scala-data-engineering-on-jvm-runtimes — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited scala-data-engineering-on-jvm-runtimes (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Use this skill when Scala is the implementation language for distributed or streaming data systems. It helps agents manage build compatibility, packaging, JVM dependency issues, typed data models, serialization behavior, and runtime assumptions that often cause production failures long after code compiles.
Scala Spark jobsFlink, Kafka Streams, or JVM-native data processors in Scalasbt builds, shaded JARs, or runtime compatibilityDo not assume compile success means distributed runtime safety.
Include:
Scala versionChoose:
Decide:
sbt or other build surfaceCheck:
Require:
| Rationalization | Reality |
|---|---|
| "It compiles, so the job is fine." | Distributed classpath, serialization, and dependency issues often appear only at runtime. |
| "We can fix the JAR if deployment fails." | Packaging problems discovered at deploy time slow delivery and often hide deeper compatibility issues. |
| "A quick UDF is simpler." | Overusing UDFs can hide schema, optimizer, and performance problems in JVM data engines. |
Scala, engine, and connector versions are not pinned together intentionallyScala, and library compatibility is explicit~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.