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video-sourcing视频来源

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

20,627

周安装

877

GitHub Stars

公开资料未说明

下载量

7,226
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:video-sourcing(视频来源)
来源仓库:https://github.com/samuelz12/video-sourcing
安装命令:
openclaw skills install video-sourcing
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 video-sourcing

简介

使用固定的自引导运行时,为 /video_source 运行具有确定性、简洁的聊天 UX 的视频源代理。

SKILL.md

name
video-sourcing
description
Run the Video Sourcing Agent with deterministic, concise chat UX for /video_sourcing using a pinned self-bootstrap runtime.
user-invocable
true
metadata
{"openclaw":{"os":["darwin","linux"],"homepage":"https://github.com/Memories-ai-labs/video-sourcing-agent","requires":{"bins":["git","uv"],"env":["GOOGLE_API_KEY","YOUTUBE_API_KEY"]}}}

Video Sourcing Skill

Use this skill when the user asks to find, compare, or analyze social videos (YouTube, TikTok, Instagram, Twitter/X), or explicitly invokes /video_sourcing.

This workflow expects host runtime execution (sandbox mode off). The runner auto-bootstraps a pinned runtime from Memories-ai-labs/video-sourcing-agent@v0.2.5 when VIDEO_SOURCING_AGENT_ROOT is not set.

Triggering

Run this workflow when either condition is true:

  1. Message starts with /video_sourcing.
  2. The user asks for video sourcing/trend/creator/brand analysis and wants concrete video links.

If /video_sourcing is used with no query body, ask for the missing query.

Execution contract

  1. Resolve query text:

- /video_sourcing ... => strip /video_sourcing and use remaining text. - Free-form => use user message as query.

  1. Default to compact mode:

- --event-detail compact

  1. If user asks for debugging/raw payloads:

- Switch to --event-detail verbose

/video_sourcing deterministic path

  1. Build command with required args:

- <skill_dir>/scripts/run_video_query.sh --query "<query>" --event-detail <compact|verbose> --ux-mode three_message --progress-gate-seconds 5

  1. Start with exec using background: true and explicit timeout:

- timeout: 420

  1. Poll with process using action: "poll" every 2-4 seconds until process exits.
  2. Parse NDJSON output and render only these events, using your persona voice for all user-facing text:

- started => send a brief message conveying that video sourcing has begun, written in your persona voice - ux_progress => read the summary field as structured status data and compose a concise, natural progress update in your persona voice (do not echo summary verbatim) Send each ux_progress as a separate assistant message in Telegram. - terminal event (complete, clarification_needed, error) => send final message as-is

  1. Do not forward raw progress, tool_call, or tool_result events for /video_sourcing.
  2. Preserve the user's existing OpenClaw personality behavior across all messages — progress and final alike.
  3. Never launch a second run while a prior run session is still active.

- If retrying, call process with action: "kill" for the prior sessionId first.

  1. If process exits without a terminal event, send a concise fallback message that:

- states run ended before completion, - includes one actionable next step, - does not start another run automatically.

Behavior target for /video_sourcing:

  1. Fast run (<5s): 2 messages (started, terminal).
  2. Longer run (>=5s): recurring throttled ux_progress updates, then terminal.

Free-form path (non-strict)

  1. Keep existing flexible behavior.
  2. Build command without forcing three_message mode:

- <skill_dir>/scripts/run_video_query.sh --query "<query>" --event-detail <compact|verbose>

  1. Stream useful progress updates and final response naturally.

Final response format

When terminal event is complete:

  1. One short paragraph conclusion.
  2. Top 3 video references only by default:

- title - url - one-line relevance note

  1. Tools used: ... with a compact status summary.

If fewer than 3 videos exist, show all available references.

When terminal event is clarification_needed:

  1. Ask the clarification question directly.
  2. Treat this as the final response for the current run.

When terminal event is error:

  1. Send concise failure reason.
  2. Include one actionable next step.

Safety and fallback

  1. If script fails due to missing env/tooling, explain exact missing piece (for example VIDEO_SOURCING_AGENT_ROOT, uv, or API key env var).
  2. If VIDEO_SOURCING_AGENT_ROOT is unset, the runner uses managed path:

- ~/.openclaw/data/video-sourcing-agent/v0.2.5

  1. VIDEO_SOURCING_AGENT_ROOT remains an advanced override for local development.
  2. Keep response concise and action-oriented.
  3. Never fabricate video URLs or metrics.

适合场景

01

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

04

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

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

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

OpenClaw

86.7%
按下载量换算6,265

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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