bigquery-ml-model-creator
Bigquery 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.
34
Quality
3%
Does it follow best practices?
Impact
89%
0.98xAverage 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/bigquery-ml-model-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 severely underdeveloped, consisting mainly of the skill name and category metadata without any substantive content. It lacks concrete actions, natural trigger terms, and explicit guidance on when to use the skill. Claude would struggle to appropriately select this skill from a list of alternatives.
Suggestions
Add specific concrete actions the skill performs, e.g., 'Creates and trains machine learning models in BigQuery using SQL, including classification, regression, clustering, and forecasting models.'
Include a 'Use when...' clause with natural trigger terms like 'Use when the user wants to create ML models in BigQuery, train predictive models with SQL, or mentions BQML, BigQuery ML, or machine learning in GCP.'
Add common variations of terminology users might use: 'BigQuery ML', 'BQML', 'train model', 'machine learning', 'predictive analytics', 'CREATE MODEL statement'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only states 'Bigquery Ml Model Creator' without describing any concrete actions. There are no verbs or specific capabilities listed - it doesn't explain what creating a model involves or what operations are supported. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and has no 'Use when...' clause or equivalent guidance for when Claude should select this skill. Both what and when are essentially missing. | 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 variations users would say like 'create ML model', 'machine learning', 'train model', 'BigQuery ML', 'BQML', etc. | 1 / 3 |
Distinctiveness Conflict Risk | The mention of 'BigQuery ML' and 'model creator' provides some specificity to GCP's BigQuery ML service, but without describing actual capabilities, it could overlap with other ML or BigQuery-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 template with no actual content about BigQuery ML model creation. It contains only generic boilerplate describing what a skill could do, without any concrete SQL syntax, model types, training parameters, or workflow guidance. Claude would gain no actionable knowledge from this skill.
Suggestions
Add concrete CREATE MODEL SQL examples showing at least one model type (e.g., linear regression, logistic regression, or k-means clustering) with actual syntax
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 model options and hyperparameters for common use cases (classification, regression, clustering, forecasting)
Add validation steps showing how to check model performance metrics and common error patterns to avoid
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that provides no actual information about BigQuery ML model creation. It explains what the skill does in abstract terms without any concrete guidance, wasting tokens on meta-description rather than actionable content. | 1 / 3 |
Actionability | There is zero executable guidance - no SQL examples, no CREATE MODEL syntax, no specific BigQuery ML commands or configurations. The content only describes what it could do rather than providing any concrete instructions Claude could follow. | 1 / 3 |
Workflow Clarity | No workflow is defined at all. Creating ML models in BigQuery involves multiple steps (data preparation, model selection, training, evaluation, prediction) but none are mentioned, let alone sequenced with validation checkpoints. | 1 / 3 |
Progressive Disclosure | The content is a flat, uninformative structure with no references to detailed materials, no links to examples, schemas, or advanced topics. It mentions being part of 'GCP Skills' but provides no navigation to related resources. | 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
0c08951
- Reviewed
Table of Contents
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