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Data Engineering Data Driven Feature

Explore data engineering data driven feature as a data & databases workflow from sickn33/agentic-awesome-skills. Compare its source, maintenance and review signals before choosing it for your agent.

What it does

This source provides a task-specific instruction workflow for Data & databases. Its source file is linked below so you can inspect the exact procedure, tools and dependencies. A full editorial review has not been completed.

Best for

Exploring Data & databases workflows with an agent. Confirm that the source matches your task and environment.

Tradeoffs and requirements

The automated catalog record does not establish task performance or runtime safety. Check supporting scripts and external services in the source before use.

Unknown; inspect source requirements and supporting scripts.

Install from the source

First time installing a skill? Follow the walkthrough →

Inspect the pinned source snapshot and its supporting files first. The command selects this skill through the open-source skills CLI. Node.js and agent-specific setup may be required. Installation can download code. Catalog ingestion never executes skill instructions or install scripts.

npx skills add https://github.com/sickn33/agentic-awesome-skills/tree/6f819e34e3847c4a9a4715409ec4d76b0ad42bdb/skills/data-engineering-data-driven-feature --skill data-engineering-data-driven-feature

Review pinned skill folder ↗ · CLI documentation ↗

After source review, use npx skills check and npx skills update to inspect and apply upstream updates. Re-check changed instructions before running them.

Safety & review signals

Static review only. This is not a security audit or a guarantee of safety.

SKILL.md text only; scripts, dependencies and runtime behavior not audited.

No configured text patterns matched. Unmatched or concealed behavior can still exist.

Allowed tools declaration: Unknown. Runtime permissions and network behavior: Unknown.

AI Craft Pad Skill Score

79/100 · Metadata coverage 100% · Model 1.0

Scores summarize observable discovery signals. Popularity and repository activity apply to the whole repository. Unknown runtime safety earns no certification.

Documentation
100/100
100
Maintenance
100/100
100
License Clarity
100/100
100
Repository Health
100/100
100
Compatibility Evidence
80/100
80
Popularity
84/100
84
Originality
0/100
0
Static Safety
60/100
60
Read the formula and limits →

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