Videodb

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:

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 = 0 (negative values are silently accepted but produce broken output)
- `start` must be = 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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: affaan-m
• Source: affaan-m/ECC
• License: MIT
• Homepage: https://ecc.tools

Install and usage instructions live in the source repository linked above.