NotebookLM Research Assistant
PleasePrompto/notebooklm-skill
Lets Claude Code ask questions of your Google NotebookLM notebooks through browser automation and return answers grounded in your uploaded sources.
Agent skill
Deep Researcher Add Data Source
by NVIDIA-AI-Blueprints in NVIDIA-AI-Blueprints/deep-researcher-agent
A skill your agent uses when adding or changing an Deep Researcher Agent data source under sources/, registering it as a NeMo Agent Toolkit function, wiring it into the datasourceregistry for UI…
Apache-2.0Auto-check: notes
Install Deep Researcher Add Data Source
$ npx skills add NVIDIA-AI-Blueprints/deep-researcher-agent --skill deep-researcher-add-data-source -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA-AI-Blueprints/deep-researcher-agent deep-researcher-add-data-source --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/deep-researcher-add-data-source .claude/skills/deep-researcher-add-data-source && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "deep-researcher-add-data-source" agent skill from https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent/tree/develop/.agents/skills/deep-researcher-add-data-source into .claude/skills/deep-researcher-add-data-source/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-researcher-add-data-source", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent/tree/develop/.agents/skills/deep-researcher-add-data-sourceType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NVIDIA-AI-Blueprints/deep-researcher-agent --skill deep-researcher-add-data-source -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA-AI-Blueprints/deep-researcher-agent deep-researcher-add-data-source --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/deep-researcher-add-data-source .agents/skills/deep-researcher-add-data-source && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "deep-researcher-add-data-source" agent skill from https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent/tree/develop/.agents/skills/deep-researcher-add-data-source into .agents/skills/deep-researcher-add-data-source/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-researcher-add-data-source", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA-AI-Blueprints/deep-researcher-agent --skill deep-researcher-add-data-source -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA-AI-Blueprints/deep-researcher-agent deep-researcher-add-data-source --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/deep-researcher-add-data-source .cursor/skills/deep-researcher-add-data-source && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "deep-researcher-add-data-source" agent skill from https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent/tree/develop/.agents/skills/deep-researcher-add-data-source into .cursor/skills/deep-researcher-add-data-source/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-researcher-add-data-source", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent.git --path .agents/skills/deep-researcher-add-data-source--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA-AI-Blueprints/deep-researcher-agent --skill deep-researcher-add-data-source -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA-AI-Blueprints/deep-researcher-agent deep-researcher-add-data-source --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/deep-researcher-add-data-source .gemini/skills/deep-researcher-add-data-source && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "deep-researcher-add-data-source" agent skill from https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent/tree/develop/.agents/skills/deep-researcher-add-data-source into .gemini/skills/deep-researcher-add-data-source/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-researcher-add-data-source", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NVIDIA-AI-Blueprints/deep-researcher-agent deep-researcher-add-data-sourceInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NVIDIA-AI-Blueprints/deep-researcher-agent --skill deep-researcher-add-data-source -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/deep-researcher-add-data-source .github/skills/deep-researcher-add-data-source && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "deep-researcher-add-data-source" agent skill from https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent/tree/develop/.agents/skills/deep-researcher-add-data-source into .github/skills/deep-researcher-add-data-source/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-researcher-add-data-source", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA-AI-Blueprints/deep-researcher-agent --skill deep-researcher-add-data-source -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA-AI-Blueprints/deep-researcher-agent deep-researcher-add-data-source --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/deep-researcher-add-data-source .opencode/skills/deep-researcher-add-data-source && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "deep-researcher-add-data-source" agent skill from https://github.com/NVIDIA-AI-Blueprints/deep-researcher-agent/tree/develop/.agents/skills/deep-researcher-add-data-source into .opencode/skills/deep-researcher-add-data-source/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-researcher-add-data-source", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
deep-researcher-add-data-source- GitHub stars
- 886
- Token cost
- ~1.1k tokens
- SKILL.md length
- 426 words
- Files
- 4 (incl. references)
- Skills in repo
- 15
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
A skill your agent uses when adding or changing an Deep Researcher Agent data source under sources/, registering it as a NeMo Agent Toolkit function, wiring it into the datasourceregistry for UI…
- Works in 7 steps: Pick the closest existing package under… → Create sources// with src/register.py,… → Define a FunctionBaseConfig subclass… → …
- Changing an Deep Researcher Agent data source under sources/
- SKILL.md covers Start Here, Authoritative References, Workflow and Validation, plus 2 more sections
- Calls uv
What it does
Deep Researcher Add Data Source is an agent skill from NVIDIA-AI-Blueprints/deep-researcher-agent. Use when adding or changing an Deep Researcher Agent data source under sources/, registering it as a NeMo Agent Toolkit function, wiring it into the datasourceregistry for UI toggles, or validating retrieval behavior with tests.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/package-layout.md`, `references/registry-and-ui.md` and `references/validation.md`). Compatibility notes: Claude Code, Codex, Cursor, OpenCode, and Agent Skills-compatible tools.
