Creates dbt models following project conventions. Use when working with dbt models for: (1) Creating new models (any layer - discovers project's naming conventions first) (2) Task mentions "create", "build", "add", "write", "new", or "implement" with model, table, or SQL (3) Modifying existing model logic, columns, joins, or transformations (4) Implementing a model from schema.yml specs or expected output requirements Discovers project conventions before writing. Runs dbt build (not just compile) to verify. --- # dbt Model Development **Read before you write. Build after you write. Verify your output.** ## Critical Rules 1. **ALWAYS run `dbt build`** after creating/modifying models - compile is NOT enough 2. **ALWAYS verify output** after build using `dbt show` - don't assume success 3. **If build fails 3+ times**, stop and reassess your entire approach ## Workflow ### 1. Understand the Task Requirements - What columns are needed? List them explicitly. - What is the grain of the table (one row per what)? - What calculations or aggregations are required? ### 2. Discover Project Conventions ```bash cat dbt_project.yml find models/ -name "*.sql" | head -20 ``` Read 2-3 existing models to learn naming, config, and SQL patterns. ### 3. Find Similar Models ```bash # Find models with similar purpose find models/ -name "*agg*.sql" -o -name "*fct_*.sql" | head -5 ```
Automatically generate dbt dimensional models from raw Snowflake tables. Use when: user wants to generate dbt models, shift left data modeling, automate dimensional modeling, create facts and dimensions from raw data, build a star schema from raw tables, or auto-generate dbt code. Triggers: generate dbt models, shift left, dimensional model, auto model, star schema from raw, dbt from iceberg, dbt from raw, one big table, OBT, wide table.
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Sort by downloads/likes/comments/updated to find higher-quality skills.
4. Which import methods are supported?
Upload archive: .zip / .skill (recommended)
Upload skills folder
Import from GitHub repository
Note: file size for all methods should be within 10MB.
5. How to use in Claude / Codex?
Typical paths (may vary by local setup):
Claude Code：~/.claude/skills/
Codex CLI：~/.codex/skills/
One SKILL.md can usually be reused across tools.
6. Can one skill be shared across tools?
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
7. Are these skills safe to use?
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
8. Why does it not work after import?
Most common reasons:
Wrong folder path or nested one level too deep
Invalid/incomplete SKILL.md fields or format
Dependencies missing (Python/Node/CLI)
Tool has not reloaded skills yet
9. Does SkillWink include duplicates/low-quality skills?
We try to avoid that. Use ranking + comments to surface better skills:
