research-driven-development

Manage and document research processes for complex questions.

1|Updated Jul 7, 2026

Search Tags:#document generation #AI research #knowledge synthesis #research management #parallel research

Ready to run

npx skills add https://github.com/the-inconvenience-store/superbeads --skill research-driven-development

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: research-driven-development
Source: https://github.com/the-inconvenience-store/superbeads/tree/main/skills/research-driven-development
Command: npx skills add https://github.com/the-inconvenience-store/superbeads --skill research-driven-development

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill facilitates thorough research by organizing and documenting the process, ensuring no information is overlooked and all findings are preserved for future reference.

Core Features & Use Cases

Structured Research Process: Follows a defined 6-step process to scope, decompose, synthesize, write, and close research tasks.
Parallel Research Agents: Dispatches sub-agents for broad and focused research.
Persistent Documentation: Generates research documents with summaries, key findings, comparisons, and recommendations.

Quick Start

Use the research-driven-development skill to research the topic "AI coding agent practices".

Frequently Asked Questions about research-driven-development

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

FAQPage Schema

How do I manage and document the research process for complex technical questions?▼

To manage and document research, you can use a structured six-step process that scopes, decomposes, synthesizes, writes, and closes research tasks. This ensures all findings are preserved as persistent documentation in your docs directory.

What is the best way to synthesize knowledge from parallel research agents?▼

Synthesizing knowledge from parallel research agents involves dispatching sub-agents for broad and focused inquiries, then aggregating their findings. The process generates persistent documents with summaries, key findings, comparisons, and actionable recommendations.

How do I generate persistent documentation for AI research tasks?▼

Generating persistent documentation for AI research tasks requires writing the synthesized findings into a dedicated docs/research/ directory. This creates a permanent record with summaries, key findings, and recommendations for future reference.

Can I use parallel research agents to decompose broad knowledge inquiries?▼

Yes, you can use parallel research agents to decompose broad knowledge inquiries. The system triggers on research or planning prompts, dispatching focused sub-agents to ensure comprehensive coverage before synthesizing the results into a unified document.

Does research-driven development work without external dependencies?▼

Yes, research-driven development operates without external dependencies. It uses internal scripts, references, and assets to manage the entire six-step research workflow, from initial scoping to final document generation, entirely within your local environment.

When should I not use a structured research process for knowledge synthesis?▼

You should avoid using a structured research process for simple, single-query lookups that do not require persistent documentation. The overhead of dispatching parallel agents and following a six-step synthesis workflow is designed for complex, multi-faceted research tasks.