# Vss Search Archive

Use this skill when a user wants to search archived VSS video that is already...

- Repository: https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization (1959 stars)
- Category: Media
- License: Apache-2.0
- Last updated: 2026-11-01
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-search-archive -g -a claude-code -y`
Codex: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-search-archive -g -a codex -y`
Cursor: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-search-archive -g -a cursor -y`
Gemini CLI: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-search-archive -g -a gemini-cli -y`

## Description

Use this skill when a user wants to search archived VSS video that is already registered in a configured deployment, by natural-language, similarity, attribute, object-ID, or lexical tag query. Not for fresh clip Q&A, live captioning, video summarization, deployment, or source ingestion/deletion.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Search archived VSS video

## When to Use

- Search archived VSS video that is already registered in a configured deployment, by natural-language, similarity, attribute, object-ID, or lexical tag query.

Not for:

- A fresh visual question about a supplied local clip, `vss-ask-video`.
- Long-form summarization of a recording, `vss-summarize-video`.
- Deploying or changing a profile, `/vss-build-vision-ai`.
- Ingesting or deleting a source, use the deployment's source-management workflow.

Answer from the configured deployment through the installed `vss` CLI. Do not
fall back to raw REST when a CLI command fails.

> **Hard rule, use the `vss` CLI for retrieval.** `vss configure` has already
> pointed the CLI at the deployment, so every search action goes through
> `vss search run` and nothing reaches the deployment any other way.
>
> Four things follow:
>
> - use the `vss` on PATH (see Prerequisites); never `docker exec`, `kubectl
>   exec`, a pod shell, or a hand-built `/api/v1/search` call;
> - a named source is resolved with `vss vios list` before search, never
>   inferred from a display name, and never substituted when missing;
> - capture stdout and the exit status separately, never put the command
>   behind `if !`, which hides the real exit code, and never discard usable
>   exit-6 results;
> - a failing command is a finding: report the exit code rather than routing
>   around it, repairing the deployment, or retrying with broadened scope.

## Prerequisites

- A running VSS `search` profile with `vss configure` already run against its origin. Refresh configuration after first ingestion, once source provisioning has established readiness; lazy raw indexes enable frame enrichment for attribute/fusion.
- The `vss` CLI on PATH. The OpenClaw and Hermes harness images ship it; anywhere else, install it from the same checkout as this skill so the CLI and the skill match: `uv tool install <checkout>/libs/vss/cli`.

The rest: https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization/blob/HEAD/skills/operations/vss-search-archive/SKILL.md