Multi-Agent CLI Orchestration Research Platform
Project description
zwarm
Multi-agent CLI orchestration research platform. Coordinate multiple coding agents (Codex, Claude Code) with delegation, conversation, trajectory alignment, and automatic context management.
Key Features
- Multi-adapter support: Codex MCP, Claude Code adapters with unified interface
- Sync & async modes: Conversational (iterative refinement) or fire-and-forget
- Token tracking: Per-session token usage tracked and persisted for cost analysis
- Context compaction: Automatic LRU-style pruning when approaching context limits
- Trajectory watchers: Composable guardrails (progress, budget, scope, pattern, delegation)
- State persistence: Resume sessions, track history, replay events
- Weave integration: Full tracing and observability
Installation
# From the workspace (recommended during development)
cd /path/to/labs
uv sync
# Or install directly
uv pip install -e ./zwarm
Requirements:
- Python 3.13+
codexCLI installed (for Codex adapter)claudeCLI installed (for Claude Code adapter)
Quick Start
# 1. Initialize zwarm in your project
zwarm init
# 2. Test an executor directly
zwarm exec --task "What is 2+2?"
# 3. Run the orchestrator with a task
zwarm orchestrate --task "Create a hello world Python function"
# 4. Check state after running
zwarm status
# 5. View event history
zwarm history
Task Input Options
# Direct task
zwarm orchestrate --task "Build a REST API"
# From file
zwarm orchestrate --task-file task.md
# From stdin
echo "Fix the bug in auth.py" | zwarm orchestrate
Configuration
zwarm looks for configuration in this order:
--configflag (YAML file).zwarm/config.toml(created byzwarm init)config.tomlin working directory (legacy, for backwards compat)- Default settings
Minimal .zwarm/config.toml
[weave]
enabled = true
project = "your-wandb-entity/zwarm"
[executor]
adapter = "codex_mcp" # or "claude_code"
Environment Variables
# Weave tracing (optional but recommended)
export WEAVE_PROJECT="your-entity/zwarm"
# Executor authentication (required - set based on which adapter you use)
export OPENAI_API_KEY="sk-..." # Required for codex_mcp adapter
export ANTHROPIC_API_KEY="sk-ant-..." # Required for claude_code adapter
Important: The orchestrator agent runs with your credentials, but the executor adapters (Codex, Claude Code) need their own authentication. If executors fail with auth errors, check that the appropriate API key is set in your environment.
You can also put these in a .env file in your project root - zwarm will load it automatically.
Full Configuration Reference
# config.yaml
orchestrator:
lm: gpt-5-mini # Model for the orchestrator itself
max_steps: 100 # Maximum orchestrator steps
compaction: # Context window management
enabled: true
max_tokens: 100000 # Trigger compaction above this
threshold_pct: 0.85 # Compact at 85% of max
target_pct: 0.7 # Target 70% after compaction
keep_first_n: 2 # Always keep system + task
keep_last_n: 10 # Always keep recent context
executor:
adapter: codex_mcp # Default adapter: codex_mcp | claude_code
model: null # Model override (null = use adapter default)
# codex_mcp default: gpt-5.1-codex-mini
# claude_code default: claude-sonnet-4-5-20250514
sandbox: workspace-write # Codex sandbox mode
weave:
enabled: true
project: your-entity/zwarm
state_dir: .zwarm # State directory for sessions/events
watchers:
enabled: true
message_role: user # Role for nudge messages: user | assistant | system
watchers:
- name: progress
- name: budget
config:
max_steps: 50
max_sessions: 10
- name: delegation_reminder
config:
threshold: 10 # Nudge after N consecutive non-delegation calls
lookback: 30 # How many messages to check
- name: scope
config:
keywords: []
Adapters
zwarm supports multiple CLI coding agents through adapters. Each adapter wraps a different coding CLI and handles the mechanics of starting sessions, sending messages, and capturing responses.
Codex MCP (default)
Uses Codex via MCP server for true conversational sessions. This is the recommended adapter for iterative work where you need back-and-forth refinement.
