Skip to content

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

License

Notifications You must be signed in to change notification settings

parcadei/Continuous-Claude-v3

Repository files navigation

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)

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│
              └────┬─────┘                          └────┬─────┘
                   │                                      │
                   ▼                                      ▼
              ┌──────────┐                          ┌──────────┐
              │  commit  │                          │  commit  │
              └──────────┘                          └──────────┘


  /tdd                                  /refactor
  ────                                  ─────────
  ┌──────────┐  ┌──────────┐            ┌──────────┐  ┌──────────┐
  │plan-agent│─▶│  arbiter │            │ phoenix  │─▶│  warden  │
  │ (design) │  │(tests 🔴)│            │(analyze) │  │ (review) │
  └──────────┘  └────┬─────┘            └──────────┘  └────┬─────┘
                     │                                      │
                     ▼                                      ▼
              ┌──────────┐                          ┌──────────┐
              │  kraken  │                          │  kraken  │
              │(code 🟢) │                          │(transform│
              └────┬─────┘                          └────┬─────┘
                   │                                      │
                   ▼                                      ▼
              ┌──────────┐                          ┌──────────┐
              │  arbiter │                          │  judge   │
              │(verify ✓)│                          │ (review) │
              └──────────┘                          └──────────┘

Data Layer Architecture

┌─────────────────────────────────────────────────────────────────────────────┐
│                           DATA LAYER ARCHITECTURE                           │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  TLDR 5-LAYER CODE ANALYSIS              SEMANTIC INDEX                     │
│  ┌────────────────────────┐              ┌────────────────────────┐         │
│  │ L1: AST (~500 tok)     │              │ BGE-large-en-v1.5      │         │
│  │     └── Functions,     │              │ ├── All 5 layers       │         │
│  │         classes, sigs  │              │ ├── 10 lines context   │         │
│  │                        │              │ └── FAISS index        │         │
│  │ L2: Call Graph (+440)  │              │                        │         │
│  │     └── Cross-file     │──────────────│ Query: "auth logic"    │         │
│  │         dependencies   │              │ Returns: ranked funcs  │         │
│  │                        │              └────────────────────────┘         │
│  │ L3: CFG (+110 tok)     │                                                 │
│  │     └── Control flow   │                                                 │
│  │                        │              MEMORY (PostgreSQL+pgvector)       │
│  │ L4: DFG (+130 tok)     │              ┌────────────────────────┐         │
│  │     └── Data flow      │              │ sessions (heartbeat)   │         │
│  │                        │              │ file_claims (locks)    │         │
│  │ L5: PDG (+150 tok)     │              │ archival_memory (BGE)  │         │
│  │     └── Slicing        │              │ handoffs (embeddings)  │         │
│  └────────────────────────┘              └────────────────────────┘         │
│         ~1,200 tokens                                                       │
│         vs 23,000 raw                                                       │
│         = 95% savings                    FILE SYSTEM                        │
│                                          ┌────────────────────────┐         │
│                                          │ thoughts/              │         │
│                                          │ ├── ledgers/           │         │
│                                          │ │   └── CONTINUITY_*.md│         │
│                                          │ └── shared/            │         │
│                                          │     ├── handoffs/*.yaml│         │
│                                          │     └── plans/*.md     │         │
│                                          │                        │         │
│                                          │ .tldr/                 │         │
│                                          │ └── (daemon cache)     │         │
│                                          └────────────────────────┘         │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

Core Systems

Skills System

Skills are modular capabilities triggered by natural language. Located in .claude/skills/.

Meta-Skills (Workflow Orchestrators)

Meta-Skill Chain Use When
/workflow Router → appropriate workflow Don't know where to start
/build discovery → plan → validate → implement → commit Building features
/fix sleuth → premortem → kraken → test → commit Fixing bugs
/tdd plan → arbiter (tests) → kraken (implement) → arbiter Test-first development
/refactor phoenix → plan → kraken → reviewer → arbiter Safe code transformation
/review parallel specialized reviews → synthesis Code review
/explore scout (quick/deep/architecture) Understand codebase
/security vulnerability scan → verification Security audits
/release audit → E2E → review → changelog Ship releases

Meta-Skill Reference

Each meta-skill supports modes, scopes, and flags. Type the skill alone (e.g., /build) to get an interactive question flow.

