Agent skill

Videodb

by affaan-m in affaan-m/ECC

视频与音频的查看、理解与行动。查看:从本地文件、URL、RTSP/直播源或实时录制桌面获取内容;返回实时上下文和可播放流链接。理解:提取帧,构建视觉/语义/时间索引,并通过时间戳和自动剪辑搜索片段。行动:转码和标准化(编解码器、帧率、分辨率、宽高比),执行时间线编辑(字幕、文本/图像叠加、品牌化、音频叠加、配音、翻译),生成媒体资源(图像、音频、视频),并为直播流或桌面捕获的事件创建实时警报。

MITAuto-check: notes

Install Videodb

skills CLI
$ npx skills add affaan-m/ECC --skill videodb -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC videodb --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/docs/zh-CN/skills/videodb .claude/skills/videodb && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
videodb
GitHub stars
277k
Used in
2 other repos
Token cost
~2.5k tokens
SKILL.md length
339 words
Files
11
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

视频与音频的查看、理解与行动。查看:从本地文件、URL、RTSP/直播源或实时录制桌面获取内容;返回实时上下文和可播放流链接。理解:提取帧,构建视觉/语义/时间索引,并通过时间戳和自动剪辑搜索片段。行动:转码和标准化(编解码器、帧率、分辨率、宽高比),执行时间线编辑(字幕、文本/图像叠加、品牌化、音频叠加、配音、翻译),生成媒体资源(图像、音频、视频),并为直播流或桌面捕获的事件创建实时警报。

  • Works in 2 steps: 安装 SDK → 配置 API 密钥
  • SKILL.md covers 使用场景, 工作原理, 错误处理 and 示例, plus 1 more section
  • Calls python and pip; reaches youtube.com; needs VIDEO_DB_API_KEY

What it does

Videodb is an agent skill from affaan-m/ECC. 视频与音频的查看、理解与行动。查看:从本地文件、URL、RTSP/直播源或实时录制桌面获取内容;返回实时上下文和可播放流链接。理解:提取帧,构建视觉/语义/时间索引,并通过时间戳和自动剪辑搜索片段。行动:转码和标准化(编解码器、帧率、分辨率、宽高比),执行时间线编辑(字幕、文本/图像叠加、品牌化、音频叠加、配音、翻译),生成媒体资源(图像、音频、视频),并为直播流或桌面捕获的事件创建实时警报。

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files (for example `reference/api-reference.md`, `reference/capture-reference.md` and `reference/capture.md`).

It works with Python. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

Example prompts

  • “/videodb”

Requirements

  • Python 3
  • A credential in VIDEO_DB_API_KEY
  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash(python:*)

Workflow steps

2 steps, taken from the step headings in SKILL.md.

  1. 安装 SDK
  2. 配置 API 密钥

What it can do on your machine

Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Bash(python:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • youtube.com

    Also links to:

    • console.videodb.io
    • videodb.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • VIDEO_DB_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Videodb loads about 2.5k tokens when it runs. Until then it costs about 52 tokens; SKILL.md has 339 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~52
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:67
    load_dotenv(".env")
  • NoteMentions a .env fileSKILL.md:76
    2. 项目当前目录中的 `.env` 文件
  • NoteMentions a .env fileSKILL.md:87
    load_dotenv(".env")
  • NoteMentions a .env fileSKILL.md:117
    * **项目 `.env` 文件**:将 `VIDEO_DB_API_KEY=your-key` 保存在项目的 `.env` 文件中

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 339 words, ~2,520 tokens.

Download SKILL.mdSave it as .claude/skills/videodb/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
videodb
description
视频与音频的查看、理解与行动。查看:从本地文件、URL、RTSP/直播源或实时录制桌面获取内容;返回实时上下文和可播放流链接。理解:提取帧,构建视觉/语义/时间索引,并通过时间戳和自动剪辑搜索片段。行动:转码和标准化(编解码器、帧率、分辨率、宽高比),执行时间线编辑(字幕、文本/图像叠加、品牌化、音频叠加、配音、翻译),生成媒体资源(图像、音频、视频),并为直播流或桌面捕获的事件创建实时警报。
allowed-tools
Read, Grep, Glob, Bash(python:*)
origin
ECC
argument-hint
[task description]

