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weave

Query and maintain a project's structured knowledge index with subcommands.

8|1|Updated Jan 24, 2026
Search Tags:#validation#provenance#data management#visualization#querying#knowledge index
One-click install
npx skills add https://github.com/Meme-Theory/meme-engine --skill weave-meme-theory
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: weave
Source: https://github.com/Meme-Theory/meme-engine/tree/main/plugins/research-clab/templates/skills/weave
Command: npx skills add https://github.com/Meme-Theory/meme-engine --skill weave-meme-theory

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill provides a comprehensive interface for querying, maintaining, and visualizing the structured knowledge index of a project, ensuring data integrity and accessibility.

Core Features & Use Cases

  • Knowledge Index Management: Rebuild, query, and validate the project's knowledge index stored in tools/knowledge-index.json.
  • Data Visualization: Generate various graphs and diagrams (topology, timeline, provenance, citations, gates) to understand project knowledge.
  • Use Case: After updating research findings, use /weave --update to rebuild the index, then /weave --trace "specific entity" to see its evidence chain and related information.

Quick Start

Use the weave skill to rebuild the project knowledge index.

Frequently Asked Questions about weave

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

FAQPage Schema
How do I query a project knowledge index to trace entity provenance?▼

Rebuild and validate the project knowledge index by running update operations through integrated Python scripts. This regenerates the structured data store and synchronizes the database to ensure data integrity and accessibility.

Can I generate data visualizations from a structured knowledge index?▼

The knowledge index supports validation operations to ensure data integrity, provenance analysis to trace evidence chains, and querying capabilities to extract specific entity relationships from the structured project data.

How do I rebuild and validate the knowledge index after updating research findings?▼

Use the update command to rebuild the project knowledge index stored in the JSON file, leveraging integrated Python scripts for index generation and database synchronization to maintain current data integrity.

What is the best way to maintain a project's structured knowledge index?▼

Maintain the knowledge index by using dedicated subcommands to rebuild, query, and validate the structured data store, ensuring ongoing data integrity and accessibility for project analysis and visualization.

Do I need Python scripts to generate and synchronize a knowledge index?▼

Yes, the index generation and database synchronization processes integrate directly with Python scripts to rebuild the structured knowledge index and maintain data consistency across the project.

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