/build <mode> [options] [description]

Mode Chain Use For
greenfield discovery → plan → validate → implement → commit → PR New feature from scratch
brownfield onboard → research → plan → validate → implement Feature in existing codebase
tdd plan → test-first → implement Test-driven development
refactor impact analysis → plan → TDD → implement Safe refactoring
Option Effect
--skip-discovery Skip interview phase (have clear spec)
--skip-validate Skip plan validation
--skip-commit Don't auto-commit
--skip-pr Don't create PR description
--parallel Run research agents in parallel

/fix <scope> [options] [description]

Scope Chain Use For
bug debug → implement → test → commit General bug fix
hook debug-hooks → hook-developer → implement → test Hook issues
deps preflight → oracle → plan → implement → qlty Dependency errors
pr-comments github-search → research → plan → implement → commit PR feedback
Option Effect
--no-test Skip regression test
--dry-run Diagnose only, don't fix
--no-commit Don't auto-commit

/explore <depth> [options]

Depth Time What It Does
quick ~1 min tldr tree + structure overview
deep ~5 min onboard + tldr + research + documentation
architecture ~3 min tldr arch + call graph + layers
Option Effect
--focus "area" Focus on specific area (e.g., --focus "auth")
--output handoff Create handoff for implementation
--output doc Create documentation file
--entry "func" Start from specific entry point

/tdd, /refactor, /review, /security, /release

These follow their defined chains without mode flags. Just run:

/tdd "implement retry logic"
/refactor "extract auth module"
/review                           # reviews current changes
/security "authentication code"
/release v1.2.0

Key Skills (High-Value Tools)

Planning & Risk

  • premortem: TIGERS & ELEPHANTS risk analysis - use before any significant implementation
  • discovery-interview: Transform vague ideas into detailed specs

Context Management

  • create_handoff: Capture session state for transfer
  • resume_handoff: Resume from handoff with context
  • continuity_ledger: Track state within session

Code Analysis (95% Token Savings)

  • tldr-code: Call graph, CFG, DFG, slicing
  • ast-grep-find: Structural code search
  • morph-search: Fast text search (20x faster than grep)

Research

  • perplexity-search: AI-powered web search
  • nia-docs: Library documentation search
  • github-search: Search GitHub code/issues/PRs

Quality

  • qlty-check: 70+ linters, auto-fix
  • braintrust-analyze: Session analysis, replay, and debugging failed sessions

Math & Formal Proofs

  • math: Unified computation (SymPy, Z3, Pint) — one entry point for all math
  • prove: Lean4 theorem proving with 5-phase workflow (Research → Design → Test → Implement → Verify)
  • pint-compute: Unit-aware arithmetic and conversions
  • shapely-compute: Computational geometry

The /prove skill enables machine-verified proofs without learning Lean syntax. Used to create the first Lean formalization of Sylvester-Gallai theorem.

The Thought Process

What do I want to do?
├── Don't know → /workflow (guided router)
├── Building → /build greenfield or brownfield
├── Fixing → /fix bug
├── Understanding → /explore
├── Planning → premortem first, then plan-agent
├── Researching → oracle or perplexity-search
├── Reviewing → /review
├── Proving → /prove (Lean4 formal verification)
├── Computing → /math (SymPy, Z3, Pint)
└── Shipping → /release

See detailed skills breakdown →


Agents System

Agents are specialized AI workers spawned via the Task tool. Located in .claude/agents/.

Agent Categories (32 active)

Note: There are likely too many agents—consolidation is a v4 goal. Use what fits your workflow.

Orchestrators (2)

  • maestro: Multi-agent coordination with patterns (Pipeline, Swarm, Jury)
  • kraken: TDD implementation agent with checkpoint/resume support

Planners (4)

  • architect: Feature planning + API integration
  • phoenix: Refactoring + framework migration planning
  • plan-agent: Lightweight planning with research/MCP tools
  • validate-agent: Validate plans against best practices

Explorers (4)

  • scout: Codebase exploration (use instead of Explore)
  • oracle: External research (web, docs, APIs)
  • pathfinder: External repository analysis
  • research-codebase: Document codebase as-is

Implementers (3)

