CLI-first operational workflows and traces for AI agents.
Agentplane helps you run local agent workflows, record traces, manage context, apply recipes, and keep agent work reproducible and inspectable.
install -> init -> run -> trace -> export
Build, run, trace, and operationalize AI agents with reproducible local workflows.
npm i -g agentplane
agentplane init
agentplane run ./agentplane.yaml
agentplane trace openRequirements: Node.js 24+, Git, and a local terminal.
Agentplane is not another agent framework. It is the operational layer around AI agents: workflows, orchestration, traces, local context, recipes, verification, and run artifacts.
Use Agentplane when you want agent work to be debuggable, reproducible, observable, and safe to operate beyond a single chat session.
agentplane init and local workflow runs create inspectable operational artifacts:
AGENTS.md Repository policy gateway
.agentplane/WORKFLOW.md Workflow contract
.agentplane/runs/<run-id>/ Run state
.agentplane/traces/<run-id>.json Trace spans
.agentplane/exports/<run-id>.json Exported artifacts
.agentplane/tasks/<task-id>/ Task state and evidence
.agentplane/tasks/<task-id>/acr.json Agent Change Record
The default quickstart runs locally and writes local project artifacts. It does not require account creation. If you enable integrations that publish feedback, traces, or artifacts, the integration docs explain the destination and opt-in setting.
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 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 checkThe 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.
agentplane run ./agentplane.yaml
agentplane trace list
agentplane trace export <run-id> --format json- 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: runs, traces, context, recipes, checks, exports, and artifacts.
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.
- 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.
Fast local loops in the current checkout. Use it for solo work, prototypes, and short tasks.
Per-task branches, worktrees, PR artifacts, and integration handoff. Use it for teams and stricter review boundaries.
- Agentplane + Claude Code
- Agentplane + Codex
- Agentplane + Cursor
- Agentplane + Aider
- Agentplane + GitHub Actions
- Agentplane + branch_pr workflow
Contributions are welcome. See CONTRIBUTING.md.
If Agentplane saved you a bad merge, star the repo and drop a note in Discussions. It is the only growth signal we use.
MIT