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Architecture

Waggle is a monorepo with 28 packages under packages/ organized around a layered architecture: the memory substrate, agent intelligence, server API, and UI presentation. This document covers the package structure, data flow, and extension points.

Note (2026-04-30 monorepo migration): the persistent-memory substrate (mind/ + harvest/) moved out of @waggle/core into @waggle/hive-mind-core (packages/hive-mind-core/src/{mind,harvest}). The React UI is not a package — it lives in apps/web/src. There is no @waggle/ui package.

Package Overview

waggle-os/
  apps/
    web/            # Main web app UI (React 19 + Vite + Tailwind 4 + base-ui/react)
    www/            # Marketing site (Next.js)
    browser-ext/    # Browser extension (unpacked; not an npm workspace)
  packages/
    # Product packages (MIT)
    agent/          # Agent loop, tools, sub-agents, workflows, trust, hooks, personas, evolution
    core/           # Config, vault (secrets), cron, file store, telemetry, compliance/audit
    server/         # Fastify API server, local + team routes, daemons, KVARK client, scheduler
    shared/         # Shared types, Zod schemas, tiers, MCP catalog
    marketplace/    # Marketplace catalog, installer, security gate, sync
    optimizer/      # Prompt optimization (GEPA engine)
    weaver/         # Memory consolidation daemon
    waggle-dance/   # Swarm orchestration protocol
    worker/         # Background task processing (BullMQ)
    sdk/            # Plugin/skill SDK, capability packs, starter skills
    cli/            # Command-line REPL
    launcher/       # AI-tool launcher / dock backend
    admin-web/      # Admin dashboard for team deployments
    wiki-compiler/  # Knowledge / wiki compiler
    memory-mcp/     # MCP server exposing the memory substrate to external agents
    # Memory substrate — hive-mind-* (Apache-2.0), mirrored to marolinik/hive-mind
    hive-mind-core/         # The substrate: FrameStore, HybridSearch, KnowledgeGraph, Identity/Awareness, Harvest (src/mind + src/harvest)
    hive-mind-cli/          # CLI for the substrate
    hive-mind-mcp-server/   # MCP server for the substrate
    hive-mind-shim-core/    # Signal-emitter shim library
    hive-mind-wiki-compiler/# Wiki compiler (OSS)
    hive-mind-hooks-core/   # Shared hook library
    hive-mind-hooks-*/      # Per-tool capture hooks: claude-code, claude-desktop, codex,
                            #   codex-desktop, cursor, hermes, openclaw
  sidecar/          # Node.js sidecar for Tauri desktop app
  app/              # Tauri 2.0 desktop shell (Rust + WebView2) — loads the apps/web build

Package Details

@waggle/hive-mind-core

The persistent-memory substrate (Apache-2.0; mirrored to the public marolinik/hive-mind repo). Zero network dependencies; runs on SQLite + sqlite-vec.

  • MindDB (src/mind/db.ts, schema.ts): SQLite wrapper for .mind files. Tables for memory frames, knowledge-graph entities/relations, embeddings, sessions, and improvement signals.
  • FrameStore (src/mind/frames.ts): CRUD on memory frames with FTS5 full-text search, importance ranking, and access counting.
  • HybridSearch (src/mind/search.ts): vector + keyword retrieval, with an optional cross-encoder reranker.
  • KnowledgeGraph (src/mind/knowledge.ts): entity-relation graph with temporal validity (valid_from/valid_to).
  • IdentityLayer / AwarenessLayer (src/mind/identity.ts, awareness.ts): personal-identity persistence and active task/state tracking.
  • Embeddings (src/mind/*-embedder.ts): pluggable providers — in-process, Ollama, Voyage, OpenAI, mock.
  • Harvest (src/harvest/): conversation/file ingestion adapters (ChatGPT, Claude, Claude Code, Gemini, Perplexity, PDF, markdown, URL, plaintext) plus the dedup pipeline.

Develop the substrate here and mirror it out — never the reverse. See the "Memory Substrate Sync" section of the root CLAUDE.md.

@waggle/core

The foundation layer for the desktop/server runtime. Zero network dependencies.

  • WaggleConfig: Configuration management (~/.waggle/config.json). Provider keys, default model, team server config.
  • Vault: AES-256-GCM encrypted secret storage. Stores API keys, connector credentials, and sensitive metadata.
  • MultiMind: Manages personal + workspace minds simultaneously — routes searches to both and merges results. Wraps the @waggle/hive-mind-core substrate.
  • FileStore: Workspace filesystem access with a segment-boundary + symlink-aware containment guard and a secret deny-list (see the threat model).
  • CronStore: Schedule management for the cron service. CRUD on cron expressions with last/next run tracking.
  • ImportParser (memory-import.ts): parses ChatGPT and Claude export files into importable knowledge items.
  • InstallAudit: append-only capability-install trail (proposed / approved / installed / rejected / uninstalled) backing the EU-AI-Act provenance story.
  • Telemetry / Compliance: telemetry pipeline and compliance reporting (compliance/).

