rag-pipeline-starter@1.0.1
VERIFIED· install onlyPublisher claims: "Set up and optimize RAG pipelines for large datasets (50K-500K rows) with document chunking, embedding benchmarking, vector indexing, and retrieval tuning." Observed in sandbox: no network, touches nothing outside the project, writes no memory.
Coverage
Nothing executable in the bundle ran; the trace covers the install step only.- Tested
- every file read, file written and host contacted by what ran
- Not tested
- use of the skill by an agent
Is [email protected] safe to install?
KillerSkills ran it in the KillerSkills honeypot sandbox (1 scenario; nothing executable in the bundle ran; the trace covers the install step only) on 2026-11-14 and scored it 91/100 (Verified). In what ran, nothing we could detect went wrong: no undeclared network egress, no credential reads, no persistent instruction writes. What it does with a real credential was not observed; the static findings and the publisher carry the rest of the score. Summary: no network, touches nothing outside the project, writes no memory.
Behavior trace
Honeypot run · 0 s · 1 scenarios · 0 deviationsStatic findings
python chunking_analyzer.py --strategy recursive --input ./data/doc.txt --output ./chunks/ --chunk-size 500 --overlap 50Fix: Remove the call, or declare the host in frontmatter and explain in the README what is sent and why.python retrieval_tuner.py --index ./vector_store/ --queries ./test_queries.json --output tuning_results.jsonFix: Remove the call, or declare the host in frontmatter and explain in the README what is sent and why.Cost to the agent
Tokens estimated at four characters each. Skills load their instruction text when triggered; the figure is what that costs.
Known vulnerabilities
Vulnerability advisories (OSV) cover npm and PyPI packages; this registry has no advisory database.