  • kraken: TDD implementation with strict test-first workflow
  • spark: Lightweight fixes and quick tweaks
  • agentica-agent: Build Python agents using Agentica SDK

Debuggers (3)

  • sleuth: General bug investigation and root cause
  • debug-agent: Issue investigation via logs/code search
  • profiler: Performance profiling and race conditions

Validators (2) - arbiter, atlas

Reviewers (6) - critic, judge, surveyor, liaison, plan-reviewer, review-agent

Specialized (8) - aegis, herald, scribe, chronicler, session-analyst, braintrust-analyst, memory-extractor, onboard

Common Workflows

Workflow Agent Chain
Feature architect → plan-reviewer → kraken → review-agent → arbiter
Refactoring phoenix → plan-reviewer → kraken → judge → arbiter
Bug Fix sleuth → spark/kraken → arbiter → scribe

See detailed agent guide →


Hooks System

Hooks intercept Claude Code at lifecycle points. Located in .claude/hooks/.

Hook Events (30 hooks total)

Event Key Hooks Purpose
SessionStart session-start-continuity, session-register, braintrust-tracing Load context, register session
PreToolUse tldr-read-enforcer, smart-search-router, tldr-context-inject, file-claims Token savings, search routing
PostToolUse post-edit-diagnostics, handoff-index, post-edit-notify Validation, indexing
PreCompact pre-compact-continuity Auto-save before compaction
UserPromptSubmit skill-activation-prompt, memory-awareness Skill hints, memory recall
SubagentStop subagent-stop-continuity Save agent state
SessionEnd session-end-cleanup, session-outcome Cleanup, extract learnings

Key Hooks

Hook Purpose
tldr-context-inject Adds code analysis to agent prompts
smart-search-router Routes grep to AST-grep when appropriate
post-edit-diagnostics Runs pyright/ruff after edits
memory-awareness Surfaces relevant learnings

See all 30 hooks →


TLDR Code Analysis

TLDR provides token-efficient code summaries through 5 analysis layers.

The 5-Layer Stack

Layer Name What it provides Tokens
L1 AST Functions, classes, signatures ~500 tokens
L2 Call Graph Who calls what (cross-file) +440 tokens
L3 CFG Control flow, complexity +110 tokens
L4 DFG Data flow, variable tracking +130 tokens
L5 PDG Program slicing, impact analysis +150 tokens

Total: ~1,200 tokens vs 23,000 raw = 95% savings

CLI Commands

# Structure analysis
tldr tree src/                      # File tree
tldr structure src/ --lang python   # Code structure (codemaps)

# Search and extraction
tldr search "process_data" src/     # Find code
tldr context process_data --project src/ --depth 2  # LLM-ready context

# Flow analysis
tldr cfg src/main.py main           # Control flow graph
tldr dfg src/main.py main           # Data flow graph
tldr slice src/main.py main 42      # What affects line 42?

# Codebase analysis
tldr impact process_data src/       # Who calls this function?
tldr dead src/                      # Find unreachable code
tldr arch src/                      # Detect architectural layers

# Semantic search (natural language)
tldr daemon semantic "find authentication logic"

Semantic Index

Beyond structural analysis, TLDR builds a semantic index of your codebase:

  • Natural language queries — Ask "where is error handling?" instead of grepping
  • Auto-rebuild — Dirty flag hook tracks file changes; index rebuilds after N edits
  • Selective indexing — Use .tldrignore to control what gets indexed
# .tldrignore example
__pycache__/
*.test.py
node_modules/
.venv/

The semantic index uses all 5 layers plus 10 lines of surrounding code context—not just docstrings.

Hook Integration

TLDR is automatically integrated via hooks:

  • tldr-read-enforcer: Returns L1+L2+L3 instead of full file reads
  • smart-search-router: Routes Grep to tldr search
  • post-tool-use-tracker: Updates indexes when files change

See TLDR documentation →


Memory System

Cross-session learning powered by PostgreSQL + pgvector.

How It Works

Session ends → Database detects stale heartbeat (>5 min)
            → Daemon spawns headless Claude (Sonnet)
            → Analyzes thinking blocks from session
            → Extracts learnings to archival_memory
            → Next session recalls relevant learnings

The key insight: thinking blocks contain the real reasoning—not just what Claude did, but why. The daemon extracts this automatically.

