Continuous-Claude-v3 README

The project's README from github.com/parcadei/Continuous-Claude-v3. As one markdown file: 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 sprawl. Every MCP, subscription, and tool you add promises improvement but risks breaking context, tools, or prompts through clashes.

Our approach:

The failure modes of complex systems are structurally invisible until they happen. A learning, context-efficient system doesn't prevent all failures—but it recovers and improves.


How to Talk to Claude

You don't need to memorize slash commands. Just describe what you want naturally.

The Skill Activation System

When you send a message, a hook injects context that tells Claude which skills and agents are relevant. Claude infers from a rule-based system and decides which tools to use.

> "Fix the login bug in auth.py"

🎯 SKILL ACTIVATION CHECK
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

⚠️ CRITICAL SKILLS (REQUIRED):
  → create_handoff

📚 RECOMMENDED SKILLS:
  → fix
  → debug

🤖 RECOMMENDED AGENTS (token-efficient):
  → debug-agent
  → scout

ACTION: Use Skill tool BEFORE responding
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Priority Levels

Level Meaning
⚠️ CRITICAL Must use (e.g., handoffs before ending session)
📚 RECOMMENDED Should use (e.g., workflow skills)
💡 SUGGESTED Consider using (e.g., optimization tools)
📌 OPTIONAL Nice to have (e.g., documentation helpers)

Natural Language Examples

What You Say What Activates
"Fix the broken login" /fix workflow → debug-agent, scout
"Build a user dashboard" /build workflow → plan-agent, kraken
"I want to understand this codebase" /explore + scout agent
"What could go wrong with this plan?" /premortem
"Help me figure out what I need" /discovery-interview
"Done for today" create_handoff (critical)
"Resume where we left off" resume_handoff
"Research auth patterns" oracle agent + perplexity
"Find all usages of this API" scout agent + ast-grep

Why This Approach?

Benefit How
More Discoverable Don't need to know commands exist
Context-Aware System knows when you're 90% through context
Reduces Cognitive Load Describe intent naturally, get curated suggestions
Power User Friendly Still supports /fix, /build, etc. directly

Skill vs Workflow vs Agent

Type Purpose Example
Skill Single-purpose tool commit, tldr-code, qlty-check
Workflow Multi-step process /fix (sleuth → premortem → kraken → commit)
Agent Specialized sub-session scout (exploration), oracle (research)

See detailed skill activation docs →


Quick Start

Prerequisites

Installation

# Clone
git clone https://github.com/parcadei/Continuous-Claude-v3.git
cd Continuous-Claude-v3/opc

# Run setup wizard (12 steps)
uv run python -m scripts.setup.wizard

Note: The pyproject.toml is in opc/. Always run uv commands from the opc/ directory.

What the Wizard Does

Step What It Does
1 Backup existing .claude/ config (if present)
2 Check prerequisites (Docker, Python, uv)
3-5 Database + API key configuration
6-7 Start Docker stack, run migrations
8 Install Claude Code integration (32 agents, 109 skills, 30 hooks)
9 Math features (SymPy, Z3, Pint - optional)
10 TLDR code analysis tool
11-12 Diagnostics tools + Loogle (optional)

To Uninstall:

cd Continuous-Claude-v3/opc
  uv run python -m scripts.setup.wizard --uninstall

What it does

  1. Archives your current setup → Moves ~/.claude to ~/.claude-v3.archived.
  2. Restores your backup → Finds the most recent ~/.claude.backup.* (created during install) and restores it
  3. Preserves user data → Copies these back from the archive:
  1. Removes CC-v3 additions → Everything else (hooks, skills, agents, rules)

Safety Features

Remote Database Setup

By default, CC-v3 runs PostgreSQL locally via Docker. For remote database setups:

1. Database Preparation

# Connect to your remote PostgreSQL instance
psql -h hostname -U user -d continuous_claude

# Enable pgvector extension (requires superuser or rds_superuser)
CREATE EXTENSION IF NOT EXISTS vector;

# Apply the schema (from your local clone)
psql -h hostname -U user -d continuous_claude -f docker/init-schema.sql

Managed PostgreSQL tips:

  • AWS RDS: Add vector to shared_preload_libraries in DB Parameter Group
  • Supabase: Enable via Database Extensions page
  • Azure Database: Use Extensions pane to enable pgvector

2. Connection Configuration

Set CONTINUOUS_CLAUDE_DB_URL in ~/.claude/settings.json:

{
  "env": {
    "CONTINUOUS_CLAUDE_DB_URL": "postgresql://user:password@hostname:5432/continuous_claude"
  }
}

Or export before running Claude:

export CONTINUOUS_CLAUDE_DB_URL="postgresql://user:password@hostname:5432/continuous_claude"
claude

See .env.example for all available environment variables.

