bigquery-ml-model-creator
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill bigquery-ml-model-creatorBigquery Ml Model Creator - Auto-activating skill for GCP Skills. Triggers on: bigquery ml model creator, bigquery ml model creator Part of the GCP Skills skill category.
Overall
score
19%
Does it follow best practices?
Validation for skill structure
Activation
7%This description is severely underdeveloped, essentially just restating the skill name without explaining capabilities or usage triggers. It provides no actionable information for Claude to determine when to select this skill over others, and the duplicate trigger term suggests a copy-paste error.
Suggestions
Add specific actions the skill performs, e.g., 'Creates and trains machine learning models directly in BigQuery, including classification, regression, clustering, and forecasting models.'
Add a 'Use when...' clause with natural trigger terms like 'Use when the user wants to create ML models in BigQuery, train predictive models on BigQuery data, or use BQML for machine learning tasks.'
Include common user phrases and variations: 'BigQuery ML', 'BQML', 'train model in BigQuery', 'ML predictions', 'CREATE MODEL statement', 'GCP machine learning'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only states 'Bigquery Ml Model Creator' without describing any concrete actions. There are no specific capabilities listed like 'create ML models', 'train models', 'deploy predictions', etc. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and has no 'Use when...' clause or explicit guidance on when Claude should select this skill. | 1 / 3 |
Trigger Term Quality | The trigger terms are just the skill name repeated twice ('bigquery ml model creator, bigquery ml model creator'). Missing natural user terms like 'machine learning', 'ML model', 'BigQuery', 'train model', 'predictions', 'GCP ML'. | 1 / 3 |
Distinctiveness Conflict Risk | While 'BigQuery ML' is a specific GCP service which provides some distinctiveness, the lack of detail about what operations it performs could cause confusion with other GCP or ML-related skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%This skill is an empty template that provides no actual guidance on BigQuery ML model creation. It contains only generic boilerplate text describing what the skill claims to do without any concrete instructions, code examples, or actionable content. The skill would be completely useless for actually helping someone create ML models in BigQuery.
Suggestions
Add concrete SQL examples showing CREATE MODEL syntax for common model types (linear regression, logistic regression, k-means, etc.)
Include a clear workflow: 1) Prepare training data, 2) Choose model type, 3) Create and train model, 4) Evaluate with ML.EVALUATE, 5) Make predictions with ML.PREDICT
Provide specific BigQuery ML function references (ML.EVALUATE, ML.PREDICT, ML.FEATURE_INFO) with usage examples
Add validation steps showing how to check model performance metrics and common troubleshooting for training failures
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that provides no actual information about BigQuery ML model creation. Phrases like 'provides automated assistance' and 'follows industry best practices' are meaningless filler that waste tokens. | 1 / 3 |
Actionability | There is zero concrete guidance - no SQL examples, no CREATE MODEL syntax, no specific BigQuery ML commands, no code whatsoever. The skill describes what it claims to do rather than actually instructing how to do it. | 1 / 3 |
Workflow Clarity | No workflow is provided at all. Creating ML models in BigQuery involves specific steps (data preparation, model selection, training, evaluation, prediction) but none are mentioned or sequenced. | 1 / 3 |
Progressive Disclosure | The content is a shallow placeholder with no actual substance to organize. There are no references to detailed documentation, no links to examples, and no structured navigation to deeper content. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
69%Validation — 11 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') | Warning |
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
body_steps | No step-by-step structure detected (no ordered list); consider adding a simple workflow | Warning |
Total | 11 / 16 Passed | |
Reviewed
Table of Contents
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