dask
Pass
Audited by Gen Agent Trust Hub on Jun 27, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill's core purpose is providing technical guidance on Dask DataFrames, Arrays, Bags, and Futures. All code examples use standard APIs for distributed computing and do not include malicious commands or unauthorized file access patterns.
- [SAFE]: Data ingestion methods described in the reference files (e.g.,
dd.read_csv,dd.read_parquet,db.read_text) target generic data paths likedata/*.csvorlogs/*.json. There are no attempts to access sensitive system files such as SSH keys or environment secrets. - [SAFE]: All identified dependencies are well-known, reputable packages within the Python data science ecosystem (e.g., dask, pandas, numpy, scikit-learn). No third-party scripts or binaries are downloaded from untrusted sources.
- [SAFE]: The analysis detected no obfuscation techniques, hidden URLs, or prompt injection patterns designed to bypass agent safety filters or override instructions.
- [SAFE]: The infrastructure examples (e.g.,
Client,SLURMCluster,KubeCluster) are standard configurations for connecting to local or managed distributed clusters and do not involve credential harvesting.
Audit Metadata