@waggle/agent

The intelligence layer. Orchestrates tool execution, sub-agents, and workflows.

  • AgentLoop: Core loop that sends messages to the LLM, parses tool calls, executes tools, and streams results. Supports up to 200 turns per conversation.
  • Tools (97+): Organized across 12 categories:
    • System tools: bash, read_file, write_file, edit_file, search_files, search_content, list_directory
    • Memory tools: search_memory, save_memory, forget_memory
    • Web tools: web_search, web_fetch
    • Git tools: git_status, git_diff, git_log, git_commit
    • Plan tools: create_plan, add_plan_step, execute_step, show_plan
    • Document tools: generate_docx
    • Sub-agent tools: spawn_agent, coordinate_agents
    • Skill tools: dynamically generated from installed skills
    • KVARK tools: kvark_search, kvark_ask_document, kvark_feedback, kvark_action
    • Team tools: request_team_capability, assign_task, update_task
    • Audit tools: audit_trail, trust_assessment
    • Connector tools: dynamically generated from connected services
  • CapabilityRouter: Routes user intents to the appropriate tool or workflow based on context.
  • WorkflowComposer: Dynamically composes multi-step workflows from templates.
  • Workflow Templates: research-team (parallel research), review-pair (draft + review), plan-execute (plan + execute steps).
  • SubagentOrchestrator: Manages sub-agent lifecycle -- spawning, monitoring, result collection.
  • CommandRegistry: Slash command registration and execution (14 commands).
  • HookRegistry: Event-driven hooks (before/after tool calls, session start/end, etc.).
  • Personas: 8 predefined agent configurations with system prompts and tool presets.
  • TrustModel: Assesses capability risk level, trust source, and approval class.
  • SkillRecommender: Context-aware skill suggestions based on conversation content.

@waggle/server

The API layer. Fastify server exposing 29 route modules.

  • Local Server (src/local/): Solo mode on localhost:3333. Routes for chat, workspaces, sessions, memory, settings, vault, skills, plugins, connectors, marketplace, cron, fleet, etc.
  • Team Server (src/routes/): Multi-user mode with PostgreSQL (Drizzle ORM), Redis, Clerk auth, and WebSocket presence.
  • SSE Streaming: Chat responses stream via Server-Sent Events.
  • Anthropic Proxy: Built-in /v1/chat/completions endpoint that translates OpenAI format to Anthropic API.
  • KVARK Client (src/kvark/): HTTP facade for enterprise retrieval. User-level Bearer tokens.
  • Daemons: Background processes (memory consolidation, proactive checks).
  • Scheduler (src/scheduler/): LocalScheduler that ticks cron schedules and dispatches jobs.
  • ConnectorRegistry: Registers and manages 29 native connectors. Generates agent tools from connected services.
  • Session Manager: Manages parallel workspace sessions for Mission Control.
  • Notification System: Event bus + SSE stream for real-time notifications (cron, approval, task, agent events).

apps/web (UI)

The React UI is an application, not a package — it lives in apps/web/src (React 19 + Vite + Tailwind 4 + base-ui/react). There is no @waggle/ui package. The desktop binary (app/) loads the apps/web build. Representative surfaces:

  • ChatArea: Main conversation interface with streaming, tool cards, approval gates, and file upload.
  • MemoryBrowser: Frame list with search, importance filters, and knowledge graph visualization.
  • WorkspaceHome: Context-rich home screen with summary, decisions, threads, and suggestions.
  • Settings: Tabbed settings (Models, Permissions, Vault, Appearance, Advanced).
  • Cockpit: System dashboard showing health, schedules, runtime stats, connectors, trust audit.
  • Capabilities: Skill/pack browser with install state and family grouping.
  • Events: Tool event log with grouping and completion animations.
  • Onboarding: First-run setup flow (API key, workspace creation, starter skills, import).

@waggle/marketplace

Marketplace infrastructure. SQLite-based catalog with FTS5 search.

  • MarketplaceDB: 120+ packages across skills, plugins, and MCP servers. Auto-seeded from bundled data.
  • MarketplaceInstaller: Install/uninstall with dependency tracking.
  • SecurityGate: Heuristic-based security scanner. Scans for dangerous patterns before install.
  • MarketplaceSync: Syncs catalog from configured sources.
  • Enterprise Packs: KVARK-dependent packs (only available with enterprise connection).

