Autonomous Scientific Design
The evaluation will assess the agent system's ability to autonomously research, propose, simulate, and refine a scientific design (e.g., a hypothetical drug molecule or battery material) based on a given problem statement. Emphasis will be placed on the robustness of the LangGraph workflow, the efficacy of RAG, and the correct MCP tool integration.
Evaluation overview
How the linked challenge is judged: tasks, benchmarks, and criteria count.
Task templates
Inputs and expected outputs.
Autonomous Scientific Design
Evaluates the agent system's ability to propose a novel compound/material and simulate its properties based on provided literature and tools.
JSON with 'problem_statement': string, 'target_properties': dict (e.g., {'stability': 'high', 'toxicity': 'low'}), 'available_scientific_papers': list[string], 'mock_simulation_api_endpoint': string
JSON with 'proposed_design': string (e.g., SMILES string or material composition), 'simulated_properties': dict, 'reasoning_path': list[string] (LangGraph trace), 'final_analysis': string