First Session

# Start Claude Code
claude

# Try a workflow
> /workflow

First Session Commands

Command What it does
/workflow Goal-based routing (Research/Plan/Build/Fix)
/fix bug <description> Investigate and fix a bug
/build greenfield <feature> Build a new feature from scratch
/explore Understand the codebase
/premortem Risk analysis before implementation

Architecture

┌─────────────────────────────────────────────────────────────────────┐
│                        CONTINUOUS CLAUDE                            │
├─────────────────────────────────────────────────────────────────────┤
│                                                                     │
│  ┌─────────────┐    ┌─────────────┐    ┌─────────────┐             │
│  │   Skills    │    │   Agents    │    │    Hooks    │             │
│  │   (109)     │───▶│    (32)     │◀───│    (30)     │             │
│  └─────────────┘    └─────────────┘    └─────────────┘             │
│         │                  │                  │                     │
│         ▼                  ▼                  ▼                     │
│  ┌─────────────────────────────────────────────────────────────┐   │
│  │                     TLDR Code Analysis                       │   │
│  │   L1:AST → L2:CallGraph → L3:CFG → L4:DFG → L5:Slicing      │   │
│  │                    (95% token savings)                       │   │
│  └─────────────────────────────────────────────────────────────┘   │
│         │                  │                  │                     │
│         ▼                  ▼                  ▼                     │
│  ┌─────────────┐    ┌─────────────┐    ┌─────────────┐             │
│  │   Memory    │    │ Continuity  │    │ Coordination│             │
│  │   System    │    │   Ledgers   │    │    Layer    │             │
│  └─────────────┘    └─────────────┘    └─────────────┘             │
│                                                                     │
└─────────────────────────────────────────────────────────────────────┘

Data Flow: Session Lifecycle

SessionStart                    Working                      SessionEnd
    │                              │                             │
    ▼                              ▼                             ▼
┌─────────┐                  ┌─────────┐                   ┌─────────┐
│  Load   │                  │  Track  │                   │  Save   │
│ context │─────────────────▶│ changes │──────────────────▶│  state  │
└─────────┘                  └─────────┘                   └─────────┘
    │                              │                             │
    ├── Continuity ledger          ├── File claims               ├── Handoff
    ├── Memory recall              ├── TLDR indexing             ├── Learnings
    └── Symbol index               └── Blackboard                └── Outcome
                                         │
                                         ▼
                                    ┌─────────┐
                                    │ /clear  │
                                    │ Fresh   │
                                    │ context │
                                    └─────────┘

The Continuity Loop (Detailed)

┌─────────────────────────────────────────────────────────────────────────────┐
│                            THE CONTINUITY LOOP                              │
└─────────────────────────────────────────────────────────────────────────────┘

  1. SESSION START                     2. WORKING
  ┌────────────────────┐               ┌────────────────────┐
  │                    │               │                    │
  │  Ledger loaded ────┼──▶ Context    │  PostToolUse ──────┼──▶ Index handoffs
  │  Handoff loaded    │               │  UserPrompt ───────┼──▶ Skill hints
  │  Memory recalled   │               │  Edit tracking ────┼──▶ Dirty flag++
  │  TLDR cache warmed │               │  SubagentStop ─────┼──▶ Agent reports
  │                    │               │                    │
  └────────────────────┘               └────────────────────┘
           │                                    │
           │                                    ▼
           │                           ┌────────────────────┐
           │                           │ 3. PRE-COMPACT     │
           │                           │                    │
           │                           │  Auto-handoff ─────┼──▶ thoughts/shared/
           │                           │  (YAML format)     │    handoffs/*.yaml
           │                           │  Dirty > 20? ──────┼──▶ TLDR re-index
           │                           │                    │
           │                           └────────────────────┘
           │                                    │
           │                                    ▼
           │                           ┌────────────────────┐
           │                           │ 4. SESSION END     │
           │                           │                    │
           │                           │  Stale heartbeat ──┼──▶ Daemon wakes
           │                           │  Daemon spawns ────┼──▶ Headless Claude
           │                           │  Thinking blocks ──┼──▶ archival_memory
           │                           │                    │
           │                           └────────────────────┘
           │                                    │
           │                                    │
           └──────────────◀────── /clear ◀──────┘
                          Fresh context + state preserved

