---
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.
origin: ECC
allowed-tools: Read Grep Glob Bash(python:*)
argument-hint: "[task description]"
---

# VideoDB Skill

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

## When to use

### 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**

### Video ingest + stream
- Ingest a **file or URL** and return a **playable web stream link**
- Transcode/normalize: **codec, bitrate, fps, resolution, aspect ratio**

### 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

### 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**

### Live streams (RTSP) + monitoring
- Connect **RTSP/live feeds**
- Run **real-time visual and spoken understanding** and emit **events/alerts** for monitoring workflows

## How it works

### 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**
- 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

### Running Python code

Before running any VideoDB code, change to the project directory and load environment variables:

```python
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:

```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
```

### Setup

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

### 1. Install SDK

```bash
pip install "videodb[capture]" python-dotenv
```

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

```bash
pip install videodb python-dotenv
```

### 2. Configure API key

The user must set `VIDEO_DB_API_KEY` using **either** method:

- **Export in terminal** (before starting Claude): `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

```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")
```

### Transcript + subtitle

```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()
```

### Search inside videos

```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
```

### Scene search

```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
```

### Timeline editing

**Important:** Always validate timestamps before building a timeline:
- `start` must be >= 0 (negative values are silently accepted but produce broken output)
- `start` must be < `end`
- `end` must be <= `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()
```

### Transcode video (resolution / quality change)

```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),
)
```

### 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

```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})
```

### Generative media

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

## Error handling

```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}")
```

### 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 |

## Examples

### Canonical prompts
- "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."

### Screen Recording (Desktop Capture)

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

#### Quick Start

1. **Choose state dir**: `STATE_DIR="${VIDEODB_EVENTS_DIR:-$HOME/.local/state/videodb}"`
2. **Start listener**: `VIDEODB_EVENTS_DIR="$STATE_DIR" python scripts/ws_listener.py --clear "$STATE_DIR" &`
3. **Get WebSocket ID**: `cat "$STATE_DIR/videodb_ws_id"`
4. **Run capture code** (see reference/capture.md for the full workflow)
5. **Events written to**: `$STATE_DIR/videodb_events.jsonl`

Use `--clear` whenever you start a fresh capture run so stale transcript and visual events do not leak into the new session.

#### Query Events

```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
]
```

## 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](reference/api-reference.md) - Complete VideoDB Python SDK API reference
- [reference/search.md](reference/search.md) - In-depth guide to video search (spoken word and scene-based)
- [reference/editor.md](reference/editor.md) - Timeline editing, assets, and composition
- [reference/streaming.md](reference/streaming.md) - HLS streaming and instant playback
- [reference/generative.md](reference/generative.md) - AI-powered media generation (images, video, audio)
- [reference/rtstream.md](reference/rtstream.md) - Live stream ingestion workflow (RTSP/RTMP)
- [reference/rtstream-reference.md](reference/rtstream-reference.md) - RTStream SDK methods and AI pipelines
- [reference/capture.md](reference/capture.md) - Desktop capture workflow
- [reference/capture-reference.md](reference/capture-reference.md) - Capture SDK and WebSocket events
- [reference/use-cases.md](reference/use-cases.md) - Common video processing patterns and examples

**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, and media generation. Only fall back to local tools for operations listed under Limitations in reference/editor.md (transitions, speed changes, crop/zoom, colour grading, volume mixing).

### 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 a `Timeline` |
| Need to add subtitles | `video.add_subtitle()` or `CaptionAsset` |
| Need to combine/trim clips | `VideoAsset` on a `Timeline` |
| Need to generate voiceover, music, or SFX | `coll.generate_voice()`, `generate_music()`, `generate_sound_effect()` |

## Provenance

Reference material for this skill is vendored locally under `skills/videodb/reference/`.
Use the local copies above instead of following external repository links at runtime.

**Maintained By:** [VideoDB](https://www.videodb.io/)