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Agent Skills/NVIDIA NeMo Retriever
NVIDIADocsSKILL.mdLicense identified

Agent Skill

NVIDIA NeMo Retriever

Index and query multi-file document corpora with the NeMo Retriever CLI.

Install this skillView repository

Vendor-authored source · Apache-2.0 AND CC-BY-4.0 license.

Source snapshot: 2026-09-04. This listing does not verify installation, security, vendor participation, or product use.

Raw SKILL.mdInstall the Tokens& Agent Pack

Skill specification

Declared by NVIDIA in the package front matter. Trigger conditions are what the coding agent matches on before it loads the skill.

View package fields
NVIDIA NeMo Retriever SKILL.md front matter fields
Skill namenemo-retriever
Trigger conditionsUse 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.
Allowed toolsBash Write Read
Declared licenseApache-2.0

Install nemo-retriever

In a terminal with Node.js, npm and Git, run the command for your agent. The Skills CLI installs the complete package directory, including referenced files within it. Review its install prompt, then start a new agent session. A skill package does not set up an MCP server connection.

Claude Code

.claude/skills/nemo-retriever/SKILL.md

Project skills are committed with the repo. Use the user directory for a personal install across every project.

Project install

npx skills add 'https://github.com/NVIDIA/skills/tree/main/skills/nemo-retriever' --skill 'nemo-retriever' --agent 'claude-code'
Install for all projects instead

Personal install

npx skills add 'https://github.com/NVIDIA/skills/tree/main/skills/nemo-retriever' --skill 'nemo-retriever' --agent 'claude-code' --global

Codex

.agents/skills/nemo-retriever/SKILL.md

Codex reads `.agents/skills/` as its primary location, which is also the cross-platform default other clients honour.

Project install

npx skills add 'https://github.com/NVIDIA/skills/tree/main/skills/nemo-retriever' --skill 'nemo-retriever' --agent 'codex'
Install for all projects instead

Personal install

npx skills add 'https://github.com/NVIDIA/skills/tree/main/skills/nemo-retriever' --skill 'nemo-retriever' --agent 'codex' --global

Cursor

.agents/skills/nemo-retriever/SKILL.md

Cursor also loads `.agents/skills/`, `.claude/skills/`, and `.codex/skills/`, so one committed copy can serve several clients.

Project install

npx skills add 'https://github.com/NVIDIA/skills/tree/main/skills/nemo-retriever' --skill 'nemo-retriever' --agent 'cursor'
Install for all projects instead

Personal install

npx skills add 'https://github.com/NVIDIA/skills/tree/main/skills/nemo-retriever' --skill 'nemo-retriever' --agent 'cursor' --global

SKILL.md

View raw source

Source snapshot fetched 2026-09-04 from github.com/NVIDIA/skills/tree/main/skills/nemo-retriever. The install command fetches the upstream package, which may have changed since this snapshot.

Read full skill instructions

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 typeRead this onceThen execute
Setup turn (first turn — ./lancedb/nv-ingest.lance doesn't exist)references/setup.mdBuild the index
Query turn (every subsequent turn — user asks a question)references/query.mdOne retriever query call
Anything errored or returned emptyreferences/troubleshooting.mdApply 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.

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