---
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. Use when ingesting, indexing, searching, editing, transcoding, or alerting on video or audio content.
metadata:
  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 [console.videodb.io](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.
