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llm-wiki-all-in-one

Compile ingested sources into a cross-linked wiki with query and audit operations.

1|Updated May 19, 2026
Search Tags:#knowledge base#wiki compilation#semantic query#documentation linting#human feedback audits#web viewer deployment
One-click install
npx skills add https://github.com/igamenovoer/tool-skills --skill llm-wiki-all-in-one
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llm-wiki-all-in-one
Source: https://github.com/igamenovoer/tool-skills/tree/main/misc/llm-wiki-all-in-one
Command: npx skills add https://github.com/igamenovoer/tool-skills --skill llm-wiki-all-in-one

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Maintains a persistent, cross-linked knowledge base by compiling ingested sources into wiki pages, answering questions grounded in that wiki, and tracking AI mistakes through an anchored human feedback workflow.

Core Features & Use Cases

  • Builds a compiled wiki instead of ad-hoc RAG: ingests raw articles/papers to generate summaries, concept pages, entity pages, and a consolidated wiki/index.md.
  • Supports five core operations: compile, ingest, query, lint, and audit, with daily logs.
  • Turns feedback into durable corrections: routes human comments to audit/ and applies them during the audit operation using anchored text windows.

Quick Start

Use the llm-wiki-all-in-one skill to scaffold a new wiki, then ingest your first set of sources and ask it a question about the topic.

Frequently Asked Questions about llm-wiki-all-in-one

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

FAQPage Schema
How do I compile ingested articles and papers into a structured wiki?▼

To compile a structured wiki, ingest raw articles and papers to automatically generate summaries, concept pages, entity pages, and a consolidated index. This builds a persistent, cross-linked knowledge base instead of relying on ad-hoc retrieval.

What is the best way to track and correct AI mistakes in a knowledge base?▼

To track AI mistakes in a knowledge base, route human comments into an audit directory. The system applies these corrections during the audit operation using anchored text windows, turning feedback into durable wiki updates.

How do I query a compiled wiki grounded strictly in my own ingested sources?▼

You can query your compiled wiki by using the built-in query operation. It provides answers grounded strictly in the structured wiki pages generated from your ingested articles, papers, and web pages.

Can I deploy a local web viewer to browse my compiled wiki content?▼

Yes, you can deploy a local web viewer using the packaged assets provided. This allows you to browse your compiled wiki content and navigate the cross-linked knowledge base directly on your filesystem.

Does documentation linting work on wiki pages generated from PDFs?▼

Yes, documentation linting works on wiki pages generated from ingested PDFs. The lint operation enforces strict wiki layout conventions and deterministic filesystem operations across all compiled content.

When should I choose a compiled wiki over standard ad-hoc retrieval methods?▼

Choose a compiled wiki over ad-hoc retrieval when you need a persistent, cross-linked knowledge base. It compiles raw sources into structured pages and tracks human feedback, whereas standard retrieval lacks durable corrections.

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