@waggle/waggle-dance

Swarm orchestration protocol for multi-agent coordination.

  • Protocol: Message types for task assignment, status updates, and result collection.
  • Dispatcher: Routes work to available agents based on capability and load.
  • HiveQuery: Broadcast queries across multiple agents for parallel investigation.

@waggle/worker

Background task processing for team mode.

  • BullMQ Integration: Redis-backed job queues.
  • Execution Strategies: Parallel (fan-out), sequential (pipeline), and coordinator (master-worker).
  • Agent Worker: Real runAgentLoop execution in background worker processes.

Data Flow

Chat Message Flow

User Input
  --> POST /api/chat (Fastify route)
    --> Workspace context loaded (memory, state, persona)
    --> System prompt composed (core + persona + skills + context)
    --> runAgentLoop() invoked
      --> LLM API call (Anthropic proxy or direct)
      --> Tool calls parsed and executed
        --> Approval gate check (if sensitive)
        --> Tool result returned
      --> Memory auto-save (decisions, facts, preferences)
      --> SSE events streamed to client
    --> Session persisted to .jsonl file
  --> UI renders streaming response

Memory Flow

Conversation
  --> Agent detects important information
  --> save_memory tool called
    --> FrameStore.add() writes to workspace .mind
    --> Embeddings generated (sqlite-vec)
    --> Knowledge graph updated (entity extraction)

Later search:
  --> search_memory tool called
  --> MultiMind.search() queries personal + workspace minds
  --> FTS5 + vector similarity results merged
  --> Top results injected into agent context

Workspace Startup Flow

Open workspace
  --> GET /api/workspaces/:id/context
    --> Load workspace mind (MindDB)
    --> Read recent memory frames
    --> Extract decisions from memories
    --> Read session files (titles, summaries)
    --> Extract progress items (tasks, completions, blockers)
    --> Build workspace state summary
    --> Generate contextual suggested prompts
  --> UI renders Home screen

Extension Points

Adding a New Tool

  1. Define the tool in the appropriate category under packages/agent/src/
  2. Follow the ToolDefinition interface: name, description, parameters (JSON Schema), handler function
  3. Register the tool in the agent's tool list
  4. If the tool is sensitive, add it to the approval gate check list

Adding a New Connector

  1. Implement the ConnectorCapability interface in packages/server/src/services/connectors/
  2. Define id, name, service, authType, connect(), healthCheck(), and generateTools()
  3. Register in packages/server/src/local/index.ts with connectorRegistry.register()
  4. The connector's tools are automatically available when credentials are in the vault

Adding a Skill

Create a markdown file in ~/.waggle/skills/. The skill content is appended to the agent's system prompt. Use YAML frontmatter for metadata:

---
name: my-skill
permissions:
  - read_file
  - web_search
---
# My Skill

Instructions for the agent...

Adding a Slash Command

  1. Create a CommandDefinition in packages/agent/src/commands/
  2. Implement name, aliases, description, usage, and handler
  3. Register with registry.register() in the appropriate registration function

Adding a Workflow Template

  1. Define a factory function that returns a WorkflowTemplate with steps
  2. Register in the WORKFLOW_TEMPLATES map in packages/agent/src/
  3. Each step defines a role, instructions, and optional tool restrictions

Storage Locations

Data Location Format
Personal memory ~/.waggle/default.mind SQLite
Workspace memory ~/.waggle/workspaces/{id}/workspace.mind SQLite
Sessions ~/.waggle/workspaces/{id}/sessions/*.jsonl JSON Lines
Tasks ~/.waggle/workspaces/{id}/tasks.jsonl JSON Lines
File registry ~/.waggle/workspaces/{id}/files.jsonl JSON Lines
Config ~/.waggle/config.json JSON
Vault ~/.waggle/vault.db SQLite (encrypted values)
Marketplace ~/.waggle/marketplace.db SQLite
Skills ~/.waggle/skills/*.md Markdown
Plugins ~/.waggle/plugins/ Package directories
Permissions ~/.waggle/permissions.json JSON

Security Model

  • Vault: AES-256-GCM encryption for all secrets. Keys never stored in plain text after vault migration.
  • Approval Gates: Sensitive tool executions require explicit user approval.
  • SecurityGate: Marketplace installs scanned for dangerous patterns. CRITICAL severity always blocked.
  • Content Hashing: SHA-256 hashes detect unauthorized skill modifications.
  • Audit Trail: Every capability install, uninstall, and security decision is recorded.
  • Input Validation: All route parameters validated against path traversal and injection.
  • YOLO Mode: Opt-in auto-approval, disabled by default.
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