Token导航 LogoToken导航TokenDH.com
研究检索敏感数据github未标认证来源可访问许可证需确认审计异常

videodbvideodb 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

10,011

周安装

413

GitHub Stars

74

下载量

3,271
CodexClaudeCursorGemini CLI

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

unknown

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:videodb(videodb 搜索)
来源仓库:https://github.com/video-db/skills
仓库路径:skills/videodb
安装命令:
npx skills add https://github.com/video-db/skills --skill videodb
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/video-db/skills --skill videodb

简介

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。

  • 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。
  • videodb 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

VideoDB Skill

Perception + memory + actions for video, live streams, and desktop sessions.

Use this skill when you need to:

1) Desktop Perception

  • Start/stop a desktop session capturing screen, mic, and system audio
  • Stream live context and store episodic session memory
  • Run real-time alerts/triggers on what’s spoken and what's happening on screen
  • Produce session summaries, a searchable timeline, and playable evidence links

2) Video ingest + stream

  • Ingest a file or URL and return a playable web stream link
  • Transcode/normalize: codec, bitrate, fps, resolution, aspect ratio

3) Index + search (timestamps + evidence)

  • Build visual, spoken, and keyword indexes
  • Search and return exact moments with timestamps and playable evidence
  • Auto-create clips from search results

4) Timeline editing + generation

  • Subtitles: generate, translate, burn-in
  • Overlays: text/image/branding, motion captions
  • Audio: background music, voiceover, dubbing
  • Programmatic composition and exports via timeline operations

5) Live streams (RTSP) + monitoring

  • Connect RTSP/live feeds
  • Run real-time visual and spoken understanding and emit events/alerts for monitoring workflows

Common inputs

  • Local file path, public URL, or RTSP URL
  • Desktop capture request: start / stop / summarize session
  • Desired operations: get context for understanding, transcode spec, index spec, search query, clip ranges, timeline edits, alert rules

Common outputs

  • Stream URL — make it playable: https://console.videodb.io/player?url={STREAM_URL}
  • Search results with timestamps and evidence links
  • Generated assets: subtitles, audio, images, clips
  • Event/alert payloads for live streams
  • Desktop session summaries and memory entries

Canonical prompts (examples)

  • “Start desktop capture and alert when a password field appears.”
  • “Record my session and produce an actionable summary when it ends.”
  • “Ingest this file and return a playable stream link.”
  • “Index this folder and find every scene with people, return timestamps.”
  • “Generate subtitles, burn them in, and add light background music.”
  • “Connect this RTSP URL and alert when a person enters the zone.”

Running Python code

CRITICAL: Always cd to the user's project directory before running Python code. This ensures load_dotenv(".env") finds the correct .env file.

from dotenv import load_dotenv
load_dotenv(".env")

import videodb
conn = videodb.connect()

This reads VIDEO_DB_API_KEY from:

  1. Environment (if already exported)
  2. Project's .env file in current directory

If the key is missing, videodb.connect() raises AuthenticationError automatically.

Do NOT write a script file when a short inline command works.

When writing inline Python (python -c "..."), always use properly formatted code — use semicolons to separate statements and keep it readable. For anything longer than ~3 statements, use a heredoc instead:

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

Setup

When the user asks to "setup videodb" or similar:

1. Install SDK

pip install "videodb[capture]" python-dotenv

If videodb[capture] fails on Linux, install without the capture extra:

pip install videodb python-dotenv

2. Configure API key

The user must set VIDEO_DB_API_KEY using either method:

  • Export in terminal (recommended): export VIDEO_DB_API_KEY=your-key
  • Project .env file: Save VIDEO_DB_API_KEY=your-key in the project's .env file

Get a free API key at https://console.videodb.io (50 free uploads, no credit card).

Do NOT read, write, or handle the API key yourself. Always let the user set it.

