groundwork

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SUMMARY

A tool-agnostic workflow for building software with AI agents: spec → plan → test-first build loop → human-approved ship.

README.md

Groundwork

CI
npm
Docs
License: MIT

Spec, proof, approval. A workflow your AI agent can't skip.

Your agent writes the code. Groundwork is the project layer: it owns the spec, the cards, the
evidence and the approvals, so any session can pick up where the last one stopped.

An OpenCode session: /gw sets the project up, interviews for the spec, and writes the plan of cards.

cd your-project
npx groundwork-ai init

Needs Node.js 22+ and a git repo. Then open your AI tool and type /gw.
New to Groundwork? Read the 5-minute quickstart.

The problem

AI agents are fast and confident. Real projects need more: the chat fills up and the plan goes
with it, "done" is whatever the model says, and the rules you agreed yesterday are gone by
tomorrow. A week in, nobody can say what shipped, what's next, or why a choice was made.

Before and after

Without Groundwork
You:   Add voting to my book club app.
Agent: Done! A clean voting page with results and a summary.
You:   ... (Is it tested? What was I doing yesterday? Which parts moved?)
With Groundwork
You:   /gw I want a page where my book club votes on next month's book
Agent: A few specific questions: who can vote, one vote or rank several, hide results?
You:   Anyone with the link. One vote. Hide results until it closes.
Agent: Spec saved. Card 1.1: tests written, code passing, review passed.
       What changed: the home page lists this month's books.
       How to check: run npm run dev. Caveats: no styling yet.
You:   /gw-approve
Agent: Committed [1.1] Book list page. Next up: card 1.2 Voting.

The project survives the session, so the next session starts where this one stopped.

How it works

Three steps, one card at a time. Your main session is the runner: it hands each card to three
roles and stops at your door.

  1. Spec and plan. The agent asks specific questions, suggests the smallest useful version
    first, then writes phases and small cards. Stack choices are yours: options with trade-offs,
    and your pick is recorded.
  2. Build one card. The tester writes failing tests, the implementer makes them pass, and a
    reviewer with fresh context re-runs everything and checks every criterion. The proof is saved
    next to the card, with steps you can follow to check it yourself.
  3. You approve. Nothing is committed until you do, card by card or once per phase. When the
    same mistake happens twice it becomes a rule; if it still happens, a guard blocks it.
flowchart TD
  idea([Your idea]) --> spec[Spec<br/>a few specific questions]
  spec --> plan[Plan<br/>phases and small cards]
  plan --> card

  subgraph card [For each card]
    direction LR
    tester[Tester<br/>writes failing tests] --> impl[Implementer<br/>makes them pass]
    impl --> review[Reviewer<br/>checks the evidence]
    review -. sent back .-> impl
  end

  card --> approve{You approve?}
  approve -- yes --> commit([Committed, on to the next card])
  approve -. no, with a reason .-> card

  classDef you fill:#fef3c7,stroke:#d97706,color:#451a03
  classDef agent fill:#e0e7ff,stroke:#6366f1,color:#1e1b4b
  classDef done fill:#dcfce7,stroke:#16a34a,color:#052e16
  class idea,approve you
  class spec,plan,tester,impl,review agent
  class commit done
  style card fill:none,stroke:#94a3b8,stroke-dasharray:4 3

Read the deep version: the build loop and evidence and approval.

What's new in 0.7.0

  • A lighter runner. Each role gets a short hand-off, checks run once instead of between roles, and /gw-approve suggests a fresh session when a phase closes.
  • Roles keep their own records. The tester and implementer write their own History and call: lines on the card, and anything missing from the files counts as not agreed.
  • doctor reports startup cost. It shows what /gw and each role read before any code, flags long cards, and finds evidence saved as UTF-16.
  • OpenCode sessions start briefed. On OpenCode 2.x, every new session gets the handoff lines Claude Code shows at start.
  • Safer defaults. New projects start with the no-ai-trailers guard on, and evidence images are marked binary so git can't corrupt screenshots.
  • gw-ui-spec names what tests look for (an id, label or role), so testers don't guess selectors.

Full notes: the v0.7.0 release.

What it costs

Every session loads about 480 tokens of Groundwork files, and npx groundwork-ai doctor shows
your project's number. A card runs three fresh role sessions of about 9k tokens each, at $0.04 to
$0.13 per card on the calculator build. On a small app in one sitting, a plain chat is probably
cheaper; once a project outlives one context window the flat cost per card wins, and resuming the
finished calculator took 6.8x fewer tokens at $0.009, against $0.023 without Groundwork.
What it costs, and when it pays off.

Proof

Every number here comes from one recorded build. The calculator walkthrough has the sessions, transcripts and metrics, and the proof page has the charts.

Who it's for

  • Experienced developers. A real review step before anything merges, evidence saved in the repo, and guards for rules you are done repeating.
  • Early career, no senior around. Work one small card at a time, with a reviewer that catches what you would miss and proof you can point to.
  • Vibecoders. Answer a few questions, approve in plain English, and ship; small changes take the quick path and features get structure.

Honest comparison

Groundwork A raw agent session
Project state Files: spec, cards, handoff, decisions The chat scrollback
"Done" Evidence attached; approval refuses without it Whatever the model summarizes
Review A separate reviewer with fresh context, can't edit code The context that wrote it
Learning Repeated mistakes become rules, then guards Starts fresh every session
Resume Any session, tool or model continues from the handoff Re-explain everything

When not to use it: one-off scripts and throwaway experiments (ask your agent). Fully
autonomous overnight runs: Groundwork stops for you by design. Teams and pull-request flows: not
built yet. There are no benchmarks or evals; the claim is the mechanism, not a score.

Quickstart

The 5-minute quickstart goes from install to your first approval. These pages cover the rest:

Running npx groundwork-ai init: choosing a tool, then the files it creates and the next step.

FAQ

  • Does it work with an existing project? Yes. Setup maps the codebase, records what is already in use, and saves a test baseline so old failures don't block new work. Existing projects.
  • Can I use any AI tool? Any tool that reads files. Claude Code and OpenCode get native commands, subagents and guards; others follow the markdown.
  • What does it cost in context? About 480 tokens are always loaded; everything else loads when a step needs it, and npx groundwork-ai doctor shows your project's number.

More questions: the FAQ.

Contributing

Issues and pull requests are welcome. The docs live in docs/. Run npm test before opening a PR;
CI runs Windows and Linux on Node 22 and 24.

License

MIT

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