Agent Wave: orchestrate parallel git worktree workflow for AI agents.
Project description
Agent Wave (agvv)
agvv is a lightweight task orchestrator for coding agents.
It gives each task an isolated git worktree, runs the agent in a detached tmux session, and tracks lifecycle state in SQLite.
What It Does
- Isolates task changes with
git worktree(main+ per-feature worktrees). - Runs agent sessions in background
tmuxso work continues after terminal disconnect. - Persists task state/events in SQLite (
pending,running,done,failed,timed_out,cleaned). - Provides operational commands:
task run/status/retry/cleanupanddaemon run.
Requirements
- Python
>=3.10 gittmux- A coding agent CLI in
PATH:codex(default)claude(used when--agent claudeor--agent claude_code)
uv(recommended for install/run)
Agent provider note:
--agent claudeand--agent claude_codeare equivalent inputs.- Both normalize to the internal provider
claude_codeand invoke theclaudeCLI binary.
Install
From PyPI:
uv tool install agent-wave
agvv --help
From source:
uv sync --dev
uv run agvv --help
Quick Start
1) Create task.md
Write the detailed coding requirement in Markdown.
2) Create task.json
Minimal valid spec:
{
"project_name": "demo",
"feature": "feat_demo",
"task_doc": "./task.md"
}
task_doc or requirements must be present (at least one).
3) Start a task
For an existing local repository:
agvv task run --spec ./task.json --project-dir /path/to/repo
For a new managed project (under current directory):
agvv task run --spec ./task.json
Use Claude Code instead of Codex:
agvv task run --spec ./task.json --agent claude
--agent claude_code is also valid and behaves the same as --agent claude.
4) Monitor and reconcile state
agvv task status
agvv daemon run --once
Run daemon run --once repeatedly to move states forward (running -> done/timed_out).
5) Retry or cleanup
Retry:
agvv task retry --task-id <task_id>
Force restart an existing tmux session during retry:
agvv task retry --task-id <task_id> --force-restart
Cleanup worktree resources:
agvv task cleanup --task-id <task_id>
Force cleanup even with dirty worktree:
agvv task cleanup --task-id <task_id> --force
task.json Contract (CLI)
Required fields
project_name:^[A-Za-z0-9_-]+$feature:^[A-Za-z0-9_-]+$, and must not bemainorrepo.git- One of:
task_doc(must end with.md)requirements(non-empty string)
Common optional fields
repo: optional repository slug/identifierfrom_branch: base branch for feature worktree (default:main)session: custom tmux session nameticket: optional ticket identifier (for task metadata)constraints: list of extra constraintstimeout_minutes: session timeout in minutes (default:240)agent_extra_args: extra args passed to the agent command
Important runtime behavior
task_idis generated at runtime; user-providedtask_idis ignored.agent/agent_modelin spec are reset by runtime; choose provider via CLI--agent.base_dirin spec is overridden by runtime:- no
--project-dir: current working directory - with
--project-dir: parent directory of that project
- no
CLI Summary
agvv task run --spec <path> [--db-path <path>] [--agent <codex|claude|claude_code>] [--agent-non-interactive|--agent-interactive] [--project-dir <path>]
agvv task status [--db-path <path>] [--task-id <id>] [--state <pending|running|done|failed|timed_out|cleaned>]
agvv task retry --task-id <id> [--db-path <path>] [--session <name>] [--force-restart]
agvv task cleanup --task-id <id> [--db-path <path>] [--force]
agvv daemon run [--db-path <path>] [--once] [--interval-seconds <n>] [--max-loops <n>] [--max-workers <n>]
Data and Layout
- Default DB path:
~/.agvv/tasks.db - Override DB path with
--db-pathor environment variableAGVV_DB_PATH - Managed project layout:
<runtime_base>/<project_name>/
repo.git/ # bare repository
main/ # main worktree
<feature>/ # feature worktree for one task
Notes
daemon run --onceis required to reconcile background task state.task cleanupremoves the feature worktree and deletes the feature branch in managed repo.
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