VideoDB 技能

针对视频、直播流和桌面会话的感知 + 记忆 + 操作。

使用场景

桌面感知
  • 启动/停止桌面会话,捕获屏幕、麦克风和系统音频
  • 流式传输实时上下文并存储片段式会话记忆
  • 对所说的内容和屏幕上发生的事情运行实时警报/触发器
  • 生成会话摘要、可搜索的时间线和可播放的证据链接
视频摄取 + 流
  • 摄取文件或URL并返回可播放的网络流链接
  • 转码/标准化:编解码器、比特率、帧率、分辨率、宽高比
索引 + 搜索(时间戳 + 证据)
  • 构建视觉、语音和关键词索引
  • 搜索并返回带有时间戳和可播放证据的精确时刻
  • 从搜索结果自动创建片段
时间线编辑 + 生成
  • 字幕:生成、翻译、烧录
  • 叠加层:文本/图片/品牌标识,动态字幕
  • 音频:背景音乐、画外音、配音
  • 通过时间线操作进行程序化合成和导出
直播流(RTSP)+ 监控
  • 连接RTSP/实时流
  • 运行实时视觉和语音理解,并为监控工作流发出事件/警报

工作原理

常见输入
  • 本地文件路径、公共URL或RTSP URL
  • 桌面捕获请求:启动 / 停止 / 总结会话
  • 期望的操作:获取理解上下文、转码规格、索引规格、搜索查询、片段范围、时间线编辑、警报规则
常见输出
  • 流URL
  • 带有时间戳和证据链接的搜索结果
  • 生成的资产:字幕、音频、图片、片段
  • 用于直播流的事件/警报负载
  • 桌面会话摘要和记忆条目
运行 Python 代码

在运行任何 VideoDB 代码之前,请切换到项目目录并加载环境变量:

python
from dotenv import load_dotenv
load_dotenv(".env")

import videodb
conn = videodb.connect()

这会从以下位置读取 VIDEO_DB_API_KEY:

  1. 环境变量(如果已导出)
  2. 项目当前目录中的 .env 文件

如果密钥缺失,videodb.connect() 会自动引发 AuthenticationError。

当简短的內联命令有效时,不要编写脚本文件。

编写內联 Python (python -c "...") 时,始终使用格式正确的代码——使用分号分隔语句并保持可读性。对于任何超过约3条语句的内容,请改用 heredoc:

bash
python << 'EOF'
from dotenv import load_dotenv
load_dotenv(".env")

import videodb
conn = videodb.connect()
coll = conn.get_collection()
print(f"Videos: {len(coll.get_videos())}")
EOF
设置

当用户要求“设置 videodb”或类似操作时:

1. 安装 SDK
bash
pip install "videodb[capture]" python-dotenv

如果在 Linux 上 videodb[capture] 失败,请安装不带捕获扩展的版本:

bash
pip install videodb python-dotenv
2. 配置 API 密钥

用户必须使用任一方法设置 VIDEO_DB_API_KEY:

  • 在终端中导出(在启动 Claude 之前):export VIDEO_DB_API_KEY=your-key
  • 项目 .env 文件:将 VIDEO_DB_API_KEY=your-key 保存在项目的 .env 文件中

免费获取 API 密钥,请访问 console.videodb.io(50 次免费上传,无需信用卡)。

请勿自行读取、写入或处理 API 密钥。始终让用户设置。

快速参考
上传媒体
python
# URL
video = coll.upload(url="https://example.com/video.mp4")

# YouTube
video = coll.upload(url="https://www.youtube.com/watch?v=VIDEO_ID")

# Local file
video = coll.upload(file_path="/path/to/video.mp4")
转录 + 字幕
python
# force=True skips the error if the video is already indexed
video.index_spoken_words(force=True)
text = video.get_transcript_text()
stream_url = video.add_subtitle()
在视频内搜索
python
from videodb.exceptions import InvalidRequestError

video.index_spoken_words(force=True)

# search() raises InvalidRequestError when no results are found.
# Always wrap in try/except and treat "No results found" as empty.
try:
    results = video.search("product demo")
    shots = results.get_shots()
    stream_url = results.compile()
except InvalidRequestError as e:
    if "No results found" in str(e):
        shots = []
    else:
        raise
场景搜索
python
import re
from videodb import SearchType, IndexType, SceneExtractionType
from videodb.exceptions import InvalidRequestError

# index_scenes() has no force parameter — it raises an error if a scene
# index already exists. Extract the existing index ID from the error.
try:
    scene_index_id = video.index_scenes(
        extraction_type=SceneExtractionType.shot_based,
        prompt="Describe the visual content in this scene.",
    )
except Exception as e:
    match = re.search(r"id\s+([a-f0-9]+)", str(e))
    if match:
        scene_index_id = match.group(1)
    else:
        raise

# Use score_threshold to filter low-relevance noise (recommended: 0.3+)
try:
    results = video.search(
        query="person writing on a whiteboard",
        search_type=SearchType.semantic,
        index_type=IndexType.scene,
        scene_index_id=scene_index_id,
        score_threshold=0.3,
    )
    shots = results.get_shots()
    stream_url = results.compile()
except InvalidRequestError as e:
    if "No results found" in str(e):
        shots = []
    else:
        raise
时间线编辑