Conversational Interface

What You Say What Happens
"Remember that auth uses JWT" Stores learning with context
"Recall authentication patterns" Searches memory, surfaces matches
"What did we decide about X?" Implicit recall via memory-awareness hook

Database Schema (4 tables)

Table Purpose
sessions Cross-terminal awareness
file_claims Cross-terminal file locking
archival_memory Long-term learnings with BGE embeddings
handoffs Session handoffs with embeddings

Recall Commands

# Recall learnings (hybrid text + vector search)
cd opc && uv run python scripts/core/recall_learnings.py \
    --query "authentication patterns"

# Store a learning explicitly
cd opc && uv run python scripts/core/store_learning.py \
    --session-id "my-session" \
    --type WORKING_SOLUTION \
    --content "What I learned" \
    --confidence high

Automatic Memory

The memory-awareness hook surfaces relevant learnings when you send a message. You'll see MEMORY MATCH indicators—Claude can use these without you asking.


Continuity System

Preserve state across context clears and sessions.

Continuity Ledger

Within-session state tracking. Location: thoughts/ledgers/CONTINUITY_<topic>.md

# Session: feature-x
Updated: 2026-01-08

## Goal
Implement feature X with proper error handling

## Completed
- [x] Designed API schema
- [x] Implemented core logic

## In Progress
- [ ] Add error handling

## Blockers
- Need clarification on retry policy

Handoffs

Between-session knowledge transfer. Location: thoughts/shared/handoffs/<session>/

---
date: 2026-01-08T15:26:01+0000
session_name: feature-x
status: complete
---

# Handoff: Feature X Implementation

## Task(s)
| Task | Status |
|------|--------|
| Design API | Completed |
| Implement core | Completed |
| Error handling | Pending |

## Next Steps
1. Add retry logic to API calls
2. Write integration tests

Commands

Command Effect
"save state" Updates continuity ledger
"done for today" / /handoff Creates handoff document
"resume work" Loads latest handoff

Math System

Two capabilities: computation (SymPy, Z3, Pint) and formal verification (Lean4 + Mathlib).

The Stack

Tool Purpose Example
SymPy Symbolic math Solve equations, integrals, matrix operations
Z3 Constraint solving Prove inequalities, SAT problems
Pint Unit conversion Convert miles to km, dimensional analysis
Lean4 Formal proofs Machine-verified theorems
Mathlib 100K+ theorems Pre-formalized lemmas to build on
Loogle Type-aware search Find Mathlib lemmas by signature

Two Entry Points

Skill Use When
/math Computing, solving, calculating
/prove Formal verification, machine-checked proofs

/math Examples

# Solve equation
"Solve x² - 4 = 0"  →  x = ±2

# Compute eigenvalues
"Eigenvalues of [[2,1],[1,2]]"  →  {1: 1, 3: 1}

# Prove inequality
"Is x² + y² ≥ 2xy always true?"  →  PROVED (equals (x-y)²)

# Convert units
"26.2 miles to km"  →  42.16 km

/prove - Formal Verification

5-phase workflow for machine-verified proofs:

📚 RESEARCH → 🏗️ DESIGN → 🧪 TEST → ⚙️ IMPLEMENT → ✅ VERIFY
  1. Research: Search Mathlib with Loogle, find proof strategy
  2. Design: Create skeleton with sorry placeholders
  3. Test: Search for counterexamples before proving
  4. Implement: Fill sorries with compiler-in-the-loop feedback
  5. Verify: Audit axioms, confirm zero sorries
/prove every group homomorphism preserves identity
/prove continuous functions on compact sets are uniformly continuous

Achievement: Used to create the first Lean formalization of the Sylvester-Gallai theorem.