Workflow Chains

┌─────────────────────────────────────────────────────────────────────────────┐
│                           META-SKILL WORKFLOWS                              │
└─────────────────────────────────────────────────────────────────────────────┘

  /fix bug                              /build greenfield
  ─────────                             ─────────────────
  ┌──────────┐  ┌──────────┐            ┌──────────┐  ┌──────────┐
  │  sleuth  │─▶│ premortem│            │discovery │─▶│plan-agent│
  │(diagnose)│  │  (risk)  │            │(clarify) │  │ (design) │
  └──────────┘  └────┬─────┘            └──────────┘  └────┬─────┘
                     │                                      │
                     ▼                                      ▼
              ┌──────────┐                          ┌──────────┐
              │  kraken  │                          │ validate │
              │  (fix)   │                          │ (check)  │
              └────┬─────┘                          └────┬─────┘
                   │                                      │
                   ▼                                      ▼
              ┌──────────┐                          ┌──────────┐
              │  arbiter │                          │  kraken  │
              │ (test)   │                          │(implement│
              └────┬─────┘                          └────┬─────┘
                   │                                      │
                   ▼                                      ▼
              ┌──────────┐                          ┌─�

Continuous-Claude-v3 (parcadei/Continuous-Claude-v3)

Searching Database…

这是什么?Continuous Claude 是叠加在 Claude Code 之上的插件/环境,添加了持久记忆、节省上下文的交接和多代理编排,让 Claude 跨会话持续积累经验,而不是在上下文压缩时丢失信息。
这是独立应用,还是 Claude Code 的附加组件?它是装进现有 Claude Code 环境的附加组件,把 109 个技能、32 个代理和 30 个钩子打包放进 ~/.claude 目录,而不是作为单独的应用运行。
怎么把它跑起来?在 opc/ 目录下用 uv 包管理器运行安装向导;它会备份你现有的 .claude/ 配置,检查前置条件,建立数据库,启动 Docker 服务栈,执行迁移,然后安装 Claude Code 集成。
运行向导前需要装好什么?Python 3.11+、uv 包管理器、Docker(用于 PostgreSQL),以及 Claude Code CLI 本身。
以后想删掉怎么办?它有内置的卸载流程:先把当前的 ~/.claude 归档到带时间戳的文件夹,恢复最近一次安装前的备份,把历史记录、MCP 配置、API 密钥和项目数据复制回来,然后再移除新增的钩子/技能/代理。
必须用 Docker 里默认的本地 Postgres,还是可以用托管数据库?默认在 Docker 里本地运行 PostgreSQL,但也支持远程托管的 Postgres(AWS RDS、Supabase、Azure Database),只要该实例启用了 pgvector。
这需要付费的 API 订阅吗?没有必须付费的服务——Perplexity 和 NIA 集成是可选的附加功能,并非必需。
实际使用时怎么和它交互——斜杠命令还是自然语言?你可以用大白话描述需求(例如“修复登录故障”“今天就到这”),一个钩子会推断该激活哪些技能、代理或工作流;高手仍然可以使用 /fix、/build 这类明确的斜杠命令。
这里的技能(skill)、工作流(workflow)和代理(agent)有什么区别?技能是单一用途的工具(如 commit 或 tldr-code),工作流是多步骤的技能/代理链(如 /fix 依次运行 sleuth → premortem → kraken → commit),代理则是拥有隔离上下文的专职子会话(如负责探索的 scout 或负责调研的 oracle)。
它怎么避开 Claude Code 常见的上下文压缩问题?它用 YAML 交接在会话之间以更少的 token 传递上下文,还有记忆守护进程自动提炼经验,奉行“复利累积,而非压缩丢弃”(Compound, don't compact)的理念,而不是依赖有损的压缩。
TLDR 代码分析系统是干什么的?它是一套五层代码分析加语义索引,目的是避免在通读整个文件上烧 token,让 Claude 以精简的方式理解代码库。
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parcadei
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CommitJan 26
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