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cosmos-dbt-core

Use when turning a dbt Core project into an Airflow DAG/TaskGroup using Astronomer Cosmos. Does not cover dbt Fusion. Before implementing, verify dbt engine, warehouse, Airflow version, execution environment, DAG vs TaskGroup, and manifest availability.

68

Quality

83%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

77%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a strong, highly actionable skill that provides a clear step-by-step implementation checklist for Cosmos + dbt Core integration. Its main strengths are the executable code examples at every step and the decision tables that map user constraints to configuration choices. The primary weakness is length—the body could be more concise by moving some of the longer code examples (especially Option C and operational extras) to referenced files, improving both conciseness and progressive disclosure.

Suggestions

Move Option C (individual operators example) and the 'Setting Dependencies on Individual Cosmos Tasks' section to a referenced file like 'reference/cosmos-advanced-patterns.md' to reduce body length.

Consider moving Appendix B (Operational Extras) to the referenced 'reference/cosmos-config.md' file, keeping the main skill focused on the core implementation workflow.

DimensionReasoningScore

Conciseness

The skill is generally efficient and avoids explaining basic concepts, but it's quite long (~300+ lines) with some redundancy. The three full DAG assembly examples (Options A, B, C) are verbose, and Option C in particular is very lengthy with an S3 check example that may not be needed for most users. Some tables repeat information that could be consolidated.

2 / 3

Actionability

Every step includes fully executable Python code with correct imports, concrete configuration objects, and copy-paste ready examples. The decision tables clearly map constraints to choices, and the code examples cover DbtDag, DbtTaskGroup, and individual operators with real-world patterns.

3 / 3

Workflow Clarity

The 8-step sequential workflow is clearly numbered and logically ordered from project config through assembly to safety checks. Step 8 provides an explicit validation checklist with specific items to verify before finalizing, and the 'Before starting' prerequisites establish clear preconditions. The decision tables at each step guide the user to the correct choice.

3 / 3

Progressive Disclosure

The skill references 'reference/cosmos-config.md' for detailed configuration in steps 3-6, which is good progressive disclosure, but no bundle files were provided to verify these references exist. The appendices appropriately separate secondary concerns, but the main body is still quite long—Option C's full operator example and the task dependency example could potentially be moved to reference files.

2 / 3

Total

10

/

12

Passed

Description

89%

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 strong, well-targeted description for a niche skill. It clearly identifies the specific use case (dbt Core → Airflow via Cosmos), includes explicit trigger guidance and exclusions, and uses domain-appropriate terminology. The main weakness is that it could list more concrete actions/capabilities beyond the high-level 'turning into a DAG/TaskGroup' framing.

Suggestions

Add 2-3 more specific concrete actions the skill performs, e.g., 'Configures DbtTaskGroup rendering, sets up profile connections, handles operator selection (Docker/Kubernetes/Local)' to improve specificity.

DimensionReasoningScore

Specificity

The description names the domain (dbt Core to Airflow DAG/TaskGroup using Astronomer Cosmos) and mentions some actions like verifying prerequisites, but it doesn't list multiple concrete actions beyond 'turning a dbt Core project into an Airflow DAG/TaskGroup'. The verification checklist adds some specificity but these are preconditions rather than capabilities.

2 / 3

Completeness

Clearly answers both 'what' (turning a dbt Core project into an Airflow DAG/TaskGroup using Astronomer Cosmos) and 'when' (explicit 'Use when' clause at the start). Also specifies what it does NOT cover (dbt Fusion), and lists prerequisite checks.

3 / 3

Trigger Term Quality

Includes strong natural keywords users would say: 'dbt Core', 'Airflow', 'DAG', 'TaskGroup', 'Astronomer Cosmos', 'manifest', 'dbt Fusion' (as exclusion). These are the exact terms a user working in this space would naturally use.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with a very specific niche: the intersection of dbt Core, Airflow, and Astronomer Cosmos. The explicit exclusion of dbt Fusion further reduces conflict risk. This is unlikely to be confused with generic dbt or Airflow skills.

3 / 3

Total

11

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
astronomer/agents
Reviewed

Table of Contents

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