videodb

name	videodb
description	See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.
allowed-tools	Read Grep Glob Bash(python:*)
argument-hint	[task description]

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

Scenario	Error message	Solution
Indexing an already-indexed video	Spoken word index for video already exists	Use video.index_spoken_words(force=True) to skip if already indexed
Scene index already exists	Scene index with id XXXX already exists	Extract the existing scene_index_id from the error with re.search(r"id\s+([a-f0-9]+)", str(e))
Search finds no matches	InvalidRequestError: No results found	Catch the exception and treat as empty results (shots = [])
Reframe times out	Blocks indefinitely on long videos	Use start/end to limit segment, or pass callback_url for async
Negative timestamps on Timeline	Silently produces broken stream	Always validate start >= 0 before creating VideoAsset
generate_video() / create_collection() fails	Operation not allowed or maximum limit	Plan-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.

• reference/api-reference.md - Complete VideoDB Python SDK API reference
• reference/index.md - Scene indexing & extraction workflow (index, extract frames, read back, manage)
• reference/index-reference.md - Scene index code reference (methods, SceneCollection/Scene/Frame classes)
• reference/search.md - In-depth guide to video search (spoken word and scene-based)
• reference/editor.md - Timeline editing workflow guide (4-layer model, use cases, examples)
• reference/editor-reference.md - Editor code reference (constructors, parameters, enums)
• reference/streaming.md - HLS streaming and instant playback
• reference/generative.md - AI-powered media generation (images, video, audio)
• reference/rtstream.md - Live stream ingestion workflow (RTSP/RTMP)
• reference/rtstream-reference.md - RTStream SDK methods and AI pipelines
• reference/capture.md - Desktop capture workflow
• reference/capture-reference.md - Capture SDK and WebSocket events
• reference/use-cases.md - Common video processing patterns and examples

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

• scripts/ws_listener.py - WebSocket event listener (dumps to JSONL)

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

Problem	VideoDB solution
Platform rejects video aspect ratio or resolution	video.reframe() or conn.transcode() with VideoConfig
Need to resize video for Twitter/Instagram/TikTok	video.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 video	AudioAsset on an Editor Timeline with volume control
Need to add subtitles	video.add_subtitle() or CaptionAsset on Editor Timeline
Need to combine/trim clips	VideoAsset on an Editor Timeline
Need to compose images with voiceover	ImageAsset + AudioAsset on separate Editor tracks
Need to generate voiceover, music, or SFX	coll.generate_voice(), generate_music(), generate_sound_effect()