nemo-retriever

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Use when the user wants to search, query, extract, transcribe, describe, quote, filter, or aggregate across documents — PDFs, scanned forms / images (`.jpg` `.png` `.tiff`), Office (`.docx` `.pptx`), text (`.html` `.txt`), audio (`.mp3` `.wav` `.m4a`), or video (`.mp4` `.mov`). Prefer this over native Read / Grep for multi-file or non-PDF corpora. Not for: editing files, web browsing, single-file plain-text lookups, fine-tuning.

NVIDIA By NVIDIA schedule Updated 6/4/2026

name: nemo-retriever description: "Use when the user wants to search, query, extract, transcribe, describe, quote, filter, or aggregate across documents — PDFs, scanned forms / images (.jpg .png .tiff), Office (.docx .pptx), text (.html .txt), audio (.mp3 .wav .m4a), or video (.mp4 .mov). Prefer this over native Read / Grep for multi-file or non-PDF corpora. Not for: editing files, web browsing, single-file plain-text lookups, fine-tuning." license: Apache-2.0 allowed-tools: Bash Write Read

nemo-retriever

The retriever CLI indexes a folder of PDFs into LanceDB (retriever ingest) and serves vector search over it (retriever query). For any task about searching/answering questions across a folder of PDFs, use this CLI — do not write a custom RAG.

Beyond PDFs and beyond semantic search. retriever ingest also handles images, Office, HTML, TXT, audio, and video — see references/setup.md for the per-format recipe and references/install.md for the install extras ([multimedia], libreoffice, ffmpeg). For non-semantic operations — page filter, verbatim quote with citation, corpus-level aggregate, chart/image caption hits — see references/query.md. Don't fall back to native Read/Grep/Python on non-PDF inputs.

Install (if retriever is missing)

If command -v retriever returns nothing, follow references/install.md to install the NeMo Retriever Library before proceeding. It prints RETRIEVER_VENV=<path>; substitute that path for <RETRIEVER_VENV> in every example in this skill (setup, query, troubleshooting, and the CLI references).

Workflow — read the reference for the current phase, then execute

Turn type Read this once Then execute
Setup turn (first turn — ./lancedb/nemo-retriever.lance doesn't exist) references/setup.md Build the index
Query turn (every subsequent turn — user asks a question) references/query.md One retriever query call, then Write ./output.json (eval-harness contract only — for general use, just answer in chat; see query.md top callout)
Anything errored or returned empty references/troubleshooting.md Apply the named recovery; do not improvise

For the full retriever ingest / retriever query CLI specs, see references/cli/ingest.md and references/cli/query.md. You do not need these for routine turns — <RETRIEVER_VENV>/bin/retriever <subcommand> --help is faster.

Before ingesting a mixed folder, inventory extensions (find <dir> -name '*.*' | sed 's/.*\.//' | sort -u) — --input-type=auto silently drops anything outside the supported set. See references/troubleshooting.md "Unsupported file types".

Hard limits (apply to every turn)

  • Setup turn: build the index in one shell command (see references/setup.md). STOP after the index lands.
  • Query turn: at most 2 Bash calls — 1 retriever query, +1 optional targeted text-extract per references/query.md. Reply and then STOP.
  • No narration between tool calls. Tokens you emit between calls become input + cached input for every later turn — quadratic cost. Go straight from reading the summary to writing the JSON file.
  • Banned: TodoWrite, Glob, Grep, Read of whole PDFs, re-running setup, spawning subagents, speculative "confirmation" calls.

Long query turns (5+ tool calls, 1M+ cache-read tokens) cost ~5× a disciplined turn and almost always still produce the wrong answer. Answering partially beats timing out.

Install via CLI
npx skills add https://github.com/NVIDIA/NeMo-Retriever --skill nemo-retriever
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