CLAUDEMAX
Cognitive autopilot OS for Claude Code — adaptive task routing, persistent session memory, and visual state machine feedback on every prompt.
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CLAUDEMAX
A persistent cognitive operating system for Claude Code.
CLAUDEMAX transforms Claude Code from a stateless terminal assistant into a context-aware, self-routing, self-healing execution environment. Every prompt is classified, enriched, and executed through a defined pipeline. Memory accumulates across sessions via NotebookLM and LightRAG. Safety guards run on every write. The system operates without user intervention.
Architecture
CLAUDEMAX is composed of seven layers:
┌─────────────────────────────────────────────────────────────┐
│ LAYER 1 — Cognitive Router (UserPromptSubmit) │
│ Classifies prompt against 25 task types. Computes │
│ complexity score. Selects model tier. Emits routing │
│ directives: EXECUTE / SPAWN / THINK / AUTOCHAIN. │
│ Planning Gate enforces 5-step structured thinking. │
├─────────────────────────────────────────────────────────────┤
│ LAYER 2 — Safety Guards (PreToolUse) │
│ PII redactor: blocks API keys, tokens, wallet addresses. │
│ Code quality gate: rejects hardcoded secrets, empty catch. │
│ Runs on every Write / Edit / Bash invocation. │
├─────────────────────────────────────────────────────────────┤
│ LAYER 3 — Event Accumulator (PostToolUse) │
│ Writes structured tool events to turn-events.jsonl. │
│ Tool-specific failure detection (replaces blind regex). │
│ Forwards to daemon for long-term session memory. │
├─────────────────────────────────────────────────────────────┤
│ LAYER 4 — Completion Feedback (Stop) │
│ Reads accumulated events. Renders DONE diagram. │
│ Writes structured session summary to daemon. │
├─────────────────────────────────────────────────────────────┤
│ LAYER 5 — Session Context (SessionStart) │
│ Reads project memory from daemon + NLM notebook. │
│ Session intent prediction. Injects NLM-synthesized │
│ briefing. Starts Ruflo swarm engine. Status bar. │
├─────────────────────────────────────────────────────────────┤
│ LAYER 6 — NotebookLM + LightRAG (Core Memory) │
│ Per-project NLM notebooks auto-created on first session. │
│ LightRAG semantic search (sentence-transformers, │
│ all-MiniLM-L6-v2, 384-dim dense embeddings). │
│ NLM deep recall fallback when LightRAG returns weak. │
│ Cross-project knowledge graph. NLM auth auto-refresh │
│ via Chrome CDP. │
├─────────────────────────────────────────────────────────────┤
│ LAYER 7 — Anti-Laziness & Token Optimization │
│ NLM generates aggressive, task-specific directives. │
│ CLAUDE.md per-task segments (16 types, ~500 tokens). │
│ Master progress accumulator (infinite memory via NLM). │
│ 10-step precompute pipeline on session end. │
└─────────────────────────────────────────────────────────────┘
Core Components
- Ripple Autopilot — always-on router, prompt enrichment, model selection
- NotebookLM CLI — core memory layer, per-project notebooks, deep recall fallback
- LightRAG — semantic search with sentence-transformers (384-dim dense embeddings)
- Planning Gate — 5-step structured thinking on every prompt
- THINK directive — deep reasoning for complex tasks (>=50% complexity)
- AUTOCHAIN — full autopilot task execution without user intervention
- Anti-laziness enforcement — NLM-generated, aggressive, per-task-type directives
- Session intent prediction — predicts what the user will need before they ask
- Self-healing — tool-specific failure detection, 3-retry with learned strategies
- Status bar — model, context%, weekly limit%, real cost vs API cost
Key Features (v0.7.0)
Memory
- Per-project NLM notebooks auto-created on first session
- Master progress file accumulates decisions/patterns/failures across sessions
- Cross-project knowledge graph (scans gstack + Claude memory)
- NLM auth auto-refresh via Chrome CDP (no silent failures)
- Content-based vector dedup (eliminated 48% duplicates)
- 500-doc index cap with oldest-first pruning
- Type-aware memory pruning (50 sessions, 30 prompts, 10 decisions)
Token Optimization
- CLAUDE.md per-task segments (16 types, ~500 tokens vs ~6,000 full)
- Session briefing synthesized by NLM (87% token reduction)
- Learnings synthesized into 5 rules (96% token reduction)
- Prompt deduplication (stops echoing user prompt)
- Average tokens/prompt: ~478 (down from ~1,200-2,750)
Infrastructure
- 10-step precompute pipeline (background, on session end)
- Tool-specific failure detection (replaces blind regex)
- Shell injection fix (execSync to execFileSync with stdin)
- Session intent prediction
- Status bar with live metrics
Task Taxonomy
The cognitive router classifies prompts against 25 task types. See CLAUDE.md for the full taxonomy.
