A persistent, learning, multi-agent development environment built on Claude Code
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.
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.
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.
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 |
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.
You don't need to memorize slash commands. Just describe what you want naturally.
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
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| 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) |
| 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 |
| 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 |
| 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 →
# 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.tomlis inopc/. Always runuvcommands from theopc/directory.
| 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) |
cd Continuous-Claude-v3/opc
uv run python -m scripts.setup.wizard --uninstall
What it does
Preserves user data → Copies these back from the archive:
history.jsonl (your command history)
Safety Features
By default, CC-v3 runs PostgreSQL locally via Docker. For remote database setups:
# 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
vectortoshared_preload_librariesin DB Parameter Group - Supabase: Enable via Database Extensions page - Azure Database: Use Extensions pane to enable pgvector
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.
# Start Claude Code
claude
# Try a workflow
> /workflow
| 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 |
┌─────────────────────────────────────────────────────────────────────┐
│ 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 │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────┘
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 │ └─────────────────────────────────────────────────────────────────────────────┘
$ claude mcp add Continuous-Claude-v3 \
-- python -m otcore.mcp_server <graph>