KS
Killer-Skills

new-dagster-asset — how to use new-dagster-asset how to use new-dagster-asset, new-dagster-asset setup guide, what is new-dagster-asset, new-dagster-asset alternative, new-dagster-asset vs dagster, new-dagster-asset install, dagster asset management, python dagster integration, nephila ai agent

v1.0.0
GitHub

About this Skill

Perfect for Python-based AI Agents needing advanced workflow management and data pipeline capabilities with Dagster new-dagster-asset is a skill that enables the addition of new Dagster assets, leveraging Python decorators and PipelineSettings for efficient workflow management.

Features

Declares assets using Python decorators with @asset
Utilizes PipelineSettings for customized workflow management
Follows a specific file naming convention, <type>_<function>.py
Supports dependency declaration with deps=["<upstream_asset>"]
Adds output metadata with context.add_output_metadata
Chooses layer files from asset_bronze.py, asset_silver.py, or asset_gold.py

# Core Topics

spideystreet spideystreet
[3]
[0]
Updated: 2/27/2026

Quality Score

Top 5%
33
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add spideystreet/nephila/new-dagster-asset

Agent Capability Analysis

The new-dagster-asset MCP Server by spideystreet is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use new-dagster-asset, new-dagster-asset setup guide, what is new-dagster-asset.

Ideal Agent Persona

Perfect for Python-based AI Agents needing advanced workflow management and data pipeline capabilities with Dagster

Core Value

Empowers agents to declare and manage Dagster assets using Python, leveraging PipelineSettings for efficient data processing and asset dependencies, while utilizing asset layers such as bronze, silver, or gold

Capabilities Granted for new-dagster-asset MCP Server

Declaring new Dagster assets for pharmacists to navigate drug shortages
Managing asset dependencies with upstream assets
Utilizing PipelineSettings for optimized data pipeline configuration

! Prerequisites & Limits

  • Requires Python environment
  • Dagster installation and configuration needed
  • Limited to Dagster asset management
Project
SKILL.md
943 B
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

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SKILL.md
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Skill: Add a New Dagster Asset

Steps

  1. Choose the layer file: asset_bronze.py, asset_silver.py, or asset_gold.py.

  2. Declare the asset:

    python
    1@asset(group_name="<layer>", deps=["<upstream_asset>"]) 2def <asset_name>(context: AssetExecutionContext) -> None: 3 """One-line description.""" 4 settings = PipelineSettings() 5 # ... logic 6 context.add_output_metadata({"key": "value"})
  3. File naming: follow <type>_<function>.py for any new utility files.

  4. Resources (e.g. DbtCliResource): declare in function signature, already registered in definitions.py.

  5. Register: load_assets_from_modules in definitions.py picks up the asset automatically if it's in the right module.

  6. Validate:

    bash
    1uv run dotenv -f .env run -- uv run dagster asset list 2uv run dotenv -f .env run -- uv run dagster asset materialize --select <asset_name>

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