Name: google-cloud-ai-platform
Rating: 56.8 (1 reviews)
Author: membranedev

google-cloud-ai-platform

Google Cloud AI Platform integration. Manage data, records, and automate workflows. Use when the user wants to interact with Google Cloud AI Platform data.

Quality

65%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/google-cloud-ai-platform/SKILL.md

Quality

Content

82%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 a strong, actionable integration guide with concrete commands and a well-structured connection state machine, only slightly weakened by a generic intro paragraph, a duplicated actions section, and minor sequence/reference rough edges.

Suggestions

Remove or shrink the opening overview paragraph explaining what Google Cloud AI Platform is, since Claude already knows this; start directly at the integration workflow.

Consolidate the duplicate action-discovery guidance: the "Searching for actions" and "Popular actions" sections both explain `membrane action list --intent`; merge them into one.

Number the connection workflow steps explicitly (1. ensure, 2. wait/get, 3. search, 4. run/proxy) so the "skip to Step 2" and "Step 2" references resolve to visible steps.

Dimension	Reasoning	Score
Conciseness	The body is largely efficient with command blocks and a compact flag table, but it opens with an unnecessary paragraph explaining what Google Cloud AI Platform is ("a suite of machine learning tools and services...") that Claude already knows, and a few phrases could be trimmed.	4 / 5
Actionability	Nearly every section provides concrete, copy-paste-ready commands (membrane login, connection ensure, action list/run, request) plus a flag table, covering the common integration cases with executable syntax.	5 / 5
Workflow Clarity	The connection flow is well sequenced with explicit state checks (READY / BUILDING / CLIENT_ACTION_REQUIRED / CONFIGURATION_ERROR) and a poll loop, but it mixes "Step 2" references without a clearly numbered top-level sequence and the "Popular actions" section partially repeats earlier guidance.	4 / 5
Progressive Disclosure	Content is organized into clear sections (Overview, Authentication, Connecting, Searching, Running, Proxy, Best practices) with no bundle files to split into; a few inline sections (the full clientAction schema details, the duplicate action-list section) could be tightened to reach a clean 5.	4 / 5
	Total	17 / 20 Passed

Description

48%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 its actions are generic and the trigger is shallow. It is distinguishable mainly by the product name rather than by concrete capabilities.

Suggestions

Replace generic verbs ("Manage data, records, and automate workflows") with concrete AI Platform actions such as "train and deploy ML models, manage model versions, and serve predictions from endpoints".

Expand the Use-when clause with concrete trigger phrases users would say, e.g. "Use when the user wants to train or deploy a model, manage model versions, or serve predictions on Google Cloud AI Platform".

Add natural synonyms/task terms (e.g. "AI Platform", "train a model", "deploy an endpoint") to improve trigger-term coverage.

Dimension	Reasoning	Score
Specificity	"Manage data, records, and automate workflows" names the domain but the actions are generic and minimal, with no concrete Google Cloud AI Platform operations (e.g. train, deploy, endpoint) described.	2 / 5
Completeness	The "what" is stated (manage data, records, automate workflows) and a "Use when..." trigger clause is present, but the trigger is generic ("interact with Google Cloud AI Platform data") and lacks concrete triggering conditions, so it does not clearly hit the explicit-when bar for a 4.	3 / 5
Trigger Term Quality	"Google Cloud AI Platform data" and "interact with Google Cloud AI Platform" provide the natural product name users would say, but there are no synonyms, file extensions, or common task phrasings (e.g. "train a model", "deploy an endpoint").	3 / 5
Distinctiveness Conflict Risk	The product name "Google Cloud AI Platform" gives it a clear niche distinct from other skills, though the generic "data/records/workflows" phrasing leaves minor overlap risk with other Membrane integration skills.	4 / 5
	Total	12 / 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: membranedev/application-skills
Path: skills/google-cloud-ai-platform/SKILL.md
Commit: f484c82

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.