looker-studio-bigquery
Design and configure Looker Studio dashboards with BigQuery data sources. Use when creating analytics dashboards, connecting BigQuery to visualization tools, or optimizing data pipeline performance. Handles BigQuery connections, custom SQL queries, scheduled queries, dashboard design, and performance optimization.
86
82%
Does it follow best practices?
Impact
90%
1.07xAverage score across 3 eval scenarios
Passed
No known issues
Quality
Discovery
100%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 is a well-crafted skill description that excels across all dimensions. It provides specific capabilities, includes natural trigger terms users would actually use, explicitly states both what the skill does and when to use it, and carves out a distinct niche by focusing on the Looker Studio + BigQuery combination.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Design and configure Looker Studio dashboards', 'BigQuery connections', 'custom SQL queries', 'scheduled queries', 'dashboard design', and 'performance optimization'. | 3 / 3 |
Completeness | Clearly answers both what ('Design and configure Looker Studio dashboards with BigQuery data sources', 'Handles BigQuery connections, custom SQL queries...') AND when ('Use when creating analytics dashboards, connecting BigQuery to visualization tools, or optimizing data pipeline performance'). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'Looker Studio', 'dashboards', 'BigQuery', 'analytics dashboards', 'visualization tools', 'data pipeline', 'SQL queries'. Good coverage of domain-specific terms. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche combining Looker Studio + BigQuery specifically. The combination of these two specific tools creates a distinct trigger profile unlikely to conflict with generic dashboard or database skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a comprehensive and highly actionable skill with excellent executable code examples for BigQuery and Looker Studio integration. The main weaknesses are verbosity (explaining concepts Claude knows), missing validation checkpoints for multi-step operations, and a monolithic structure that could benefit from progressive disclosure to separate files.
Suggestions
Add explicit validation steps after key operations (e.g., 'Verify scheduled query ran: check job history in BigQuery console' or 'Test data source connection before proceeding')
Remove explanatory text about basic concepts (F-pattern reading flow, what IAM roles do) and trust Claude's existing knowledge
Split advanced sections (Community Connector development, cohort analysis examples) into separate referenced files to reduce main skill length
Add error recovery guidance for common failure scenarios (e.g., permission denied, query timeout, data source connection failures)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is comprehensive but includes some unnecessary explanations (e.g., explaining what F-pattern is, basic IAM concepts). The content could be tightened by removing explanatory text Claude already knows and focusing purely on the actionable steps. | 2 / 3 |
Actionability | Provides fully executable SQL queries, bash commands, and concrete code examples throughout. The BigQuery setup, scheduled queries, and dashboard configuration steps are copy-paste ready with specific syntax and real examples. | 3 / 3 |
Workflow Clarity | Steps are clearly numbered and sequenced (Steps 1-8), but validation checkpoints are largely missing. For operations like scheduled queries and data pipeline setup, there are no explicit 'verify this worked' steps or error recovery guidance. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections, but it's a monolithic document (~400 lines) that could benefit from splitting advanced topics (Community Connectors, cohort analysis) into separate files. References section exists but points only to external docs, not internal skill files. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
Total | 10 / 11 Passed | |
- Repository
- supercent-io/skills-template
- Commit
c033769
- Reviewed
Table of Contents
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