robot_protocol_step_generator
Robot Protocol Step Generator
Overview
robot_protocol_step_generator bridges human-written protocol documentation and robot-executable code. It ingests natural language descriptions ("Add 50 µL of primer to each well in column A") or PDF/Markdown protocol text, parses them with LLM or rule-based extraction to identify liquid handling parameters (volume, source, destination, well layout), temperature settings, incubation durations, and transfer patterns, and emits either Python code for Opentrons Protocol API or PyLabRobot, or a structured JSON instruction list that can be executed by a generic robot controller. The skill enables rapid protocol translation from SOPs, protocols.io entries, or manuscript Methods sections into runnable automation — reducing the gap between written procedures and automated execution in the LabOS anywhere-lab vision.
When to Use This Skill
Use this skill when any of the following conditions are present:
- Protocol-to-robot translation: A researcher has a written protocol (PDF, Word, Markdown, protocols.io) and wants to run it on an Opentrons OT-2/Flex or PyLabRobot-compatible robot without manually writing Python.
- Natural language protocol input: The user describes a procedure in plain language — "transfer 100 µL from plate 1 column 1 to plate 2 column 1" — and the agent must generate executable steps.
- Methods section to automation: A manuscript Methods section or supplementary protocol is the source; the skill extracts the procedure and produces robot code for replication.
- Protocol variant generation: A base protocol exists; the user requests a variant (different volumes, different plate layout, different dilution scheme) and the skill generates the modified code.
- Deck layout inference: Protocol text describes reagents and plates; the skill infers a reasonable deck layout and labware positions for Opentrons/PyLabRobot.
- Serial dilution or plate replication: Complex patterns (e.g., "1:2 serial dilution across columns 1–8") are parsed and converted to loop-based or explicit transfer sequences.
- Multi-step protocol chaining: A protocol has distinct phases (PCR setup, thermocycling, cleanup); the skill produces a single Python file or JSON with ordered steps for each phase.
- Simulation-first workflow: Generate code for PyLabRobot ChatterboxBackend or Opentrons simulator to validate before running on physical hardware.
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