open-multi-agent

Self-hosted TypeScript agent runtime with durable approvals and verifiable run records. Own it, approve it, audit it.

Runs with mockssource: GitHubhomepageTypeScriptMITcommit dcffce18c8ad

TypeScript, MIT licensed. The project labels itself: agent framework, agent orchestration, agentic ai, ai agents, ai governance, anthropic, claude and claude code.

open-multi-agent runs, with stand-ins for the services it depends on. An Argusic agent installed it in 1 minute and hit no errors on a clean machine with no GPU, and the whole session was recorded.

The open-multi-agent monorepo installs, builds, type-checks, and passes all unit tests (2314 total) without network access or API keys, using mocked provider SDKs. The CLI help command works.

What the agent ended up with on a clean machine, in its own words. How this is measured

Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 92 of 100 (the mean of this project's run scores).

At a glance

verdict
Runs with mocks
Argusic Score
92 / 100
cost of the verifying run
$0.02 (measured)
recorded runs
2
last tested
stars
6,952
forks
2,434
open issues
4
watchers
58
size
15 MB
created
last push

Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.

What was measured

From the run that decided this verdict. Every line is a recorded value, not an estimate.

Install time
1 minutes
Cold machine to finish
5 minutes
Errors hit and fixed
0 hit, 0 fixed with no human help
How the result was proved
npm test exited 0: 143 core test files (2207 passed, 3 skipped), 5 create-oma-app test files (31 passed), 3 otel test files (17 passed), 11 release-bot test files (59 passed), 4 bench test files (36 passed); lint passed on all workspaces; CLI help exited 0
Model tokens used
50,912
Exact commit tested
dcffce18c8ad
Container image
sha256:cdd920bce783

What was not measured

The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.

Peak GPU memory
this ran on a CPU machine, so there was no GPU to sample
Behaviour over a long run
each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
Behaviour against real services
this run was verified against stand-in services only

Watch the session

The whole run, from a clean machine, at the speed it actually happened. Nothing is cut and nothing is sped up.

A recording of attempt 1, run . The verdict above comes from a different attempt, so read this as one session and not as the current result. The terminal recording it was made from is the evidence, stored with a sha256 fingerprint; the video is a rendering of it. Nothing loads from the video host until you press play.

The end of the recording

The last lines of the terminal session that decided this verdict, exactly as they were recorded.

tokens used
50,912
Everything works end-to-end. Let me compile the final report.
Here is the complete verification:
**Environment** — Node.js 18 was the system version; I downloaded and used Node.js 20.19.1 to meet …
| Step | Outcome |
|---|---|
| `npm install` | 304 packages added, no errors |
| `npm run build` | All 4 workspaces compiled (`core`, `create-oma-app`, `otel`, `release-bot`) |
| `npm test` | 143 test files, 2207 passed, 3 skipped (core); 5 test files, 31 passed (create-oma-a…
| `npm run lint` | All 4 workspaces type-checked clean, bench type-checked clean |
| CLI help | `node packages/core/dist/cli/oma.js help` exited 0, printed all subcommands |

Replay the whole session, every command from a clean machine to this point.

How it was tested

One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.

Strengths and limits

Measured facts, not opinions. How this is written.

What went well

  • Installed in 1 minute, faster than the median of the 3 comparable projects Argusic has measured.
  • Nothing broke on the way: zero errors between clone and running.
  • Licensed MIT, as reported by its host.
  • Measured 2 times, so the result is not a one-off.

What did not, or is not known

  • Only reached a running state against stand-in services, so nothing here proves it works against the real ones.

Of the 4 agent-framework projects Argusic has installed and timed, open-multi-agent was the 2nd fastest to reach a running state, and 2 of 4 reached one at all.

Also tested, in the same area

Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.

Run history

tested byattemptoutcomescorecost USDwhen
Argusic Runner2/3Runs with mocks92.000.02
Argusic Runner1/3Runs with mocks92.000.03

Topics (from GitHub)

agent-frameworkagent-orchestrationagentic-aiai-agentsai-governanceanthropicclaudeclaude-codedeepseekgeminillmlocal-llmmcpmulti-agentobservabilityollamaopenaiself-hostedtypescript

Embed the badge

Markdown for the project README. It links back here; terms on the terms page.

[![Tested by Argusic](https://argusic.com/badge/open-multi-agent.svg)](https://argusic.com/subject/open-multi-agent)

Questions

Does open-multi-agent run?
open-multi-agent runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 1 minutes, hitting 0 errors on the way, and recorded the session.
How did Argusic test open-multi-agent?
On a fresh, disposable machine, with every command recorded and the repository pinned at commit dcffce18c8ad. 2 attempts are recorded, and the full method is on the methodology page.
What did it cost to test open-multi-agent?
The run that produced this verdict cost $0.02: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
How long does open-multi-agent take to install?
1 minute in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
Does open-multi-agent need a GPU?
Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing open-multi-agent?
Nothing did, in the recorded run: zero errors between clone and running.
How does open-multi-agent compare with the alternatives?
Of the 4 agent-framework projects Argusic has installed and timed, open-multi-agent was the 2nd fastest to reach a running state, and 2 of 4 reached one at all.
Where is the evidence for open-multi-agent?
All 2 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.

Discussion