Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add majiang213/OpenClaw-MAS --skill videodbgit clone --depth 1 https://github.com/majiang213/OpenClaw-MASWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/majiang213/openclaw-mas/videodb)<a href="https://agentmods.dev/skills/majiang213/openclaw-mas/videodb"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/videodb/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/majiang213/openclaw-mas/videodb"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/videodb.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00125 | $0.03349 |
| Opus 5 | $0.00063 | $0.01674 |
| Sonnet 5 | $0.00025 | $0.00670 |
| Haiku 4.5 | $0.00013 | $0.00335 |
Grade A, and why
videodb scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- videodb — 95% identical, 5 lines differ
How it starts
The opening of the file, as written. The whole thing — 375 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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()
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- reference/api-reference.md 20 KB
- reference/capture-reference.md 12 KB
- reference/capture.md 4.7 KB
- reference/editor.md 16 KB
- reference/generative.md 10 KB
- reference/rtstream-reference.md 15 KB
- reference/rtstream.md 1.8 KB
- reference/search.md 7.7 KB
- reference/streaming.md 12 KB
- reference/use-cases.md 4.3 KB
- scripts/ws_listener.py 8.2 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 375 lines · 125 tokens per session scan A 85e9391e6234
videodb is a skill published in the GitHub repository majiang213/OpenClaw-MAS (5 stars, last pushed 5mo ago), licensed MIT. It adds 125 tokens to every session and 3,349 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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