The repository describes itself as: The NVIDIA Deep Researcher Agent Blueprint is an open reference example for building intelligent AI agents that connect to your enterprise data, reason using state-of-the-art… The licence is Apache-2.0.
When your agent uses it
- Changing an Deep Researcher Agent data source under sources/
- Registering it as a NeMo Agent Toolkit function
- Wiring it into the datasourceregistry for UI toggles
- Validating retrieval behavior with tests
Example prompts
- “/deep-researcher-add-data-source”
Requirements
- Python 3
- Compatibility (from SKILL.md): Claude Code, Codex, Cursor, OpenCode, and Agent Skills-compatible tools.
- Pre-approved tools (allowed-tools): Read, Bash, Edit
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Pick the closest existing package under sources/ and inspect its layout.
- Create sources// with src/register.py, the client
- Define a FunctionBaseConfig subclass with a stable name= and resolve any
- Yield a graceful stub when the required secret is missing.
- Install the package editable and add it to the data_source_registry in the
- Add focused tests; run the validation commands below.
- Summarize changed files and paste the test/lint evidence.
What it can do on your machine
Read from SKILL.md and the folder at commit 951a1a1. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadBashEdit
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
uv
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Compatibility
Claude Code, Codex, Cursor, OpenCode, and Agent Skills-compatible tools.
From compatibility in the SKILL.md frontmatter.
Context cost
Deep Researcher Add Data Source loads about 1.1k tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 66 tokens; SKILL.md has 426 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Read, Bash, Edit
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from NVIDIA-AI-Blueprints/deep-researcher-agent at commit 951a1a1, republished under its Apache-2.0 licence (© NVIDIA-AI-Blueprints). 426 words, ~1,092 tokens.
Download SKILL.mdSave it as
.claude/skills/deep-researcher-add-data-source/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- deep-researcher-add-data-source
- description
- Use when adding or changing an Deep Researcher Agent data source under sources/, registering it as a NeMo Agent Toolkit function, wiring it into the data_source_registry for UI toggles, or validating retrieval behavior with tests.
- allowed-tools
- Read, Bash, Edit
- compatibility
- Claude Code, Codex, Cursor, OpenCode, and Agent Skills-compatible tools.
- license
- Apache-2.0
- metadata.version
- 0.1.0
- metadata.source-repo
- NVIDIA-AI-Blueprints/deep-researcher-agent
- metadata.tags
- deep-researcher nemo-agent-toolkit data-source sources registry
Add an Deep Researcher Agent Data Source
Use this skill when a developer wants to add a retrieval or search source to
Deep Researcher Agent and expose it as a toggleable source in the UI. A data source is a NeMo
Agent Toolkit (NAT) function package under sources/, registered in the
data_source_registry.
Start Here
- Confirm this is a new retrieval/search source (not a UI, auth, or prompt
change). For a general utility function, use
deep-researcher-add-toolinstead. - Read the authoritative files below before editing.
- Copy the closest existing source package rather than inventing a new shape.
- Never print or commit API keys; resolve secrets at runtime via
SecretStr.
Authoritative References
docs/source/extending/adding-a-data-source.md: canonical package and registration walkthrough (the steps below mirror it).sources/google_scholar_paper_search/: complete example package with a client, a config + registration, a graceful missing-secret stub, and tests.sources/tavily_web_search/: minimal source package for comparison.src/deep_researcher_agent/common/data_source_registry.py: thedata_source_registryconfig (name="data_source_registry") that drivesGET /v1/data_sources.docs/source/customization/tools-and-sources.md: how the registry maps to UI toggles and per-request filtering.frontends/ui/src/features/layout/data-sources.ts: the UIDataSourcetype; sources are fetched dynamically, so usually no UI code change is needed.
Longer procedures live in this bundle:
- references/package-layout.md: package files,
pyproject.toml, config class,@register_function, and the missing-secret stub. - references/registry-and-ui.md: registering in YAML and how the registry surfaces toggles and filtering.
- references/validation.md: install, test, and lint commands with expected results.
Show full SKILL.md (209 more words)Show less
Workflow
- Pick the closest existing package under
sources/and inspect its layout. - Create
sources/<my_data_source>/withsrc/register.py, the client module,pyproject.toml, andtests/(see package-layout reference). - Define a
FunctionBaseConfigsubclass with a stablename=and resolve any API key viaSecretStr; register it with@register_function. - Yield a graceful stub when the required secret is missing.
- Install the package editable and add it to the
data_source_registryin the relevant config underconfigs/. - Add focused tests; run the validation commands below.
- Summarize changed files and paste the test/lint evidence.
Validation
Run the narrowest commands first; broaden only if the change touches shared code.
uv pip install -e ./sources/my_data_source
uv run pytest sources/my_data_source/tests
uv run ruff check sources/my_data_source
uv run ruff format --check sources/my_data_sourceExpected: the package installs, its tests pass, and Ruff reports no lint or format failures for the new source package.
