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 dralkh/seerai --skill pylabrobotgit clone --depth 1 https://github.com/dralkh/seeraiWrote 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/dralkh/seerai/pylabrobot)<a href="https://agentmods.dev/skills/dralkh/seerai/pylabrobot"><img src="https://agentmods.dev/badge/skills/dralkh/seerai/pylabrobot/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/dralkh/seerai/pylabrobot"><img src="https://agentmods.dev/badge/skills/dralkh/seerai/pylabrobot.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 | $0.00073 | $0.01835 |
| Opus 5.5 | $0.00029 | $0.00734 |
| Sonnet 5.5 | $0.00015 | $0.00367 |
| Haiku 4.5 | $0.00007 | $0.00184 |
Grade A, and why
pylabrobot 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 24d 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.
This is a copy
97% identical to pylabrobot — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PyLabRobot
Overview
PyLabRobot is a hardware-agnostic, pure Python Software Development Kit for automated and autonomous laboratories. Use this skill to control liquid handling robots, plate readers, pumps, heater shakers, incubators, centrifuges, and other laboratory automation equipment through a unified Python interface that works across platforms (Windows, macOS, Linux).
When to Use This Skill
Use this skill when:
- Programming liquid handling robots (Hamilton STAR/STARlet, Opentrons OT-2, Tecan EVO)
- Automating laboratory workflows involving pipetting, sample preparation, or analytical measurements
- Managing deck layouts and laboratory resources (plates, tips, containers, troughs)
- Integrating multiple lab devices (liquid handlers, plate readers, heater shakers, pumps)
- Creating reproducible laboratory protocols with state management
- Simulating protocols before running on physical hardware
- Reading plates using BMG CLARIOstar or other supported plate readers
- Controlling temperature, shaking, centrifugation, or other material handling operations
- Working with laboratory automation in Python
Core Capabilities
PyLabRobot provides comprehensive laboratory automation through six main capability areas, each detailed in the references/ directory:
1. Liquid Handling (references/liquid-handling.md)
Control liquid handling robots for aspirating, dispensing, and transferring liquids. Key operations include:
- Basic Operations: Aspirate, dispense, transfer liquids between wells
- Tip Management: Pick up, drop, and track pipette tips automatically
- Advanced Techniques: Multi-channel pipetting, serial dilutions, plate replication
- Volume Tracking: Automatic tracking of liquid volumes in wells
- Hardware Support: Hamilton STAR/STARlet, Opentrons OT-2, Tecan EVO, and others
2. Resource Management (references/resources.md)
Manage laboratory resources in a hierarchical system:
- Resource Types: Plates, tip racks, troughs, tubes, carriers, and custom labware
- Deck Layout: Assign resources to deck positions with coordinate systems
- State Management: Track tip presence, liquid volumes, and resource states
- Serialization: Save and load deck layouts and states from JSON files
- Resource Discovery: Access wells, tips, and containers through intuitive APIs
What ships with it
6 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.
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.
- 24d ago First seen · 183 lines · 73 tokens per session scan A 38d3315b81e1
pylabrobot is a skill published in the GitHub repository dralkh/seerai (90 stars, last pushed 11d ago), licensed MIT. It adds 73 tokens to every session and 1,835 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to pylabrobot, differing in 10 lines, and is treated as a copy.
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