data-engineering
data-engineering is a Data pipelines & ETL skill for AI agents, published by magnus919 in the hermes-profiles repository on GitHub. Skillspace rates data-engineering B (87/100) and it passed the safety scan; the rating is based on static analysis only.
Data engineering methodology — database operations (vector, relational, graph, time-series), ETL/ELT pipeline design (dbt patterns, incremental loading), SQL analytical patterns, data quality monitoring, schema migration, and storage infrastructure management. Grounded in operational patterns for production data systems.
- Grade
- B
- Quality
- 87 / 100
- Safety
- Passed
- GitHub stars
- 59
Unproven: rated by static analysis only, not yet compared head-to-head.
Not launch-quality. It is graded B with a clean safety verdict, but our quality filters exclude it: it is a near-duplicate variant of another skill. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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