Agentplane

CLI-first operational workflows and evidence for AI agents.

Agentplane helps you route local agent work through tasks, plans, verification, context, recipes, and Git-visible evidence.

install -> init -> quickstart -> task -> verify -> acr

Operationalize AI-assisted engineering with reproducible local workflow records.

Install

npm i -g agentplane
agentplane init
agentplane quickstart
agentplane demo

Requirements: Node.js 24+, Git, and a local terminal.

What is Agentplane?

Agentplane is not another agent framework. It is the operational layer around AI agents: workflows, orchestration, local context, recipes, verification, task artifacts, and ACR evidence.

Use Agentplane when you want agent work to be debuggable, reproducible, observable, and safe to operate beyond a single chat session.

What Agentplane writes

agentplane init and task lifecycle commands create inspectable operational artifacts:

AGENTS.md or CLAUDE.md                 Repository policy gateway
.agentplane/WORKFLOW.md                Workflow/config contract
.agentplane/agents/                    Installed agent profiles
.agentplane/tasks/<task-id>/README.md  Task intent, plan, verification, rollback, findings
.agentplane/tasks/<task-id>/acr.json   Agent Change Record
.agentplane/tasks/<task-id>/pr/        branch_pr review artifacts when that mode is active

The default quickstart runs locally and writes local project artifacts. It does not require account creation. If you enable integrations that publish feedback or artifacts, the integration docs explain the destination and opt-in setting.

Agent Change Record

An Agent Change Record is a machine-readable record of AI-assisted engineering work. It captures task intent, workflow state, changed files, verification evidence, and review status.

agentplane acr generate <task-id> --work-commit HEAD --write
agentplane acr validate <task-id> --mode local
agentplane acr check <task-id> --mode ci
agentplane acr explain <task-id>

Schema: schemas/acr-v0.1.schema.json.

Local context

Local context is the operational knowledge an agent needs for a specific repository or workflow: conventions, constraints, current state, reusable notes, tool instructions, and run history.

context/raw/**              source material
context/wiki/**             maintained markdown wiki
context/facts/**/*.jsonl    sourced facts
context/graph/**/*.jsonl    entities and relationships
.agentplane/context/derived disposable generated projection

Initialize it with:

agentplane context init
agentplane context learn changes
agentplane context learn tasks --tag release --limit 20 --dry-run
agentplane context search "release checklist"
agentplane context check

The model matches the LLM Wiki pattern: raw sources stay immutable, the wiki accumulates synthesis, and schema/policy files tell agents how to maintain it. Agentplane adds task lifecycle, provenance, proposal-before-promotion, and verification gates so context updates remain reviewable.

Read Local context.

First local workflow

agentplane task begin "Inspect Agentplane artifacts" --tag docs --verify "agentplane task verify-show <task-id>"
agentplane task verify-show <task-id>
agentplane task complete <task-id> --result "Inspected generated artifacts" --commit <git-rev>

Agentplane is not

• a model provider;
• a prompt playground;
• a low-code chatbot builder;
• a replacement for every agent framework;
• a black-box runtime that hides operational state.

Agentplane is the local operational layer around agent workflows: tasks, plans, context, recipes, checks, ACRs, and artifacts.

Recipes

Recipes are reusable workflow overlays. Start with the task -> plan -> verify -> ACR flow first; add recipes when you want a repeatable TDD, security review, or documentation update loop.

• TDD recipe
• Security review recipe
• Docs update recipe

Who uses it

• Solo developers who want future-you to know why an agent changed 19 files.
• OSS maintainers who require agent-generated PRs to include task intent, plan, checks, and ACR.
• Engineering teams that make agent work follow a shared lifecycle before review.
• Platform and security teams that need local, inspectable, policy-aware, CI-gateable AI work.

DCO sign-off and multi-author commits are first-class. Agentplane-managed commits preserve DCO identity fallbacks so agent and human co-authoring stays compliant.

Using Agentplane in a real repo? Tell us in Discussions. We will add your story to docs/showcase.

Workflow modes

direct

Fast local loops in the current checkout. Use it for solo work, prototypes, and short tasks.

branch_pr

Per-task branches, worktrees, PR artifacts, and integration handoff. Use it for teams and stricter review boundaries.

Workflow guides

• Agentplane + Claude Code
• Agentplane + Codex
• Agentplane + Cursor
• Agentplane + Aider
• Agentplane + Hermes Kanban
• Agentplane + GitHub Actions
• Agentplane + branch_pr workflow

Documentation

• Overview
• Setup
• Workflow
• Task lifecycle
• Commands
• CLI reference
• Architecture
• CLI contract

Status

Contributing

Contributions are welcome. See CONTRIBUTING.md.

Help us ship this

If Agentplane saved you a bad merge, star the repo and drop a note in Discussions. It is the only growth signal we use.

Stargazers over time

License

MIT