Operator-ready prompt for reuse, tuning, and workspace runs.
This item is set up for developers who want to inspect the original language, fork it into Workspace, and adapt the evidence model without losing the source prompt structure.
Implementation handoffs, eval setup, and prompt tuning where you need the original structure intact.
Inspect first, copy once, then fork into Workspace when you want variants, notes, and model settings attached to the same run.
Swap domain facts, examples, and any hard-coded entities for your own context.
Tighten the evidence or verification requirement if this is headed toward production.
Decide which failure mode you want to evaluate first before you branch the prompt.
This prompt already carries implementation detail, tool context, and a final-output instruction. Keep that structure intact when you tune it, or your comparison runs get noisy fast.
Open this prompt inside Workspace when you want a live iteration loop.
Copy for quick reuse, or run it in Workspace to keep prompt variants, model settings, and prompt-history changes in one place.
Structured source with 1 active lines to adapt.
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Prompt content
Original prompt text with formatting preserved for inspection and clean copy.
Using CrewAI, define three agents: 'Linker Specialist', 'Antibody Engineer', and 'Qwen3_Scientific_Reviewer'. Assign the 'Reviewer' role to the Qwen 3 model. Ensure the 'Linker Specialist' focuses on cathepsin-B-cleavable chemistry. Provide the initialization code including 'from crewai import Agent, Task, Crew'.
Adaptation plan
Keep the source stable, then branch your edits in a predictable order so the next prompt run is easier to evaluate.
Hold the task contract and output shape stable so generated implementations remain comparable.
Update libraries, interfaces, and environment assumptions to match the stack you actually run.
Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.
Copy once for a pristine source snapshot, then move the prompt into Workspace when you want variants, run history, and side-by-side tuning without losing the original.
Prompt diagnostics
Quick signals for how structured this prompt already is and where adaptation work is likely to happen first.
This prompt already mixes executable detail with instructions, so the safest path is to tune examples and interfaces before you rewrite the overall scaffold.
Multi-Agent Antibody-Oligonucleotide Conjugate (AOC) Design with CrewAI & Qwen 3
Antibody-oligonucleotide conjugates (AOCs) are a rapidly evolving drug modality that combines the targeting precision of antibodies with the gene-silencing power of oligonucleotides. In this challenge, you will use CrewAI to orchestrate a collaborative team of AI agents to design a novel AOC. The team will consist of a Linker Chemist, a Target Biologist, and a Senior Peer Reviewer powered by the Qwen 3 model. Your task is to automate the selection of the optimal antibody-target pair and the chemical linker strategy (e.g., cleavable vs. non-cleavable) for a specific disease indication like Myotonic Dystrophy. The Qwen 3 agent will act as the 'Scientific Critic,' leveraging its high-reasoning capabilities to evaluate the safety and efficacy of the designs proposed by the other agents. The final output must be a comprehensive AOC Synthesis Protocol that details the conjugation site, the oligonucleotide sequence, and the predicted pharmacokinetic profile.
Use the challenge page to recover the original task boundaries before you tune the prompt. That keeps your variants grounded in the same evaluation target instead of drifting into a different problem.