vertex-ai-pipeline-creator
Vertex Ai Pipeline Creator - Auto-activating skill for GCP Skills. Triggers on: vertex ai pipeline creator, vertex ai pipeline creator Part of the GCP Skills skill category.
35
3%
Does it follow best practices?
Impact
91%
1.03xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/14-gcp-skills/vertex-ai-pipeline-creator/SKILL.mdQuality
Discovery
7%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is essentially a placeholder that provides almost no useful information for skill selection. It relies entirely on the skill name without explaining capabilities, use cases, or meaningful trigger terms. Claude would struggle to know when to select this skill over other GCP or ML-related skills.
Suggestions
Add specific actions the skill performs, e.g., 'Creates and configures Vertex AI Pipelines for ML workflows, defines pipeline components, sets up training and deployment stages, configures compute resources'
Include a 'Use when...' clause with natural trigger terms like 'ML pipeline', 'Kubeflow', 'training workflow', 'model deployment pipeline', 'Vertex AI workflow', 'GCP machine learning orchestration'
Differentiate from other GCP skills by specifying the exact scope - does it handle only pipeline creation, or also monitoring, debugging, or template management?
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the skill ('Vertex Ai Pipeline Creator') without describing any concrete actions. There are no verbs or specific capabilities listed - it doesn't explain what creating a pipeline actually involves. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and provides no 'when should Claude use it' guidance. The 'Triggers on' section just repeats the skill name rather than providing meaningful trigger scenarios. | 1 / 3 |
Trigger Term Quality | The trigger terms are just the skill name repeated twice ('vertex ai pipeline creator'). Missing natural variations users might say like 'ML pipeline', 'Kubeflow', 'training pipeline', 'workflow orchestration', or 'GCP ML workflow'. | 1 / 3 |
Distinctiveness Conflict Risk | The mention of 'Vertex AI' and 'GCP' provides some specificity to Google Cloud's ML platform, which helps distinguish it from generic pipeline tools. However, without describing what aspects of pipeline creation it handles, it could conflict with other GCP or ML-related skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is essentially a placeholder with no substantive content. It describes what a Vertex AI pipeline creator skill should do but provides absolutely no actual guidance, code examples, or workflows for creating pipelines. The entire content could be replaced with actual Kubeflow/Vertex AI pipeline SDK examples and would be infinitely more useful.
Suggestions
Add executable Python code examples using the Vertex AI Pipelines SDK (kfp) showing how to define components and compile pipelines
Include a clear workflow: 1) Define components, 2) Create pipeline function, 3) Compile to JSON, 4) Submit to Vertex AI with validation steps
Remove all generic boilerplate ('provides automated assistance', 'follows best practices') and replace with specific Vertex AI pipeline patterns
Add references to component types (container components, Python function components) and link to example files for common pipeline patterns
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that explains nothing Claude doesn't already know. Phrases like 'provides automated assistance' and 'follows industry best practices' are meaningless filler with no actual information about Vertex AI pipelines. | 1 / 3 |
Actionability | There is zero concrete guidance - no code, no commands, no specific steps for creating Vertex AI pipelines. The content only describes what the skill claims to do without actually providing any executable instructions. | 1 / 3 |
Workflow Clarity | No workflow is defined at all. For a 'pipeline creator' skill, there should be clear steps for defining components, compiling pipelines, and submitting to Vertex AI, but none exist. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of vague descriptions with no references to detailed documentation, examples, or related files. There's no structure that would help navigate to actual implementation details. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 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 | 9 / 11 Passed | |
- Commit
b8a3b3e
- Reviewed
Table of Contents
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.