Real file from a public repo · synced Sep 3, 2026
rag-eval
Guide agents through NVIDIA RAG Blueprint filesystem benchmarks: preparing corpus/ and train.json, running scripts/eval/evaluate_rag.py, tuning retrieval and generation flags for quality comparisons, interpreting RAGAS JSON outputs, and triaging failures (HTTP/stream errors, empty contexts,…
Works with
Install in three steps
- 1
Download the ZIP
One file per agent, plus INSTALL.md with the exact paths below.
- 2
Claude Code: copy SKILL.md into your skills folder
.claude/skills/rag-eval/SKILL.md # this project ~/.claude/skills/rag-eval/SKILL.md # every project
- 3
Other agents: use the matching file
skill.mdc goes in Cursor’s .cursor/rules/. AGENTS.md works as GitHub Copilot instructions, a legacy .cursorrules, or a Codex / Gemini CLI instructions file.

