Check what your AI agent actually did

Your AI agent says it's done. You gave it the job so you wouldn't have to do it, and now you're checking its work, which is the job. We're building Excellent to take on that check: establish what the agent actually did and how it compares with what you asked.

Excellent is being built for independent verification of AI-agent work. The intended workflow connects the task, the checks, the evidence and the result, so you can inspect what was established and what remains unresolved. The published CLI, version 0.1.0, provides repository setup and a separate-agent review gate. It does not yet include the wider verification workflow described below.

Why we're building it

AI agents can produce more work than people can carefully review. That's the point, and the problem. A wrong "done" looks exactly like a right one.

The easy fix is to ask another model whether the first one did a good job. That helps. But it's still a model reading a claim, and the gap stays open.

The planned workflow starts with independent observations. The repo, the tests, the build and the browser can each tell you something real about the result, within the limits of the checks connected to the task.

Software comes first because it leaves unusually good evidence. The question is the same for a refund, a booking or an email: what would show it was done?

The planned verification workflow

This is the intended v1 workflow our docs describe. The verification rules explain the supported checks and their limits. The published CLI predates this workflow; its current capabilities are listed below.

• Run. Every attempt starts on the record. Its agent, model, task and repo are captured before the work begins.
• Check. Excellent saves the result as it was handed in. Then it gathers evidence from the repo and the tools connected to the task: the git tree, the test runner, the build, the browser, CI. If a check can't run, Excellent says so. It won't quietly call that a pass.
• Return. Wrong work comes back with the unmet check, what was expected and what was observed. The next attempt starts from that evidence instead of a fresh prompt.
• Receipt. Accepted work leaves a receipt: signed, append-only and kept on your machine. A retry is a new attempt. The first one doesn't get rewritten.

The design keeps verification separate from the agent doing the work. Deterministic checks or authorized human review can support a pass when the evidence requirements are met. Model judgment alone cannot; it can lower a verdict or send it to a person.

The authored animation on our homepage illustrates this design with a hypothetical refund. Its amounts and outcomes are scripted. In the story, an agent is asked to refund the one damaged item on order 58213 and says the refund is ready: $96.00. The animation shows an amount check expecting $48.00 and returning the attempt. A second attempt shows $48.00, four passing checks and a verified result, with both attempts visible. These are illustrative states, not observations from a running refund integration or stored verification records.

The illustration gives both attempts the same confident tone. The intended check distinguishes them by the amount.

What's on npm today

The CLI on npm is @excellent-so/cli 0.1.0, published July 21, 2026. It holds:

• Two commands in one package: excellent, and excellent-mcp, a Model Context Protocol server that gives any MCP-capable agent the same tools.
• excellent init, which sets a repository up for your agent. It writes an AGENTS.md and a .excellent/ folder for project context and settings.
• A review gate. excellent-mcp review queue lists work waiting for verification that the current agent didn't ship. review approve refuses to sign off on work the same agent shipped.
• excellent-mcp agent converge, which alternates a verifier and a shipper until the queue is verifiably done, stalls, or reaches its cycle limit. Workers run through Claude Code or Codex, picked with --cli.
• excellent doctor checks the runtime, the local database, providers, installed agent CLIs and your PATH in one read.
• excellent update updates the CLI in place.

The installer checks the mirrored build against its published SHA-256 checksum before installing it. If they don't match, it stops.

So, plainly: 0.1.0 predates the v1 workflow above. It does not include the documented excellent run, excellent verify or excellent receipt verify commands. The changelog lists every published version and what each one holds.

Free to run

Excellent is free for individuals. No account, no credit card. It runs on macOS today. Windows and Linux are not supported yet. It needs Node.js 22.3 or newer.

curl -fsSL https://excellent.so/install.sh | sh
cd your-repo
excellent init

Teams can join early access, or work directly with Excellent engineers on a deployment.

What we publish

We publish what we learn about agents doing real work, under three questions. How do we know an agent actually accomplished an objective? What predicts failure in long-running agentic systems? What changes when agents encounter real businesses?

Our first research piece goes up on Research today: a close read of a benchmark number that's easy to mistake for a typical agent's failure rate. Why local verification matters for AI agents and Introducing Excellent cover the idea behind the product.