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README

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: - Time, not money — No required paid services. Perplexity and NIA are optional, high-value-per-token. - Learn, don't accumulate — A system that learns handles edge cases better than one that collects plugins. - Shift-left validation — Hooks run pyright/ruff after edits, catching errors before tests.

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

  • Python 3.11+
  • uv package manager
  • Docker (for PostgreSQL)
  • Claude Code CLI

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:

  4. history.jsonl (your command history)

  5. mcp_config.json (MCP servers)
  6. .env (API keys)
  7. projects.json (project configs)
  8. file-history/ directory
  9. projects/ directory
  10. Removes CC-v3 additions → Everything else (hooks, skills, agents, rules)

Safety Features

  • Your current setup is archived with timestamp - nothing gets deleted
  • The wizard asks for confirmation before proceeding
  • It restores from the backup that was made during installation
  • All your Claude Code settings stay intact

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 │ │ │ │ └────────────────────┘ │ │ │ ▼ │ ┌────────────────────┐ │

Core symbols most depended-on inside this repo

parse_array
called by 399
opc/scripts/cc_math/math_base.py
print
called by 301
opc/scripts/setup/wizard.py
get_np
called by 157
opc/scripts/cc_math/numpy_compute.py
search
called by 156
opc/scripts/core/db/memory_protocol.py
parse_matrix
called by 114
opc/scripts/cc_math/math_base.py
execute
called by 58
opc/scripts/core/artifact_index.py
get_array_info
called by 47
opc/scripts/cc_math/math_base.py
get_headers
called by 44
opc/scripts/mcp/nia_docs.py

Shape

Function 1,369
Method 154
Route 141
Class 57

Languages

Python100%

Modules by API surface

opc/scripts/cc_math/scipy_compute.py345 symbols
opc/scripts/cc_math/mpmath_compute.py232 symbols
opc/scripts/cc_math/numpy_compute.py197 symbols
opc/scripts/cc_math/math_router.py115 symbols
opc/scripts/mcp/nia_docs.py51 symbols
opc/scripts/core/db/embedding_service.py49 symbols
opc/scripts/cc_math/sympy_compute.py41 symbols
opc/scripts/claude_spawn.py40 symbols
opc/scripts/core/db/memory_service_pg.py35 symbols
opc/scripts/cc_math/math_base.py33 symbols
opc/scripts/core/artifact_index.py31 symbols
opc/scripts/cc_math/math_tutor.py31 symbols

Dependencies from manifests, versioned

aiofiles23.0.0 · 1×
aiohttp3.13.2 · 1×
aiosqlite0.19.0 · 1×
asyncpg0.31.0 · 1×
autoevals0.0.90 · 1×
fastapi0.127.0 · 1×
feedparser6.0.12 · 1×
jq1.6.0 · 1×
matplotlib3.10.8 · 1×
mcp1.0.0 · 1×
mpmath1.3.0 · 1×
openai1.0.0 · 1×

Datastores touched

continuous_claudeDatabase · 1 repos
opcDatabase · 1 repos
postgresDatabase · 1 repos
agentica_memoryDatabase · 1 repos

For agents

$ claude mcp add Continuous-Claude-v3 \
  -- python -m otcore.mcp_server <graph>

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