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research-wiki

Maintains searchable record of project assets and locations in a centralized repository for reuse across workflows.

1|Updated Jul 21, 2026
Search Tags:#research#wiki#knowledge-graph#knowledge-base#llm-wiki#research-lifecycle
One-click install
npx skills add https://github.com/dogekiki/SP-test --skill research-wiki-dogekiki
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-wiki
Source: https://github.com/dogekiki/SP-test/tree/main/.trae/skills/research-wiki
Command: npx skills add https://github.com/dogekiki/SP-test --skill research-wiki-dogekiki

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the problem of fragmented research knowledge by creating a persistent, structured wiki that compounds over time, preventing the loss of insights from past papers, experiments, and failed ideas.

Core Features & Use Cases

  • Structured Knowledge Graph: Automatically tracks relationships between papers, ideas, experiments, and claims using a materialized edge graph.
  • Anti-Self-Poisoning: Implements rigorous capture hygiene to ensure only durable, high-quality research findings are stored, filtering out transient operational noise.
  • Context-Aware Synthesis: Generates a compressed, context-window-friendly query pack that provides the AI with a high-level summary of project gaps, failed ideas, and top papers for informed decision-making.

Quick Start

Initialize the research wiki for your current project by running the research-wiki init command.

Frequently Asked Questions about research-wiki

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

FAQPage Schema
How do I maintain a persistent knowledge base for my research project?▼

Build a persistent research knowledge base by tracking papers, ideas, and experiments through an automated graph-based relationship mapping system, ensuring research intelligence compounds securely across the project lifecycle.

What is the best way to map relationships between academic papers and experiments?▼

Automatically track relationships between papers, ideas, and experiments using a materialized edge graph that maps connections and maintains data integrity throughout the research lifecycle.

How do I prevent AI context window overload when summarizing research literature?▼

Generate compressed, context-window-friendly query packs providing high-level summaries of project gaps, failed ideas, and top papers to prevent AI context window overload during research synthesis.

How do I filter out transient noise when capturing research intelligence?▼

Implement rigorous capture hygiene and anti-self-poisoning protocols to filter transient operational noise, ensuring only durable, high-quality research findings are stored in the knowledge base.

Do I need Python to manage a structured research wiki?▼

Yes, a Python-based helper script is required to manage entity ingestion, edge creation, and health linting, ensuring data integrity within the structured research wiki.

How do I initialize a research wiki for my current project?▼

Run the research-wiki init command to initialize a persistent, structured wiki environment for your current project, enabling the accumulation of research intelligence across the project lifecycle.

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