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 AndyZhuang/Opentest --skill protocol_video_matchinggit clone --depth 1 https://github.com/AndyZhuang/OpentestWrote 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/andyzhuang/opentest/protocol_video_matching)<a href="https://agentmods.dev/skills/andyzhuang/opentest/protocol_video_matching"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/protocol_video_matching/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/andyzhuang/opentest/protocol_video_matching"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/protocol_video_matching.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 | $0.00060 | $0.03120 |
| Opus 5 | $0.00030 | $0.01560 |
| Sonnet 5 | $0.00012 | $0.00624 |
| Haiku 4.5 | $0.00006 | $0.00312 |
Grade A, and why
protocol_video_matching 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Protocol Video Matching
Overview
protocol_video_matching bridges the physical bench and the digital protocol by continuously aligning a first-person XR headset video stream (e.g., Meta Quest, HoloLens 2, Magic Leap) against structured protocol text in real time. The skill parses each protocol step into a semantic action graph, tracks operator gestures and reagent interactions through a Vision-Language Model (VLM), detects when execution diverges from the ground-truth procedure, and surfaces instant corrective guidance as spatial overlays — turning every researcher into a compliant, self-auditing one-person lab.
When to Use This Skill
Use this skill when any of the following conditions are present:
- Live XR-assisted experiments: An operator wearing a first-person XR headset is executing a wet-lab protocol (PCR, cell culture, CRISPR editing, RNA extraction, Western blot, etc.) and needs real-time step-by-step guidance or compliance validation.
- Protocol compliance auditing: A lab manager needs post-hoc or live documentation showing whether a protocol was followed exactly — including timing, reagent volumes, temperature set-points, and action sequence.
- Deviation interception: The agent must interrupt or warn the operator the moment a step is skipped, performed out of order, or executed with incorrect parameters (wrong pipette volume, wrong incubation time, incorrect tube labeling).
- Training and onboarding: A trainee is learning a complex protocol and requires spatial annotations, step-completion confirmations, and error explanations anchored to their field of view.
- GMP / GLP documentation: A regulated workflow (clinical sample processing, diagnostic assay) requires a timestamped, frame-accurate audit trail of every protocol action for regulatory submission.
- Remote expert supervision: A remote PI or supervisor needs a live or recorded feed where protocol adherence is automatically annotated so they can intervene selectively.
- Autonomous lab robot verification: A robotic arm (Opentrons, Hamilton) is executing the protocol and the XR feed from an overhead or wrist-mounted camera must be validated against the digital twin protocol in real time.
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.
- 9d ago First seen · 202 lines · 60 tokens per session scan A 85c5702b6f07
protocol_video_matching is a skill published in the GitHub repository AndyZhuang/Opentest (22 stars, last pushed 6mo ago), licensed MIT. It adds 60 tokens to every session and 3,120 once invoked, about $0.0003 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 2026-08-30.
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