Entrepreneur: brain-dump, write-content, brainstorm, decide, research, strategy, pitch, fundraise, hire
Engineering: bug-fix, new-feature, deploy-ship, design, security, refactor, performance, investigate, planning, code-review, autoplan
Complexity scoring adjusts dynamically: repeat task types get +15%, large projects get +5%.
Install
curl -fsSL https://raw.githubusercontent.com/Blockchainpreneur/CLAUDEMAX/main/install.sh | bash
Or clone and run locally:
git clone https://github.com/Blockchainpreneur/CLAUDEMAX ~/claudemax
cd ~/claudemax && bash install.sh
Hook Pipeline
Event File Function
─────────────────────────────────────────────────────────────────────
PreToolUse pii-redactor.mjs Block secrets on Write/Edit/Bash
PreToolUse code-quality-gate.mjs Block hardcoded creds, warn on any/empty-catch
UserPromptSubmit rational-router-apex.mjs Classify → route → Planning Gate → directives
PostToolUse post-tool-use-apex.mjs Accumulate tool events, failure detection
Stop task-complete.mjs DONE diagram + structured session summary
Stop session-stop.mjs Post session end to memory daemon
SessionStart session-start.mjs Welcome panel + status bar
SessionStart session-start-daemon.mjs Inject NLM-synthesized project context
SessionStart ruflo daemon Start swarm engine (60+ agents)
All hooks exit 0 unconditionally. Claude never waits on them.
gstack — AI Software Factory (28 Skills)
Sprint workflow: /office-hours → /plan-ceo-review → /plan-eng-review → /plan-design-review → /design-consultation → /review → /investigate → /design-review → /qa → /qa-only → /cso → /ship → /land-and-deploy → /canary → /benchmark → /document-release → /retro
Power tools: /browse, /autoplan, /codex, /careful, /freeze, /unfreeze, /guard, /setup-deploy, /gstack-upgrade
Non-negotiable: never ship without /review + /qa + /cso. After deploy: /canary then /retro.
Memory System
Session memory stored at ~/.claudemax/contexts/{project-slug}.md. NotebookLM notebooks at ~/.claudemax/nlm/{project-slug}/. LightRAG index at ~/.claudemax/lightrag/.
The 10-step precompute pipeline runs on session end:
- Accumulate tool events → 2. Synthesize session summary → 3. Update NLM notebook → 4. Rebuild LightRAG index → 5. Deduplicate vectors → 6. Prune by type limits → 7. Generate anti-laziness directives → 8. Compress learnings → 9. Build per-task CLAUDE.md segments → 10. Update cross-project knowledge graph
MCP Servers
11 servers available. Use CLI tools first; MCP only when no CLI equivalent exists.
- context7 — live framework/library docs
- shadcn — UI component registry
- supabase — database, auth, storage
- github — PRs, issues, releases (prefer
ghCLI) - sentry — error monitoring
- figma — design file reading
- n8n — workflow automation
- magicuidesign — Magic UI components
- playwright — browser automation (prefer CLI)
- chrome-devtools — Chrome DevTools Protocol
- sequential-thinking — structured reasoning
Requirements
- macOS or Linux
- Node.js >= 18
- Claude Code CLI —
npm install -g @anthropic-ai/claude-code - Bun —
curl -fsSL https://bun.sh/install | bash - Python 3.10+ (for sentence-transformers / LightRAG)
License
MIT