Agent skill · Backend & API

aiq-research

Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.

NVIDIAgithub.com/NVIDIAGitHub ↗
claude-codecodexcan modify filesships scriptsApache-2.0
Install
npx skills add NVIDIA/skills --skill aiq-research --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 7
SKILL.md size: 16 KB
Bundled scripts: yes
Version: 2.1.0
Declared author: NVIDIA AI-Q Blueprint Team <aiq-blueprint@nvidia.com>
Allowed tools: ReadBash
Requires: | Designed for Claude Code, OpenCode, Codex, and Agent Skills-compatible tools. Requires Python 3.11+ and network…
Path: skills/aiq-research/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,789
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# AIQ Research Skill ## Purpose Use this skill to call a locally running NVIDIA AI-Q Blueprint server through the helper script at `scripts/aiq.py`. Use this skill for research-shaped requests, including: - "deep research on ..." - "AIQ research ..." - "research ..." - "use AI-Q to answer ..." - "ask AI-Q about ..." Do not use this skill for install, deploy, start, stop, UI, CLI, Docker, Helm, or

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About this skill
What does the aiq-research skill do?

Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.

How do I install it?

Run `npx skills add NVIDIA/skills --skill aiq-research --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From NVIDIA/skills, a repository with 2,789 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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