重要提示: 在构建时间线之前,请务必验证时间戳:

  • start 必须 >= 0(负值会被静默接受,但会产生损坏的输出)
  • start 必须 < end
  • end 必须 <= video.length
python
from videodb.timeline import Timeline
from videodb.asset import VideoAsset, TextAsset, TextStyle

timeline = Timeline(conn)
timeline.add_inline(VideoAsset(asset_id=video.id, start=10, end=30))
timeline.add_overlay(0, TextAsset(text="The End", duration=3, style=TextStyle(fontsize=36)))
stream_url = timeline.generate_stream()
转码视频(分辨率 / 质量更改)
python
from videodb import TranscodeMode, VideoConfig, AudioConfig

# Change resolution, quality, or aspect ratio server-side
job_id = conn.transcode(
    source="https://example.com/video.mp4",
    callback_url="https://example.com/webhook",
    mode=TranscodeMode.economy,
    video_config=VideoConfig(resolution=720, quality=23, aspect_ratio="16:9"),
    audio_config=AudioConfig(mute=False),
)
调整宽高比(适用于社交平台)

警告: reframe() 是一项缓慢的服务器端操作。对于长视频,可能需要几分钟,并可能超时。最佳实践:

  • 尽可能使用 start/end 限制为短片段
  • 对于全长视频,使用 callback_url 进行异步处理
  • 先在 Timeline 上修剪视频,然后调整较短结果的宽高比
python
from videodb import ReframeMode

# Always prefer reframing a short segment:
reframed = video.reframe(start=0, end=60, target="vertical", mode=ReframeMode.smart)

# Async reframe for full-length videos (returns None, result via webhook):
video.reframe(target="vertical", callback_url="https://example.com/webhook")

# Presets: "vertical" (9:16), "square" (1:1), "landscape" (16:9)
reframed = video.reframe(start=0, end=60, target="square")

# Custom dimensions
reframed = video.reframe(start=0, end=60, target={"width": 1280, "height": 720})
生成式媒体
python
image = coll.generate_image(
    prompt="a sunset over mountains",
    aspect_ratio="16:9",
)

错误处理

python
from videodb.exceptions import AuthenticationError, InvalidRequestError

try:
    conn = videodb.connect()
except AuthenticationError:
    print("Check your VIDEO_DB_API_KEY")

try:
    video = coll.upload(url="https://example.com/video.mp4")
except InvalidRequestError as e:
    print(f"Upload failed: {e}")
常见问题
场景错误信息解决方案
为已索引的视频建立索引Spoken word index for video already exists使用 video.index_spoken_words(force=True) 跳过已索引的情况
场景索引已存在Scene index with id XXXX already exists使用 re.search(r"id\s+([a-f0-9]+)", str(e)) 从错误中提取现有的 scene_index_id
搜索无匹配项InvalidRequestError: No results found捕获异常并视为空结果 (shots = [])
调整宽高比超时长视频上无限期阻塞使用 start/end 限制片段,或传递 callback_url 进行异步处理
Timeline 上的负时间戳静默产生损坏的流在创建 VideoAsset 之前,始终验证 start >= 0
generate_video() / create_collection() 失败Operation not allowed 或 maximum limit计划限制的功能——告知用户关于计划限制

示例

规范提示
  • "开始桌面捕获,并在密码字段出现时发出警报。"
  • "记录我的会话并在结束时生成可操作的摘要。"
  • "摄取此文件并返回可播放的流链接。"
  • "为此文件夹建立索引,并找到每个有人的场景,返回时间戳。"
  • "生成字幕,将其烧录进去,并添加轻背景音乐。"
  • "连接此 RTSP URL,并在有人进入区域时发出警报。"
屏幕录制(桌面捕获)

使用 ws_listener.py 在录制会话期间捕获 WebSocket 事件。桌面捕获仅支持 macOS。

快速开始
  1. 选择状态目录:STATE_DIR="${VIDEODB_EVENTS_DIR:-$HOME/.local/state/videodb}"
  2. 启动监听器:VIDEODB_EVENTS_DIR="$STATE_DIR" python scripts/ws_listener.py --clear "$STATE_DIR" &
  3. 获取 WebSocket ID:cat "$STATE_DIR/videodb_ws_id"
  4. 运行捕获代码(完整工作流程请参阅 reference/capture.md)
  5. 事件写入:$STATE_DIR/videodb_events.jsonl

