tool-preferences

You configure research tool preferences by filling in a structured template that stores your primary statistics tool, Python or R environment, libraries, reference manager, databases, and writing tool settings for consistent workflow alignment.

Centralizing tool preferences improves reproducibility by ensuring agents for statistics, literature review, and citation management load identical configurations at activation, maintaining consistent tool choices, environments, and export formats across research tasks.

Yes, the preferences template supports managing both Python libraries and literature databases, capturing primary statistics tools, environments, library dependencies, database access preferences, and reference manager settings within a single configuration file.

The best way to align agent configurations is saving a shared preferences template that specifies statistics tools, environments, reference managers, and writing tools, allowing agents to automatically load identical settings upon activation for manuscript preparation.

No, you do not need to manually set tool environments for each agent; filling the preferences template once auto-configures the toolchain for analysis, writing, and references, applying settings automatically across all activated research agents.

Settings are limited to the structured frontmatter fields provided, capturing primary statistics tools, environments, libraries, reference managers, database preferences, writing tools, and export formats, without supporting custom fields outside this template structure.