# Sync mode (conversational)
zwarm exec --adapter codex_mcp --task "Add a login function"
# The orchestrator can have back-and-forth conversations
# using delegate() and converse() tools
| Setting | Value |
|---|---|
| Default model | gpt-5.1-codex-mini |
| Requires | codex CLI installed |
| Auth | OPENAI_API_KEY environment variable |
Claude Code
Uses Claude Code CLI for execution. Good alternative when you want Claude's capabilities.
zwarm exec --adapter claude_code --task "Fix the type errors"
| Setting | Value |
|---|---|
| Default model | claude-sonnet-4-5-20250514 |
| Requires | claude CLI installed and authenticated |
| Auth | ANTHROPIC_API_KEY or claude CLI auth |
Model Selection
Models are selected with this precedence (highest to lowest):
- Per-delegation override:
delegate(task="...", model="o3") - Config file:
executor.modelin config.toml or zwarm.yaml - Adapter default: Each adapter has a sensible default
# config.toml - override the default model
[executor]
adapter = "codex_mcp"
model = "gpt-5.1-codex-max" # Use the more capable model
# Or override per-execution
zwarm exec --model gpt-5.1-codex-max --task "Complex refactoring"
Watchers (Trajectory Alignment)
Watchers are composable guardrails that monitor agent behavior and can intervene when things go wrong.
Available Watchers
| Watcher | Description |
|---|---|
progress |
Detects stuck/spinning agents |
budget |
Monitors step/session limits (counts only active sessions) |
scope |
Detects scope creep from original task |
pattern |
Custom regex pattern matching |
quality |
Code quality checks |
delegation |
Ensures orchestrator delegates instead of writing code directly |
delegation_reminder |
Nudges after many consecutive non-delegation tool calls (default: 10) |
Enabling Watchers
# config.yaml
watchers:
enabled: true
message_role: user # How nudges appear: user | assistant | system
watchers:
- name: progress
config:
max_same_calls: 3 # Flag after 3 identical tool calls
- name: budget
config:
max_steps: 50
max_sessions: 10
- name: delegation_reminder
config:
threshold: 10 # Nudge after 10 non-delegation calls
- name: scope
config:
avoid_keywords:
- "refactor everything"
- "rewrite"
The message_role setting controls how watcher nudges are injected:
user(default): Appears as a user message - strong nudge, agent must respondassistant: Appears as a previous assistant thought - softer, agent can continuesystem: Appears as system instruction - authoritative guidance
Watcher Actions
Watchers can return different actions:
continue- Keep goingwarn- Log warning but continuepause- Pause for human reviewstop- Stop the orchestrator
Weave Integration
zwarm integrates with Weave for tracing and observability.
Enabling Weave
# Via environment variable
export WEAVE_PROJECT="your-entity/zwarm"
# Or via config.toml
[weave]
enabled = true
project = "your-entity/zwarm"
What Gets Traced
- Orchestrator
step()calls with tool inputs/outputs - Individual adapter calls (
_call_codex,_call_claude) - Delegation tools (
delegate,converse,end_session) - All tool executions
View traces at: https://wandb.ai/your-entity/zwarm/weave
CLI Reference
init
Initialize zwarm in a project directory.
zwarm init [OPTIONS]
Options:
-w, --working-dir PATH Working directory [default: .]
-y, --yes Accept defaults, no prompts
--with-project Also create zwarm.yaml project config
What it creates:
config.toml- User settings (Weave project, adapter preferences, watchers).zwarm/- State directory for sessions and eventszwarm.yaml(optional) - Project-specific task configuration
Examples:
# Interactive setup with prompts
zwarm init
# Non-interactive with defaults
zwarm init --yes
# Create project config too
zwarm init --with-project
# Initialize in a different directory
zwarm init --working-dir /path/to/project
orchestrate
Start an orchestrator session to delegate tasks.
zwarm orchestrate [OPTIONS]
Options:
-t, --task TEXT Task description
-f, --task-file PATH Read task from file
-c, --config PATH Config file (YAML)
--adapter TEXT Executor adapter override
--resume Resume from previous state
--set KEY=VALUE Override config values
exec
Run a single executor directly (for testing). This bypasses the orchestrator entirely and hits the adapter (Codex/Claude) immediately with your task - useful for verifying adapters work before running full orchestration.
zwarm exec [OPTIONS]
Options:
-t, --task TEXT Task to execute
--adapter TEXT Adapter to use [default: codex_mcp]
--model TEXT Model override
--mode [sync|async] Execution mode [default: sync]
Note: Unlike orchestrate, this does NOT use watchers, compaction, state persistence, or multi-step planning. It's a single direct call to the executor.
