Dbt
dbt data transformation with SQL. Use for data pipelines.
Install
$ agentstack add skill-g1joshi-agent-skills-dbt ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
dbt (Data Build Tool)
dbt manages data transformation in the warehouse using SQL. v2.0 introduces the Fusion Engine (Rust) for performance.
When to Use
- Data Modeling: Converting raw tables into "Gold" tables.
- Testing:
not_null,uniquetests defined in YAML. - Documentation: Auto-generating data dictionaries.
Core Concepts
Models (.sql)
Select statements that dbt compiles into CREATE VIEW/TABLE.
Refs ({{ ref('users') }})
Dependency management. dbt builds the DAG automatically.
Semantic Layer
Defining metrics ("Revenue") in code so all BI tools use the same definition.
Best Practices (2025)
Do:
- Use Git: Treat data models like software code.
- Use Incremental Models: Only process new data to save cost.
- Use dbt Mesh: For cross-project dependencies in large orgs.
Don't:
- Don't put logic in BI tools: Put it in dbt.
References
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: G1Joshi
- Source: G1Joshi/Agent-Skills
- License: MIT
- Homepage: https://skills.sh/g1joshi/agent-skills
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.