Quick Reference

Upload media

# 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")

Transcript + subtitle

# 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()

Search inside videos

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

Scene search

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

Timeline editing

Use the Editor API to compose videos, images, audio, and text. See reference/editor.md for full workflow.

from videodb.editor import Timeline, Track, Clip, VideoAsset, ImageAsset, AudioAsset, Fit

timeline = Timeline(conn)
timeline.resolution = "1280x720"

video_track = Track()
video_track.add_clip(0, Clip(asset=VideoAsset(id=video.id, start=10), duration=20))

audio_track = Track()
audio_track.add_clip(0, Clip(asset=AudioAsset(id=music.id, volume=0.2), duration=20))

timeline.add_track(video_track)
timeline.add_track(audio_track)
stream_url = timeline.generate_stream()

Transcode video (resolution / quality change)

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),
)

Reframe aspect ratio (for social platforms)

Warning: reframe() is a slow server-side operation. For long videos it can take several minutes and may time out. Best practices:

  • Always limit to a short segment using start/end when possible
  • For full-length videos, use callback_url for async processing
  • Trim the video on a Timeline first, then reframe the shorter result
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})

Generative media

image = coll.generate_image(
    prompt="a sunset over mountains",
    aspect_ratio="16:9",
)

Error handling

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}")

Common pitfalls

ScenarioError messageSolution
Indexing an already-indexed videoSpoken word index for video already existsUse video.index_spoken_words(force=True) to skip if already indexed
Scene index already existsScene index with id XXXX already existsExtract the existing scene_index_id from the error with re.search(r"id\s+([a-f0-9]+)", str(e))
Search finds no matchesInvalidRequestError: No results foundCatch the exception and treat as empty results (shots = [])
Reframe times outBlocks indefinitely on long videosUse start/end to limit segment, or pass callback_url for async
Negative timestamps on TimelineSilently produces broken streamAlways validate start >= 0 before creating VideoAsset
generate_video() / create_collection() failsOperation not allowed or maximum limitPlan-gated features — inform the user about plan limits

Additional docs

Reference documentation is in the reference/ directory adjacent to this SKILL.md file. Use the Glob tool to locate it if needed.

Screen Recording (Desktop Capture)

Use ws_listener.py to capture WebSocket events during recording sessions. Desktop capture supports macOS only.

Quick Start

  1. Start listener: python scripts/ws_listener.py --cwd=<PROJECT_ROOT> &
  2. Get WebSocket ID: cat /tmp/videodb_ws_id
  3. Run capture code (see reference/capture.md for full workflow)
  4. Events written to: /tmp/videodb_events.jsonl

Query Events

import json
events = [json.loads(l) for l in open("/tmp/videodb_events.jsonl")]

# Get all transcripts
transcripts = [e["data"]["text"] for e in events if e.get("channel") == "transcript"]

# Get visual descriptions from last 5 minutes
import time
cutoff = time.time() - 300
recent_visual = [e for e in events
                 if e.get("channel") == "visual_index" and e["unix_ts"] > cutoff]

Utility Scripts

For complete capture workflow, see reference/capture.md.

Do not use ffmpeg, moviepy, or local encoding tools when VideoDB supports the operation. The following are all handled server-side by VideoDB — trimming, combining clips, overlaying audio or music, adding subtitles, text/image overlays, transcoding, resolution changes, aspect-ratio conversion, resizing for platform requirements, transcription, volume control, fade transitions, and media generation. Only fall back to local tools for operations listed under Limitations in reference/editor.md (speed changes, crop/zoom, colour grading, keyframe animation).

When to use what

ProblemVideoDB solution
Platform rejects video aspect ratio or resolutionvideo.reframe() or conn.transcode() with VideoConfig
Need to resize video for Twitter/Instagram/TikTokvideo.reframe(target="vertical") or target="square"
Need to change resolution (e.g. 1080p → 720p)conn.transcode() with VideoConfig(resolution=720)
Need to overlay audio/music on videoAudioAsset on an Editor Timeline with volume control
Need to add subtitlesvideo.add_subtitle() or CaptionAsset on Editor Timeline
Need to combine/trim clipsVideoAsset on an Editor Timeline
Need to compose images with voiceoverImageAsset + AudioAsset on separate Editor tracks
Need to generate voiceover, music, or SFXcoll.generate_voice(), generate_music(), generate_sound_effect()

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

33.98%
按下载量换算1,111

Claude

32.16%
按下载量换算1,052

Cursor

19.51%
按下载量换算638

Gemini CLI

9.12%
按下载量换算298

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

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

继续浏览同类 Skills