status
Show current orchestrator state.
zwarm status [OPTIONS]
Options:
--sessions Show session details
--tasks Show task details
--json Output as JSON
history
Show event history.
zwarm history [OPTIONS]
Options:
-n, --limit INTEGER Number of events [default: 20]
--session TEXT Filter by session ID
--json Output as JSON
configs
Manage configuration files.
zwarm configs list # List available configs
zwarm configs show NAME # Show config contents
clean
Clean up zwarm state (useful for starting fresh).
zwarm clean [OPTIONS]
Options:
--all Remove everything (events, sessions, state)
--events Remove only events
--sessions Remove only sessions
-y, --yes Skip confirmation prompt
Examples:
# Clean everything and start fresh
zwarm clean --all --yes
# Clean only events log
zwarm clean --events
Architecture
┌─────────────────────────────────────────────────────────┐
│ Orchestrator │
│ (Plans, delegates, supervises - does NOT write code) │
├─────────────────────────────────────────────────────────┤
│ Delegation Tools │
│ delegate() | converse() | check_session() | bash() │
└───────────────┬─────────────────────┬───────────────────┘
│ │
┌───────▼───────┐ ┌───────▼───────┐
│ Codex MCP │ │ Claude Code │
│ Adapter │ │ Adapter │
└───────┬───────┘ └───────┬───────┘
│ │
┌───────▼───────┐ ┌───────▼───────┐
│ codex │ │ claude │
│ mcp-server │ │ CLI │
└───────────────┘ └───────────────┘
Key Concepts
- Orchestrator: Plans and delegates but never writes code directly
- Executors: CLI agents (Codex, Claude) that do the actual coding
- Sessions: Conversations with executors (sync or async)
- Watchers: Trajectory aligners that monitor and intervene
State Management
All state and config is stored in flat files under .zwarm/:
.zwarm/
├── config.toml # Runtime settings (weave, adapter, watchers)
├── state.json # Current state
├── events.jsonl # Append-only event log
├── sessions/
│ └── <session-id>/
│ ├── messages.json # Conversation history
│ └── metadata.json # Session info
└── orchestrator/
└── messages.json # Orchestrator history (for resume)
Development
Running Tests
# Run all zwarm tests (68 tests)
uv run pytest src/zwarm/ -v
# Run specific test modules
uv run pytest src/zwarm/core/test_compact.py -v # Context compaction
uv run pytest src/zwarm/watchers/test_watchers.py -v # Watchers
uv run pytest src/zwarm/adapters/test_codex_mcp.py -v # Codex adapter
# Run integration tests (requires codex CLI)
uv run pytest -m integration
Project Structure
zwarm/
├── src/zwarm/
│ ├── adapters/ # Executor adapters
│ │ ├── base.py # ExecutorAdapter protocol
│ │ ├── codex_mcp.py # Codex MCP adapter (with token tracking)
│ │ └── claude_code.py # Claude Code adapter (with token tracking)
│ ├── cli/
│ │ └── main.py # Typer CLI
│ ├── core/
│ │ ├── compact.py # Context window compaction (LRU pruning)
│ │ ├── config.py # Configuration loading
│ │ ├── environment.py # OrchestratorEnv (progress display)
│ │ ├── models.py # ConversationSession, Message, Event, etc.
│ │ └── state.py # Flat-file state management
│ ├── tools/
│ │ └── delegation.py # delegate, converse, check_session, etc.
│ ├── watchers/
│ │ ├── base.py # Watcher protocol
│ │ ├── builtin.py # Built-in watchers (progress, budget, scope, etc.)
│ │ ├── registry.py # Watcher registration
│ │ └── manager.py # WatcherManager
│ ├── prompts/
│ │ └── orchestrator.py # Orchestrator system prompt
│ └── orchestrator.py # Main Orchestrator class
├── configs/ # Example configurations
├── README.md
└── pyproject.toml
Research Context
zwarm is a research platform exploring:
- Agent reliability - Can orchestrators reliably delegate and verify work?
- Agent meta-capability - Can agents effectively use other agents?
- Long-running agents - Can agents run for days, not hours?
See ZWARM_PLAN.md for detailed design documentation.
License
Research project - see repository license.
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