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natural-language-video-search自然语言视频搜索

Agent Skill

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

总安装

7,856

周安装

334

GitHub Stars

7

下载量

2,752
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:natural-language-video-search(自然语言视频搜索)
来源仓库:https://github.com/ssrajadh/natural-language-video-search
安装命令:
openclaw skills install natural-language-video-search
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install natural-language-video-search

简介

natural-language-video-search 利用 Gemini 嵌入实现视频内容的语义检索。

  • 适用于行车记录仪、安防录像等非结构化视频的快速定位。
  • 支持自然语言查询如“红色车辆出现时段”,返回精确时间片段。
  • 使用前需上传视频文件并建立索引,注意存储与计算资源消耗。
  • 适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

SKILL.md

name
natural-language-video-search
description
>
version
0.2.3
metadata
clawdbot
requires
env
bins
primaryEnv
GEMINI_API_KEY
homepage
https://github.com/ssrajadh/sentrysearch
emoji
🎥

Natural Language Video Search

Search video files using natural language queries powered by Gemini Embedding 2's native video-to-vector embedding.

What This Skill Does

This skill lets you index video files (dashcam footage, security camera recordings, any mp4) into a local vector database, then search them by describing what you're looking for in plain English. The top match is automatically trimmed and saved as a clip.

For Tesla dashcam footage, an optional telemetry overlay can burn speed, GPS, location, and turn signal data onto trimmed clips.

Setup

Requires uv and Python 3.11+.

  1. Clone and install:
git clone https://github.com/ssrajadh/sentrysearch.git
cd sentrysearch
uv sync

For Tesla overlay support (reverse geocoding):

uv sync --extra tesla
  1. Set your Gemini API key:
sentrysearch init

This prompts for your key, writes it to .env, and validates it with a test embedding. You can also set GEMINI_API_KEY directly as an environment variable.

Commands

Index video files

sentrysearch index <directory_or_file>

Options: --chunk-duration (default 30s), --overlap (default 5s), --no-preprocess, --target-resolution, --target-fps, --skip-still / --no-skip-still, --verbose

Search indexed footage

sentrysearch search "<natural language query>"

Options: -n / --results (default 5), -o / --output-dir, --trim / --no-trim, --threshold (default 0.41), --overlay / --no-overlay (Tesla telemetry), --verbose

Apply Tesla telemetry overlay

sentrysearch overlay <video_file>
sentrysearch overlay <video_file> -o output.mp4

Burns a HUD overlay onto a Tesla dashcam video showing speed, GPS coordinates, location name, and turn signal status. Reads telemetry from SEI NAL units embedded in Tesla firmware 2025.44.25+. Also available as --overlay flag on the search command to automatically overlay the trimmed clip.

Check index stats

sentrysearch stats

How It Works

Video files are split into overlapping chunks. Still-frame detection can skip chunks with no meaningful visual change, eliminating unnecessary API calls — this is the primary cost saver for idle footage like sentry mode or security cameras. Chunks are also preprocessed (reduced frame rate and resolution) to shrink upload size and speed up transfers, though the Gemini API bills based on video duration at a fixed token rate, not file size, so preprocessing does not reduce per-chunk token cost. Each chunk is embedded as raw video using Gemini Embedding 2 (no transcription or captioning). Vectors are stored in a local ChromaDB database. Text queries are embedded into the same vector space and matched via cosine similarity. The top match is auto-trimmed from the original file via ffmpeg.

When To Use This Skill

  • User asks to search through video files or footage
  • User wants to find a specific moment in a video by describing it
  • User asks to index or organize video footage for search
  • User mentions dashcam, security camera, or surveillance clips
  • User wants to find and extract a clip from a longer video
  • User has Tesla dashcam footage and wants speed/GPS/location overlay on clips
  • User wants to apply telemetry overlay to a Tesla video

Example Interactions

User: "Search my dashcam footage for a white truck cutting me off" Action: Run sentrysearch search "white truck cutting me off"

User: "Index all the video files in my Downloads folder" Action: Run sentrysearch index ~/Downloads

User: "Search for a red light and include the Tesla overlay on the clip" Action: Run sentrysearch search "running a red light" --overlay

User: "Add the speed and GPS overlay to this Tesla video" Action: Run sentrysearch overlay /path/to/tesla_video.mp4

User: "How much footage do I have indexed?" Action: Run sentrysearch stats

Rules

  • Always run sentrysearch init or confirm GEMINI_API_KEY is set before indexing or searching.
  • If ffmpeg is not found on PATH, the bundled imageio-ffmpeg fallback is used automatically.
  • Indexing costs ~$2.84/hour of active footage with default settings. Cost is driven by the number of chunks sent to the API — footage with long idle periods (sentry mode, security cameras) will be significantly cheaper since still-frame skipping eliminates those chunks entirely. Warn the user before indexing large directories.
  • Search results include similarity scores. Scores below the threshold (default 0.41) trigger a low-confidence prompt before trimming.
  • The Tesla overlay requires firmware 2025.44.25+ for SEI metadata. Videos without Tesla metadata will skip the overlay gracefully.
  • Requires Python 3.11+.

适合场景

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OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

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需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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按下载量换算2,329

安全审计

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敏感数据

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安装前确认

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来源信息

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