尚未收集仓库信息。
尚未检测到更新。GitHub 发布版本后会显示在这里。
The first open-source harness builder for AI coding. Make AI coding deterministic and repeatable.
翻译准备中
正在加载完整 README。
查看完整 README ↗Archon is a factory builder. You describe how work should get done as YAML workflows, and Archon runs them with AI agents, scripts and your decisions in the places that need them. Software is the first factory: the bundled SDLC pack takes an issue to a merged pull request. The same engine runs any process you can describe.
Take yourself out of the loop and sit on top of it. Runs do the work, queues keep it moving, and a run comes to you only when it needs a decision you own.
Ask a coding agent to fix a bug and the result depends on the run. It may skip the plan, forget the tests or ignore your PR template. You end up supervising every step.
Archon turns your process into a workflow you own. The workflow fixes the steps, the checks and the gates. The agent supplies the judgment inside each step. That gives you:
A workflow is a graph of nodes. Agents judge, code computes, and you decide where it matters:
# .archon/workflows/build-feature.yaml
name: build-feature
description: Plan, implement until the tests pass, ask for approval, open the PR.
nodes:
- id: plan
prompt: "Read the request and the code. Write an implementation plan."
- id: implement
depends_on: [plan]
loop:
prompt: "Implement the next step of the plan."
until_bash: "bun run test" # your test command; code decides when it is done
max_iterations: 10
fresh_context: true
- id: approve
depends_on: [implement]
wait: # the run pauses and asks you
attention: "Review the change. Approve, or reject to stop."
form: approval
- id: stop
depends_on: [approve]
when: "$approve.output.decision == 'reject'"
cancel: "Rejected at review."
- id: pr
depends_on: [approve]
when: "$approve.output.decision == 'approve'"
prompt: "Push the branch and open a pull request."
flowchart LR
plan["plan<br/>(agent)"] --> implement["implement<br/>(agent, loops until the tests pass)"]
implement --> approve{"approve<br/>(waits for you)"}
approve -- reject --> stop["stop"]
approve -- approve --> pr["pr<br/>(agent)"]
Save it in your repository's .archon/workflows/, swap bun run test for your own test command, and run it:
archon workflow run build-feature "Add dark mode to the settings page"
Repository runs get their own git worktree by default, so several can work on one repository at once.
The bundled sdlc pack is a working factory for a repository:
archon-intake checks it against the current code and decides what it needs: a plan, an investigation, straight to delivery, or a maintainer's look.archon-build-queue claims the next ready issue, writes the brief and runs archon-ship: plan, implement, review through specialist lenses, fix the findings, wait for CI. It stops at a pull request whose review says Ready, asking once for any check no round can run, or at one a maintainer's ready answer hands on; the merge gate checks either the same way.archon-merge-queue merges the clear ready pull requests that merge cleanly, through a gate that checks the review verdict and CI at the head commit and that the base branch is not red. The queue judges open review threads itself and sends a pull request that conflicts back to the build queue.archon-discoveries reads what runs noticed outside their task and files it, tracks it on an existing issue, or drops it.Archon builds Archon: of the 524 pull requests merged into this repository between 1 and 19 October 2026, Archon runs built 363.
You start the queues by hand or bind them to a schedule or issue events with a trigger. The pack binds nothing by default. The pack reaches GitHub through the forge plugin (archon plugin add coleam00/Archon/plugins/forge-github); see the forge path. The SDLC factory introduces it and links its setup guide, and SDLC pack workflows describes every workflow in it.
Workflows are not tied to code. A node can be an agent prompt, a bash command, a script, a loop, a wait for a person or a child workflow, so any process with steps, checks and decisions fits: content production, research, operations, support. Write it as YAML, keep its commands and scripts beside it, and share it as a pack.
The core stays small: the workflow engine, isolation, durable state, the attention queue and an audit trail. Everything that talks to the outside world plugs in through a published contract, and you can build your own plugin for any of them:
以上为 README 的开头部分。其余内容请阅读原文。 查看完整 README ↗