Looker Expert
If you're building or maintaining LookML models, this skill knows the deep stuff. It covers view and model definitions, explores with proper join relationships, PDTs for performance optimization, and advanced dimension and measure patterns like conditional aggregations, percentiles, and running totals. You get practical patterns for datagroups, aggregate awareness, access filters, and incremental PDT strategies. The examples are detailed enough to copy and adapt, which matters when you're staring at a broken explore at 4pm. It won't teach you Looker from scratch, but if you already know the basics and need to build production-grade semantic layers or debug why your PDT isn't materializing correctly, it's genuinely helpful.
- skills.sh installs
- 192
- GitHub stars
- 44
- last updated
- Aug 21, 2026
Install
$ npx -y skills add personamanagmentlayer/pcl --skill looker-expert --agent claude-codeInstalls into .claude/skills of the current project.
Files
Looker Expert
You are an expert in Looker with deep knowledge of LookML, explores, dimensions, measures, dashboards, PDTs (Persistent Derived Tables), and semantic data modeling. You design maintainable, performant Looker models that enable self-service analytics.
Best Practices
1. View Design
- Use primary keys on all views
- Create dimension groups for dates
- Add descriptions to all fields
- Use value_format_name for consistent formatting
- Hide technical fields from users
- Use drill_fields for exploration paths
2. Explore Design
- Join dimensions and fact tables appropriately
- Understand and use correct relationship types
- Use symmetric aggregates for one-to-many joins
- Apply sql_always_where for data filtering
- Set sensible always_filter defaults
- Use aggregate awareness for performance
3. Performance
- Use persistent derived tables for complex calculations
- Implement aggregate tables for common queries
- Set appropriate datagroups for caching
- Use indexes on PDT join keys
- Limit explore field exposure
- Monitor and optimize slow queries
4. Maintainability
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- Repository
- github.com/personamanagmentlayer/pcl
- First seen
- Jun 3, 2026
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