tool-preferences

Store user tool preferences for statistics, reference management, and literature databases.

Updated Mar 19, 2026

Search Tags:#python #libraries #statistics #databases #preferences #reference-management #writing-tools

Ready to run

npx skills add https://github.com/sencersoylu/scholar-flow --skill tool-preferences-sencersoylu

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tool-preferences
Source: https://github.com/sencersoylu/scholar-flow/tree/main/skills/profile/tool-preferences
Command: npx skills add https://github.com/sencersoylu/scholar-flow --skill tool-preferences-sencersoylu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps researchers align tool choices across statistics, literature management, and databases by centralizing preferences in a single configuration template that can be loaded by the agents to ensure consistent workflows.

Core Features & Use Cases

Preferences Template captures primary statistics tool, Python/R environment, libraries, a reference manager, database access preferences, and writing tool settings.
Agent Alignment ensures the Statistician, Literature Agent, and Citation Manager load identical tool configurations at activation for reproducible results.
Use Case: a research project auto-configures the toolchain for analysis, writing, and references based on the shared template.

Quick Start

Fill in the Preferences Template to configure your agents and save the settings.

Frequently Asked Questions about tool-preferences

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I configure research tool preferences for statistics and reference management?▼

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.

How does centralizing tool preferences improve research workflow reproducibility?▼

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.

Can I use this preferences template to manage both Python libraries and literature databases?▼

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.

What is the best way to align agent configurations for manuscript preparation and statistics?▼

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.

Do I need to manually set tool environments for each research agent or writing workflow?▼

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.

What settings limitations exist when storing export formats and reference manager configurations?▼

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.