clear 7-step sequence with a final 'Validate results' step is present, plus an error-handling table, but the validation checkpoint is generic ('validate against brand guidelines') with no concrete validate-fix-retry loop; since the skill performs batch generation, the rubric caps workflow clarity at 2.	2 / 3
Progressive Disclosure	Sections are clearly organized and one reference (references/core-capabilities.md) is real and signaled, but the bundle also contains examples.md and errors.md that are not linked from the body while their content is inlined, fitting the references-present-but-not-fully-signaled anchor at 2.	2 / 3
	Total	8 / 12 Passed

Description

35%

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 genuine niche but is dominated by template boilerplate ('automatic activation', 'trigger with relevant phrases based on skill purpose') rather than concrete capabilities or natural trigger terms. It answers 'what' and 'when' only weakly, capping most dimensions at 2 and trigger quality at 1.

Suggestions

Replace the boilerplate with concrete capabilities, e.g. 'Analyze video, generate images with Imagen 4, compose audio with Lyria, and automate marketing campaigns on Google Vertex AI.'

Add real natural-language triggers users would say: 'Use when the user asks to generate images, analyze a video, create background music, or build marketing campaign assets with Vertex AI.'

Drop the meta phrasing ('Execute automatic activation', 'Trigger with relevant phrases based on skill purpose') which adds no actionable signal.

Dimension	Reasoning	Score
Specificity	It names a domain ('google vertex ai multimodal operations') and a nominal action ('Execute automatic activation'), but no concrete capabilities (video understanding, image generation, audio generation) are listed and 'automatic activation' is abstract, so it falls short of the multi-specific-action anchor at 3.	2 / 3
Completeness	A 'Use when...' clause exists in form but is vacuous, and the 'what' is weak ('execute automatic activation for multimodal operations'); per the guideline a missing meaningful explicit trigger caps completeness at 2, which it does not exceed.	2 / 3
Trigger Term Quality	The only 'trigger' language is boilerplate ('Use when appropriate context detected. Trigger with relevant phrases based on skill purpose') with no natural keywords a user would say (e.g. 'generate image', 'analyze video'), matching the no-natural-keywords/jargon anchor at 1.	1 / 3
Distinctiveness Conflict Risk	The Vertex AI multimodal niche is specific enough to avoid broad conflicts, but the generic trigger phrasing ('appropriate context detected') means it could still overlap or misfire, fitting the somewhat-specific-but-overlapping anchor at 2.	2 / 3
	Total	7 / 12 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Commit: 3022dd3

Reviewed: 2 days ago

Table of Contents

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