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Coding

A self-learning experience layer for AI coding assistants

Coding wraps around your AI coding assistant to capture conversations, build knowledge, prevent mistakes, and track progress - creating a continuously improving development environment.

VKB Knowledge Graph


What is Coding?

Coding is an infrastructure layer that enhances AI coding assistants by:

  • Capturing everything - Automatic session logging of all prompts, tool calls, and responses
  • Learning from experience - Build a knowledge base from your coding history and conversations
  • Preventing mistakes - Constraint system stops errors before they happen

System Architecture


Key Features

Live Session Logging (LSL)

Every conversation is captured automatically with intelligent 5-layer classification that routes content between projects.

LSL Sample Output

  • Real-time monitoring with zero data loss
  • Automatic redaction of secrets and credentials
  • Multi-project support with foreign session tracking
  • Configurable time-based slots (hourly files)

Learn more about LSL


Knowledge Management (UKB/VKB)

A 14-agent AI system extracts insights from your git history and conversation logs, building a searchable knowledge graph.

VKB Viewer — interactive knowledge graph with 281 entities across Project, Component, SubComponent, and Detail hierarchy

Update Knowledge Base (UKB):

ukb           # Incremental update from last checkpoint
ukb full      # Full analysis from first commit
ukb debug     # Single-stepping with mocked LLM

View Knowledge Base (VKB):

vkb           # Opens http://localhost:8080

Learn more about Knowledge Management


Constraint System

20+ configurable constraints enforce code quality via PreToolUse hooks - preventing mistakes before they happen.

Constraint Dashboard

  • Real-time violation detection and blocking
  • Web dashboard for monitoring and configuration
  • Per-project constraint configuration
  • Auto-correction suggestions

Learn more about Constraints


Health Monitoring

3-layer supervision architecture ensures system reliability with automatic recovery.

Health Dashboard

  • Process health monitoring with automatic restart
  • Service lifecycle management
  • Multi-agent workflow visualization
  • LLM call tracing (tokens, duration, costs)

Learn more about Health Monitoring


Status Line

Real-time feedback via the unified tmux status bar showing system health, costs, and development state. All coding agents (Claude, Copilot, OpenCode, Mastracode) are wrapped in tmux sessions with a shared status line rendered by combined-status-line.js.

Coding Environment — Tmux Status Bar

Indicator Meaning
Health icons Service status (green/red)
Cost display API usage tracking
LSL status Logging window and routing

Learn more about Status Line


Multi-Agent Support

While Claude Code is the primary and default agent, coding is fully agent-agnostic. Any coding assistant can be integrated with a single config file — no changes to shared code needed.

Agent Launch Status
Claude Code (default) coding or coding --claude Full MCP integration
GitHub Copilot CLI coding --copilot Pipe-pane I/O capture
OpenCode coding --opencode Pipe-pane I/O capture
Mastracode coding --mastra Lifecycle hook transcripts

All agents share the same infrastructure: tmux session wrapping, status line, health monitoring, LSL session logging, knowledge management, and constraint enforcement. Missing agent CLIs are auto-installed on first launch.

GitHub Copilot CLI running in coding

OpenCode running in coding

Mastracode running in coding

Agent Integration Guide


Quick Start

# Clone and install
git clone --recurse-submodules https://github.com/fwornle/coding ~/Agentic/coding
cd ~/Agentic/coding && ./install.sh

# Reload shell
source ~/.bashrc  # or ~/.zshrc

# Start coding with all features
coding

# View your knowledge graph
vkb

Coding Startup

Full Installation Guide


Design Principles

Principle Description
Agent-Agnostic Designed for any AI assistant — add a new agent with a single config file. Claude, CoPilot, OpenCode, and Mastracode integrated
Non-Intrusive Docker deployment keeps your system clean
Provider Flexible Works with Anthropic, OpenAI, Groq, and local LLMs (DMR/llama.cpp)
Multi-Project Handle multiple projects with automatic context routing
Multi-Developer Session logs tagged per user for collaboration
Self-Healing 3-layer supervision with automatic recovery

Feature Status

Feature Status Description
Live Session Logging Production Full session capture with 5-layer classification
Knowledge Base (UKB) Production 14-agent knowledge extraction system
Knowledge Viewer (VKB) Production Graph visualization and exploration
Constraint System Production 20+ constraints with web dashboard
Health Monitoring Production 3-layer supervision architecture
Status Line Production Real-time terminal feedback
Online Learning Beta Continuous learning without manual UKB

MCP Integrations

Coding provides several MCP (Model Context Protocol) servers:

Integration Purpose
Semantic Analysis 14-agent AI-powered code analysis
Constraint Monitor Real-time violation detection
Code Graph RAG AST-based code search via Memgraph

Documentation

  • Getting Started


    Installation, configuration, and first steps

    Get started

  • Core Systems


    LSL, UKB/VKB, Constraints, Observational Memory

    Explore

  • Integrations


    MCP servers and external tools

    View integrations

  • Guides


    Deep-dive tutorials and workflows

    Read guides