What is vss-build-vision-ai?

A self-contained computer-vision stack based on NVIDIA's VSS Blueprint that adds capabilities such as image description, object detection, visual search, alerts, and video summaries.

It helps developers add vision features to an agent or application and choose the capabilities they need.

It gives an agent or application a configurable way to interpret visual data instead of handling each vision task separately.

vss-build-vision-ai — Skill by NVIDIA-AI-Blueprints

About the project

NVIDIA AI Blueprint for Video Search and Summarization (VSS) is a reference architecture for applications that use AI to search, analyze, question, and summarize live or recorded video. It is intended for building video analytics agents with vision-language models, language models, retrieval-augmented generation, and NVIDIA NIM microservices. The catalogue entries provide coding-agent rules, skills, commands, agents, instructions, and settings associated with the project.

NVIDIA-AI-Blueprints/video-search-and-summarization · 1,953 stars · on GitHub · build.nvidia.com

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-build-vision-ai

Clone the repo

git clone --depth 1 https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/nvidia-ai-blueprints/video-search-and-summarization/vss-build-vision-ai/github.svg)](https://agentmods.dev/skills/nvidia-ai-blueprints/video-search-and-summarization/vss-build-vision-ai)

Your own site

<a href="https://agentmods.dev/skills/nvidia-ai-blueprints/video-search-and-summarization/vss-build-vision-ai"><img src="https://agentmods.dev/badge/skills/nvidia-ai-blueprints/video-search-and-summarization/vss-build-vision-ai/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/nvidia-ai-blueprints/video-search-and-summarization/vss-build-vision-ai"><img src="https://agentmods.dev/badge/skills/nvidia-ai-blueprints/video-search-and-summarization/vss-build-vision-ai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 203 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 14,832 The whole file, excluding the scripts and references it only reads on demand.

Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Tool Misuse · line 230
Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.

Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.
medium Tool Misuse · line 232
Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.

Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00203	$0.14832
Opus 5.5	$0.00081	$0.05933
Sonnet 5.5	$0.00041	$0.02966
Haiku 4.5	$0.00020	$0.01483

Measured 14d ago against content hash d75600a8f7f7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

vss-build-vision-ai scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 14d ago.

The scan reads SKILL.md. This mod also ships 12 executable files (scripts/check_credentials.sh, scripts/normalize_resolved_yml.py, scripts/probe_remote_models.sh, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

Submit that line for approval and run it — whether the host looks like it needs it and whatever the `sudo -n true` probe returned, since the script is idempotent and its `sudo` calls are internal ([Docker pin](references

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- **Preflight the host before accepting the yes**, per the Prerequisites section of [`references/agent-harness.md`](references/agent-harness.md): `uv`, `curl`, `docker`, and `python3` on `PATH` — the bring-up pins its ow

skills/vss-build-vision-ai/SKILL.md · 475 lines

How it starts

The opening of the file, as written. The whole thing — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Build Vision Agent

build-vision-ai gives agents and developers agent-ready vision capabilities through a customizable, self-contained application stack built on the NVIDIA VSS Blueprint. A developer or agent adds vision to their application by selecting the capabilities they want (guided intake) or describing them in natural language, and the skill routes to a validated developer profile — or composes the smallest delta overlay on top of one — and deploys it. Use it whenever the user wants vision capabilities composed for them: deploying a stock profile, extending a running deployment, or building a lean custom combination.

Two ways in: guided intake (state an open intent like "build a vision agent" / "add vision capabilities" and the skill walks you through capability selection) or prompt-driven (name the capability or profile directly). Both land on the same routing and composition flow.

When to Use

Compose and deploy a self-contained vision application stack — a stock developer profile (base, alerts, lvs, search) or the warehouse industry profile — not a single microservice on its own
Extend or customize that stack as a delta overlay on a developer profile Foundation
Change a build's lifecycle: install the NemoClaw/OpenClaw/Hermes harness on it, resize it, or tear it down. Operating the running stack (search, Q&A, summaries, alerts, reports) is not this skill — see below

Do Not Use This Skill For

Operating an already-running deployment: search, summarize, VIOS, alerts, reports, and video Q&A requests should route to the matching operations skill after vss configure has recorded the deployment origin. Adding or removing alert enhancement (a custom VLM response parser) is a build change and stays here.
Deploying a single standalone microservice such as RT-VLM, RT-CV, RT-Embed, VIOS, Video Analytics API, or Alert Bridge by itself. Use the matching skills/deployment/vss-deploy-* or setup skill instead.
Helm/Kubernetes deployment, notebook-only deployment, model benchmarking, or low-level service development. This skill owns Docker Compose stock profiles, the warehouse industry profile, and delta build artifacts under _builds/.
Unsupported industry profiles such as smartcities; warehouse is the only supported industry Foundation.

Read the full file on GitHub · 475 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

14d ago Changed · +5 lines d75600a8f7f7
18d ago Changed 33d501a5405b
20d ago Changed 2d6b23563091
21d ago Changed · +8 lines d88c40f9e2b4
22d ago Changed · +12 lines 6e0bd258e06e
24d ago Changed 9d5c4e818555
25d ago Changed · -4 lines ccc42bd07ec5
26d ago Changed 943b3e856fd4
27d ago Changed 3ccb7354e45d
28d ago First seen · 454 lines · 203 tokens per session scan B 374235be21b7

Subscribe to this mod's changes

vss-build-vision-ai is a skill published in the GitHub repository NVIDIA-AI-Blueprints/video-search-and-summarization (1,953 stars, last pushed today), licensed Apache-2.0. It adds 203 tokens to every session and 14,832 once invoked, about $0.0008 per session on Opus 5.5. A static security scan graded it B with 2 findings (asks for root, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Building agents Data and AI RAG and vectors computer-vision skills video-analytics video-search vlm

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