每当开始新的捕获运行时,请使用 --clear,以免过时的转录和视觉事件泄露到新会话中。

查询事件
python
import json
import os
import time
from pathlib import Path

events_dir = Path(os.environ.get("VIDEODB_EVENTS_DIR", Path.home() / ".local" / "state" / "videodb"))
events_file = events_dir / "videodb_events.jsonl"
events = []

if events_file.exists():
    with events_file.open(encoding="utf-8") as handle:
        for line in handle:
            try:
                events.append(json.loads(line))
            except json.JSONDecodeError:
                continue

transcripts = [e["data"]["text"] for e in events if e.get("channel") == "transcript"]
cutoff = time.time() - 300
recent_visual = [
    e for e in events
    if e.get("channel") == "visual_index" and e["unix_ts"] > cutoff
]

附加文档

参考文档位于与此 SKILL.md 文件相邻的 reference/ 目录中。如果需要,请使用 Glob 工具来定位。

当 VideoDB 支持该操作时,不要使用 ffmpeg、moviepy 或本地编码工具。 以下所有操作均由 VideoDB 在服务器端处理——修剪、合并片段、叠加音频或音乐、添加字幕、文本/图像叠加层、转码、分辨率更改、宽高比转换、为平台要求调整大小、转录和媒体生成。仅当 reference/editor.md 中“限制”部分列出的操作(转场、速度变化、裁剪/缩放、色彩分级、音量混合)时,才回退到本地工具。

何时使用什么
问题VideoDB 解决方案
平台拒绝视频宽高比或分辨率使用 VideoConfig 的 video.reframe() 或 conn.transcode()
需要为 Twitter/Instagram/TikTok 调整视频大小video.reframe(target="vertical") 或 target="square"
需要更改分辨率(例如 1080p → 720p)使用 VideoConfig(resolution=720) 的 conn.transcode()
需要在视频上叠加音频/音乐在 Timeline 上使用 AudioAsset
需要添加字幕video.add_subtitle() 或 CaptionAsset
需要合并/修剪片段在 Timeline 上使用 VideoAsset
需要生成画外音、音乐或音效coll.generate_voice()、generate_music()、generate_sound_effect()

来源

此技能的参考材料在 skills/videodb/reference/ 下本地提供。 请使用上面的本地副本,而不是在运行时遵循外部存储库链接。

维护者: VideoDB

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 10 other files in docs/zh-CN/skills/videodb of affaan-m/ECC.

  • SKILL.md
  • reference/api-reference.md
  • reference/capture-reference.md
  • reference/capture.md
  • reference/editor.md
  • reference/generative.md
  • reference/rtstream-reference.md
  • reference/rtstream.md
  • reference/search.md
  • reference/streaming.md
  • reference/use-cases.md

Open the folder on GitHubat commit 2d515e4

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Works with

Questions about Videodb

What does Videodb do?

视频与音频的查看、理解与行动。查看:从本地文件、URL、RTSP/直播源或实时录制桌面获取内容;返回实时上下文和可播放流链接。理解:提取帧,构建视觉/语义/时间索引,并通过时间戳和自动剪辑搜索片段。行动:转码和标准化(编解码器、帧率、分辨率、宽高比),执行时间线编辑(字幕、文本/图像叠加、品牌化、音频叠加、配音、翻译),生成媒体资源(图像、音频、视频),并为直播流或桌面捕获的事件创建实时警报。. Videodb is an agent skill from affaan-m/ECC.

How do I install Videodb in Claude Code?

Run `npx skills add affaan-m/ECC --skill videodb -a claude-code`. Or copy the skill folder (docs/zh-CN/skills/videodb in affaan-m/ECC) into .claude/skills/videodb in your project. Claude Code loads it when a task matches its description.

How do I install Videodb in Codex?

Run `npx skills add affaan-m/ECC --skill videodb -a codex`. Or copy the skill folder (docs/zh-CN/skills/videodb in affaan-m/ECC) into .agents/skills/videodb in your project. Codex loads it when a task matches its description.

Can I use Videodb in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill videodb -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/videodb, .gemini/skills/videodb, .github/skills/videodb and .opencode/skills/videodb in your project.

What does Videodb need to run?

Going by SKILL.md and its folder, Videodb needs the command-line tools its instructions call (python and pip) and credentials named VIDEO_DB_API_KEY. Our summary lists: Python 3; A credential in VIDEO_DB_API_KEY. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash(python:*).

Does Videodb access the network?

SKILL.md names 3 domains. In commands or code: youtube.com; the agent is likely to contact it when it follows the instructions. As links in the text: console.videodb.io and videodb.io. This is read from the text; nothing was executed.

Is Videodb safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Videodb use?

Videodb is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Videodb use?

About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Videodb?

Skills that share tags, products or a category with Videodb: MCP Server Builder (anthropics/skills, 180k stars), PDF Processing (anthropics/skills, 180k stars), NotebookLM Research Assistant (PleasePrompto/notebooklm-skill, 7.8k stars) and Manim Video Production (browser-use/video-use, 29k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Videodb?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.