Coscientist

Overview

Coscientist’s repository is presented as supporting information for the article Autonomous chemical research with large language models, by Daniil A. Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes. It combines a directory identified as a simple implementation of Coscientist with data organized around specific article sections and figures. Its documented role is therefore both an implementation reference and a companion collection for examining the research, rather than a fully specified laboratory automation product.

The README maps synthesis_capabilities to the article’s discussion of web-search-assisted synthesis planning. It identifies large_library_selections as data for Figure 5e and multiple_runs_and_justifications as data for Figures 5f and 5g. The optimization directory contains data associated with the article’s treatment of reasoning through optimization problems. These mappings provide a useful starting point for selecting research material by topic and connecting it to the corresponding article discussion.

For implementation-oriented work, simple_implementation is the documented entry point. However, the source excerpts do not describe its input schema, generated outputs, dependencies, model configuration or execution procedure. They also do not establish instrument integration, operational readiness or quantitative performance. Evaluation should begin by inspecting the relevant files and their requirements, without treating the repository’s directory descriptions as proof of reproducibility. The repository code licence includes a Commons Clause condition in addition to Apache 2.0, so it should not be described as unrestricted Apache-licensed software.

Key Features

• Includes `simple_implementation`, identified in the README as a simple implementation of Coscientist.
• Organizes synthesis-planning research data in `synthesis_capabilities`, linked to the article’s web-search discussion.
• Provides `large_library_selections` data associated with Figure 5e.
• Provides `multiple_runs_and_justifications` data associated with Figures 5f and 5g.
• Includes `optimization` data tied to the article’s discussion of reasoning through optimization problems.

Use Cases

• Suggested evaluation: inspect `simple_implementation` to assess its suitability as a reference for a language-model-driven chemistry research workflow.
• Suggested evaluation: examine `synthesis_capabilities` alongside the corresponding article section to study the documented role of web search in synthesis planning.
• Suggested evaluation: use the figure-linked selection and repeated-run datasets to structure an analysis of the article’s examples and justifications.
• Suggested evaluation: inspect `optimization` to identify the problems and records available for a locally designed reasoning evaluation.

How to Use

1. Read the official README to establish the repository’s supporting-information role and select the article section or figure relevant to your question.
2. Open the repository and inspect simple_implementation if your goal is implementation evaluation. Identify any file-level instructions, input requirements and dependencies before attempting execution; these are not specified in the project README.
3. Choose the corresponding data directory: synthesis_capabilities, large_library_selections, multiple_runs_and_justifications or optimization. Examine the available formats and records before designing an analysis.
4. Define an evaluation question and document which files you use. Keep observations from your own inspection separate from claims made in the article; the source excerpts contain no numerical performance results.
5. Review the code licence before reuse or redistribution, paying particular attention to the Commons Clause condition.