10x-research

Name: 10x-research
Availability: InStock
Author: Kryptonum

Decompose codebase research questions into parallel sub-agent tasks with file:line evidence.

1|Updated Feb 26, 2025

Search Tags:#parallel agents #technical documentation #task orchestration #codebase research #file references #architecture mapping

Ready to run

npx skills add https://github.com/kryptonum-dev/fabryka-atrakcji --skill 10x-research

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: 10x-research
Source: https://github.com/kryptonum-dev/fabryka-atrakcji/tree/main/.agents/skills/10x-research
Command: npx skills add https://github.com/kryptonum-dev/fabryka-atrakcji --skill 10x-research

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you quickly understand an unfamiliar or complex codebase by producing a structured research output grounded in actual files and line-referenced findings.

Core Features & Use Cases

Parallel codebase research: Spawns multiple sub-agent tasks to explore structure, patterns, and relevant areas concurrently to reduce time-to-insight.
Evidence-based synthesis: Collects file:line references and connects findings across components into an actionable summary and detailed findings section.
Change-tracked research artifacts: Writes a self-contained research document into context/changes/<change-id>/research.md with consistent metadata, including commit/branch and repository context.

Quick Start

Provide your research question when prompted, and the Skill will research the codebase and generate a complete, referenced research document.

Frequently Asked Questions about 10x-research

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

FAQPage Schema

How do I map codebase architecture and trace implementation patterns?▼

To map codebase architecture, you can decompose technical questions into parallel sub-agent tasks that explore structure and trace patterns concurrently. This synthesizes file:line references into a structured research document with actionable findings.

What is the best way to research an unfamiliar codebase with evidence?▼

The best way to research an unfamiliar codebase is using parallel agents to concurrently explore structure, patterns, and integration points. This approach generates an evidence-based synthesis with specific file references rather than ungrounded summaries.

How do I generate technical documentation with file and line references?▼

You generate technical documentation with file references by orchestrating parallel research tasks across a repository. The process collects file:line evidence and writes a self-contained research artifact into a tracked changes folder.

Does this codebase research approach work for read-only exploration?▼

Yes, this codebase research approach requires read-only exploration tools to investigate the repository. It safely coordinates task tracking and resolves change folders outside archived paths without modifying the actual source code.

Can I use parallel agents for integration mapping across a repository?▼

Yes, you can use parallel agents for integration mapping across a repository. The task orchestration decomposes your question into concurrent sub-tasks that investigate integration points and synthesize findings into a frontmatter-rich research artifact.