Prerequisites (Optional)

Math features require installation via wizard step 9:

# Installed automatically by wizard
uv pip install sympy z3-solver pint shapely

# Lean4 (for /prove)
curl https://raw.githubusercontent.com/leanprover/elan/master/elan-init.sh -sSf | sh

Workflows

/workflow - Goal-Based Router

> /workflow

? What's your goal?
  ○ Research - Understand codebase/docs
  ○ Plan - Design implementation approach
  ○ Build - Implement features
  ○ Fix - Investigate and resolve issues

/fix - Bug Resolution

/fix bug "login fails silently"

Chain: sleuth → [checkpoint] → [premortem] → kraken → test → commit

Scope What it does
bug General bug investigation
hook Hook-specific debugging
deps Dependency issues
pr-comments Address PR feedback

/build - Feature Development

/build greenfield "user dashboard"

Chain: discovery → plan → validate → implement → commit → PR

Mode What it does
greenfield New feature from scratch
brownfield Modify existing codebase
tdd Test-first development
refactor Safe code transformation

/premortem - Risk Analysis

/premortem deep thoughts/shared/plans/feature-x.md

Output:

  • TIGERS: Clear threats (HIGH/MEDIUM/LOW severity)
  • ELEPHANTS: Unspoken concerns

Blocks on HIGH severity until user accepts/mitigates risks.


Installation

Full Installation (Recommended)

# Clone
git clone https://github.com/parcadei/continuous-claude.git
cd continuous-claude/opc

# Run the setup wizard
uv run python -m scripts.setup.wizard

The wizard walks you through all configuration options interactively.

Updating

Pull latest changes and sync your installation:

cd continuous-claude/opc
uv run python -m scripts.setup.update

This will:

  • Pull latest from GitHub
  • Update hooks, skills, rules, agents
  • Upgrade TLDR if installed
  • Rebuild TypeScript hooks if changed

What Gets Installed

Component Location
Agents (32) ~/.claude/agents/
Skills (109) ~/.claude/skills/
Hooks (30) ~/.claude/hooks/
Rules ~/.claude/rules/
Scripts ~/.claude/scripts/
PostgreSQL Docker container

Installation Mode: Copy vs Symlink

The wizard offers two installation modes:

Mode How It Works Best For
Copy (default) Copies files from repo to ~/.claude/ End users, stable setup
Symlink Creates symlinks to repo files Contributors, development

Copy Mode (Default)

Files are copied from continuous-claude/.claude/ to ~/.claude/. Changes you make in ~/.claude/ are local only and will be overwritten on next update.

continuous-claude/.claude/  ──COPY──>  ~/.claude/
     (source)                          (user config)

Pros: Stable, isolated from repo changes Cons: Local changes lost on update, manual sync needed

Symlink Mode (Recommended for Contributors)

Creates symlinks so ~/.claude/ points directly to repo files. Changes in either location affect the same files.

~/.claude/rules  ──SYMLINK──>  continuous-claude/.claude/rules
~/.claude/skills ──SYMLINK──>  continuous-claude/.claude/skills
~/.claude/hooks  ──SYMLINK──>  continuous-claude/.claude/hooks
~/.claude/agents ──SYMLINK──>  continuous-claude/.claude/agents

Pros:

  • Changes auto-sync to repo (can git commit improvements)
  • No re-installation needed after git pull
  • Contribute back easily

Cons:

  • Breaking changes in repo affect your setup immediately
  • Need to manage git workflow

Switching to Symlink Mode

If you installed with copy mode and want to switch:

# Backup current config
mkdir -p ~/.claude/backups/$(date +%Y%m%d)
cp -r ~/.claude/{rules,skills,hooks,agents} ~/.claude/backups/$(date +%Y%m%d)/

# Verify backup succeeded before proceeding
ls -la ~/.claude/backups/$(date +%Y%m%d)/

# Remove copies (only after verifying backup above)
rm -rf ~/.claude/{rules,skills,hooks,agents}

# Create symlinks (adjust path to your repo location)
REPO="$HOME/continuous-claude"  # or wherever you cloned
ln -s "$REPO/.claude/rules" ~/.claude/rules
ln -s "$REPO/.claude/skills" ~/.claude/skills
ln -s "$REPO/.claude/hooks" ~/.claude/hooks
ln -s "$REPO/.claude/agents" ~/.claude/agents

# Verify
ls -la ~/.claude | grep -E "rules|skills|hooks|agents"

Windows users: Use PowerShell (as Administrator or with Developer Mode enabled):

# Enable Developer Mode first (Settings → Privacy & security → For developers)
# Or run PowerShell as Administrator

# Backup current config
$BackupDir = "$HOME\.claude\backups\$(Get-Date -Format 'yyyyMMdd')"
New-Item -ItemType Directory -Path $BackupDir -Force
Copy-Item -Recurse "$HOME\.claude\rules","$HOME\.claude\skills","$HOME\.claude\hooks","$HOME\.claude\agents" $BackupDir

