tegwick 41773f1320 feat(llm): add OpenAI adapter, entity archive policy, process chapters 5-7
Add OpenAIAdapter for the OpenAI chat completions API (apikey-chatgpt.txt
or OPENAI_API_KEY). Set default model to arcee-ai/trinity-large-preview:free
for the infospace pipeline and increase max_tokens from 4096 to 8192.

Reprocess chapter 05 with Trinity Large (was Gemini: 1 truncated entity,
now 19 complete entities). Process chapters 06 (Aurora Alpha, 10 entities)
and 07 (Trinity Large, 15 entities including regenerated violent-policy.md).
Canonical set now at 85 unique entities.

Add entity archive policy: entities are never silently deleted. Retired
entities move to output/entities/archive/ with a dated reason header.
New CLI option: --archive-entity <slug> --reason "...". The --list
output shows the archive count alongside the canonical set.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-11 23:39:44 +01:00
2025-12-17 23:08:02 +01:00
2025-10-03 03:39:43 +02:00
2025-10-03 03:39:43 +02:00

MarkiTect Documentation

Welcome to the MarkiTect documentation. This directory contains comprehensive documentation for developers, users, and contributors.

Documentation Structure

📐 Architecture Documentation (architecture/)

Deep technical documentation about system design, performance, and implementation details.

  • Capabilities Architecture - Critical: How capabilities work as independent git submodules and separation of concerns
  • Caching System - Why and how MarkiTect's AST caching delivers 60-85% performance improvements
  • Coming soon: Database Schema, CLI Architecture

👥 User Guides (user-guides/)

End-user documentation for working with MarkiTect CLI and features.

  • Coming soon: Getting Started, Command Reference, Best Practices

🔧 Development Documentation (development/)

Documentation for contributors and developers extending MarkiTect.

  • Coming soon: Contributing Guide, Testing Strategy, Release Process

For Users

For Developers

Project Management

Key Concepts

Core Architecture Principles

  1. Parse Once, Use Many Times - AST caching for 60-85% performance improvement
  2. Convention Over Configuration - Sensible defaults with minimal setup
  3. Schema-Driven Processing - Structured markdown with validation
  4. Relational Metadata - Database-powered document relationships

Performance Philosophy

MarkiTect treats markdown documents as structured, queryable data rather than plain text. This approach enables:

  • Lightning-fast document processing through intelligent caching
  • Complex querying and relationship management
  • Schema validation and consistency enforcement
  • Scalable performance that grows with your content

Contributing to Documentation

Documentation follows the same quality standards as code:

  1. Clear Structure - Logical organization and navigation
  2. Practical Examples - Real-world usage patterns
  3. Performance Context - Why architectural decisions matter
  4. User-Focused - Written for the intended audience

Documentation Standards

  • Use clear, concise language
  • Include practical examples
  • Explain the "why" behind design decisions
  • Keep technical accuracy as the highest priority
  • Update docs when changing functionality

This documentation is maintained alongside the codebase. For the most current information, always refer to the latest version in the repository.

Description
An advanced markdown engine
https://coulomb.social/open/MarkiTect
Readme 34 MiB
2025-11-08 20:34:42 +00:00
Languages
Python 84.7%
JavaScript 8%
HTML 5.6%
Makefile 1.3%
Shell 0.2%
Other 0.1%