executing-spark
executing-spark is a Data warehousing & modelling skill for AI agents, published by data-goblin in the power-bi-agentic-development repository on GitHub. Skillspace rates executing-spark F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.
Risky. This skill has patterns associated with unsafe behaviour. Read the source carefully before running it.
Execute arbitrary Python or PySpark code on Fabric Spark compute without creating a notebook artifact; ephemeral Livy sessions with full Delta table access. Automatically invoke when the user asks to "run PySpark in Fabric", "create a Livy session", "execute Python on Fabric compute", "run Spark without a notebook", "submit code to Fabric", "ephemeral Spark execution", "run ETL in Fabric".
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 791
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since.
Our review
- Architecture
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- High-risk patterns
- License
- GPL-3.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- executes shell/subprocess
- mentions secrets in text
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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