Continuous-Claude-v3

by parcadei

Pending

Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows.

3,462stars
266forks
Python
Added 1/10/2026
AI Agentsagentsclaude-codeclaude-code-cliclaude-code-hooksclaude-code-mcpclaude-code-skillsclaude-code-subagentsclaude-skillsmcp
Installation
# Add to your Claude Code skills
git clone https://github.com/parcadei/Continuous-Claude-v3
README.md

Continuous Claude

A persistent, learning, multi-agent development environment built on Claude Code

License: MIT Claude Code Skills Agents Hooks

Continuous Claude transforms Claude Code into a continuously learning system that maintains context across sessions, orchestrates specialized agents, and eliminates wasting tokens through intelligent code analysis.

Table of Contents


Why Continuous Claude?

Claude Code has a compaction problem: when context fills up, the system compacts your conversation, losing nuanced understanding and decisions made during the session.

Continuous Claude solves this with:

| Problem | Solution | |---------|----------| | Context loss on compaction | YAML handoffs - more token-efficient transfer | | Starting fresh each session | Memory system recalls + daemon auto-extracts learnings | | Reading entire files burns tokens | 5-layer code analysis + semantic index | | Complex tasks need coordination | Meta-skills orchestrate agent workflows | | Repeating workflows manually | 109 skills with natural language triggers |

The mantra: Compound, don't compact. Extract learnings automatically, then start fresh with full context.

Why "Continuous"? Why "Compounding"?

The name is a pun. Continuous because Claude maintains state across sessions. Compounding because each session makes the system smarter—learnings accumulate like compound interest.


Design Principles

An agent is five things: Prompt + Tools + Context + Memory + Model.

| Component | What We Optimize | |-----------|------------------| | Prompt | Skills inject relevant context; hooks add system reminders | | Tools | TLDR reduces tokens; agents parallelize work | | Context | Not just what Claude knows, but how it's provided | | Memory | Daemon extracts learnings; recall surfaces them | | Model | Becomes swappable when the other four are solid |

Anti-Complexity

We resist plugin ...