# Verify backup succeeded before proceeding
Get-ChildItem $BackupDir

# Remove copies (only after verifying backup above)
Remove-Item -Recurse "$HOME\.claude\rules","$HOME\.claude\skills","$HOME\.claude\hooks","$HOME\.claude\agents"

# Create symlinks (adjust path to your repo location)
$REPO = "$HOME\continuous-claude"  # or wherever you cloned
New-Item -ItemType SymbolicLink -Path "$HOME\.claude\rules" -Target "$REPO\.claude\rules"
New-Item -ItemType SymbolicLink -Path "$HOME\.claude\skills" -Target "$REPO\.claude\skills"
New-Item -ItemType SymbolicLink -Path "$HOME\.claude\hooks" -Target "$REPO\.claude\hooks"
New-Item -ItemType SymbolicLink -Path "$HOME\.claude\agents" -Target "$REPO\.claude\agents"

# Verify
Get-ChildItem "$HOME\.claude" | Where-Object { $_.LinkType -eq "SymbolicLink" }

For Brownfield Projects

After installation, start Claude and run:

> /onboard

This analyzes the codebase and creates an initial continuity ledger.


Configuration

.claude/settings.json

Central configuration for hooks, tools, and workflows.

{
  "hooks": {
    "SessionStart": [...],
    "PreToolUse": [...],
    "PostToolUse": [...],
    "UserPromptSubmit": [...]
  }
}

.claude/skills/skill-rules.json

Skill activation triggers.

{
  "rules": [
    {
      "skill": "fix",
      "keywords": ["fix this", "broken", "not working"],
      "intentPatterns": ["fix.*(bug|issue|error)"]
    }
  ]
}

Environment Variables

Variable Purpose Required
DATABASE_URL PostgreSQL connection string Yes
BRAINTRUST_API_KEY Session tracing No
PERPLEXITY_API_KEY Web search No
NIA_API_KEY Documentation search No
CLAUDE_OPC_DIR Path to CC's opc/ directory (set by wizard) Auto
CLAUDE_PROJECT_DIR Current project directory (set by SessionStart hook) Auto

Services without API keys still work:

  • Continuity system (ledgers, handoffs)
  • TLDR code analysis
  • Local git operations
  • TDD workflow

Directory Structure

continuous-claude/
├── .claude/
│   ├── agents/           # 32 specialized AI agents
│   ├── hooks/            # 30 lifecycle hooks
│   │   ├── src/          # TypeScript source
│   │   └── dist/         # Compiled JavaScript
│   ├── skills/           # 109 modular capabilities
│   ├── rules/            # System policies
│   ├── scripts/          # Python utilities
│   └── settings.json     # Hook configuration
├── opc/
│   ├── packages/
│   │   └── tldr-code/    # 5-layer code analysis
│   ├── scripts/
│   │   ├── setup/        # Wizard, Docker, integration
│   │   └── core/         # recall_learnings, store_learning
│   └── docker/
│       └── init-schema.sql  # 4-table PostgreSQL schema
├── thoughts/
│   ├── ledgers/          # Continuity ledgers (CONTINUITY_*.md)
│   └── shared/
│       ├── handoffs/     # Session handoffs (*.yaml)
│       └── plans/        # Implementation plans
└── docs/                 # Documentation

Contributing

See CONTRIBUTING.md for guidelines on:

  • Adding new skills
  • Creating agents
  • Developing hooks
  • Extending TLDR

Acknowledgments

Patterns & Architecture

Tools & Services

  • uv - Python packaging
  • tree-sitter - Code parsing
  • Braintrust - LLM evaluation, logging, and session tracing
  • qlty - Universal code quality CLI (70+ linters)
  • ast-grep - AST-based code search and refactoring
  • Nia - Library documentation search
  • Morph - WarpGrep fast code search
  • Firecrawl - Web scraping API
  • RepoPrompt - Token-efficient codebase maps

Star History

Star History Chart


License

MIT - Use freely, contribute back.


Continuous Claude: Not just a coding assistant—a persistent, learning, multi-agent development environment that gets smarter with every session.

About

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

Topics

Resources

License

Contributing

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 13