Common Mistakes
- Forgetting to add the source to the
data_source_registry, so the UI cannot toggle it and agents do not inherit the tool. - Omitting the
[project.entry-points."nat.plugins"]entry inpyproject.toml, so NAT never discovers the registration. - Crashing on a missing API key instead of yielding a stub that returns a clear error message.
- Returning unstructured or citation-poor output, which weakens report grounding.
- Printing API keys or embedding secrets in YAML instead of using environment
variables or
SecretStr.
Related Skills
deep-researcher-configure-workflowdeep-researcher-add-tooldeep-researcher-release-qadeep-researcher-prepare-pr
© NVIDIA-AI-Blueprints, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (references) in .agents/skills/deep-researcher-add-data-source of NVIDIA-AI-Blueprints/deep-researcher-agent.
- SKILL.md
- references/package-layout.md
- references/registry-and-ui.md
- references/validation.md
Open the folder on GitHubat commit 951a1a1
Compare with similar skills
Deep Researcher Add Data Source next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Deep Researcher Add Data Source this skillNVIDIA-AI-Blueprints/deep-researcher-agent | 886 | — | ~1.1k | Automated safety check: Notes | Apache-2.0 | |
| NotebookLM Research AssistantPleasePrompto/notebooklm-skill | 7.8k | 14 repos | ~2.4k | Automated safety check: Notes | MIT | |
| Hypothesis Generationspacering-net/codeg | 3.9k | 14 repos | ~3.6k | Automated safety check: Notes | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 84k | 4 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Nature Paper CardYuan1z0825/nature-skills | 47k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Agent ReachPanniantong/Agent-Reach | 95k | — | ~1.4k | Automated safety check: Pass | MIT |
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Questions about Deep Researcher Add Data Source
What does Deep Researcher Add Data Source do?
A skill your agent uses when adding or changing an Deep Researcher Agent data source under sources/, registering it as a NeMo Agent Toolkit function, wiring it into the datasourceregistry for UI…. Deep Researcher Add Data Source is an agent skill from NVIDIA-AI-Blueprints/deep-researcher-agent. Use when adding or changing an Deep Researcher Agent data source under sources/, registering it as a NeMo Agent Toolkit function, wiring it into the datasourceregistry for UI toggles, or validating retrieval behavior with tests.
When should I use Deep Researcher Add Data Source?
Deep Researcher Add Data Source fits situations like: changing an Deep Researcher Agent data source under sources/; registering it as a NeMo Agent Toolkit function; wiring it into the datasourceregistry for UI toggles; validating retrieval behavior with tests.
How do I install Deep Researcher Add Data Source in Claude Code?
Run `npx skills add NVIDIA-AI-Blueprints/deep-researcher-agent --skill deep-researcher-add-data-source -a claude-code`. Or copy the skill folder (.agents/skills/deep-researcher-add-data-source in NVIDIA-AI-Blueprints/deep-researcher-agent) into .claude/skills/deep-researcher-add-data-source in your project. Claude Code loads it when a task matches its description.
How do I install Deep Researcher Add Data Source in Codex?
Run `npx skills add NVIDIA-AI-Blueprints/deep-researcher-agent --skill deep-researcher-add-data-source -a codex`. Or copy the skill folder (.agents/skills/deep-researcher-add-data-source in NVIDIA-AI-Blueprints/deep-researcher-agent) into .agents/skills/deep-researcher-add-data-source in your project. Codex loads it when a task matches its description.
Can I use Deep Researcher Add Data Source in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA-AI-Blueprints/deep-researcher-agent --skill deep-researcher-add-data-source -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deep-researcher-add-data-source, .gemini/skills/deep-researcher-add-data-source, .github/skills/deep-researcher-add-data-source and .opencode/skills/deep-researcher-add-data-source in your project.
What does Deep Researcher Add Data Source need to run?
Going by SKILL.md and its folder, Deep Researcher Add Data Source needs the command-line tools its instructions call (uv). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Bash, Edit. Compatibility (from SKILL.md): Claude Code, Codex, Cursor, OpenCode, and Agent Skills-compatible tools..
Does Deep Researcher Add Data Source access the network?
SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Deep Researcher Add Data Source safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Deep Researcher Add Data Source use?
Deep Researcher Add Data Source is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Deep Researcher Add Data Source use?
About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.9k tokens, read only when the agent opens those files.
What are the alternatives to Deep Researcher Add Data Source?
Skills that share tags, products or a category with Deep Researcher Add Data Source: NotebookLM Research Assistant (PleasePrompto/notebooklm-skill, 7.8k stars), Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars) and Nature Paper Card (Yuan1z0825/nature-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Deep Researcher Add Data Source?
NVIDIA-AI-Blueprints (a GitHub organization) maintains it in NVIDIA-AI-Blueprints/deep-researcher-agent, which has 886 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 9, 2026.
Source: NVIDIA-AI-Blueprints/deep-researcher-agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.