aidp-spark-debugging
aidp-spark-debugging is a Streaming & real-time data skill for AI agents, published by oracle-samples in the oracle-aidp-samples repository on GitHub. Skillspace rates aidp-spark-debugging D (67/100) and it passed the safety scan; the rating is based on static analysis only.
Diagnose slow or failed AIDP Spark work using cluster logs, metrics, and the Spark UI REST API. Use when a job/query is slow or failed, the user asks "why did this fail / why is it slow", or you need stage/task timings, skew, shuffle/spill, executor, or SQL-execution details. Lightweight triage — for deep performance tuning (skew/spill/shuffle/joins/AQE/Delta) use the `aidp-spark-optimization` skill.
- Grade
- D
- Quality
- 67 / 100
- Safety
- Passed
- GitHub stars
- 41
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, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- UPL-1.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- 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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