openclaw-nerve
Real-time web cockpit for OpenClaw: voice conversations, agent automated kanban board, workspace/file control, sub-agent sessions, inline charts, and usage visibility.
Runs with mockssource: GitHubhomepageTypeScriptMITcommit 312e27333e14
TypeScript, MIT licensed. The project labels itself: ai agent, claude, clawbot, dashboard, mission control, open source, openai and openclaw.
openclaw-nerve runs, with stand-ins for the services it depends on. An Argusic agent installed it in 12 minutes and hit 1 error and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
npm install, npm run build, and npm run setup succeed; all 1870 tests pass; the Nerve server starts on port 3080 and serves HTTP API endpoints (health, connect-defaults, version, server-info) with gateway reachable via a mock.
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
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.
What went wrong, in the agent's own words
The agent's own words, worst first, never rewritten into advice.
- System Node.js v18.19.1 is below required Node 22+2 minutes
- Install time
- 12 minutes
- Cold machine to finish
- 13 minutes
- Errors hit and fixed
- 1 hit, 1 fixed with no human help
- How the result was proved
- npm test: 142 test files, 1870 passed, 0 failed. curl -s http://127.0.0.1:3080/health returned {"status":"ok","gateway":"ok"}. curl -s http://127.0.0.1:3080/api/version returned {"version":"1.5.3"}.
- Model tokens used
- 374,655
- Exact commit tested
- 312e27333e14
- 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
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
**Install**: `npm install` succeeded (913 packages). `npm run build` succeeded. `npm run setup -- -… **Error**: The only issue was the system Node.js version (v18.19.1) being below the required Node 2… **Test suite**: All 1870 tests pass across 142 test files. **Server launch**: The server starts cleanly on port 3080. With a mock gateway on port 18789, the `… tokens used 374,655 All clean. Let me now compile the final report. Here's the complete summary of my work: **Install**: `npm install` succeeded (913 packages). `npm run build` succeeded. `npm run setup -- -… **Error**: The only issue was the system Node.js version (v18.19.1) being below the required Node 2… **Test suite**: All 1870 tests pass across 142 test files. **Server launch**: The server starts cleanly on port 3080. With a mock gateway on port 18789, the `…
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
- Recovered from all 1 error without a human stepping in, which says the failures are documented well enough to solve.
- Licensed MIT, as reported by its host.
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.
- Took 12 minutes to install, slower than the median of the 11 comparable projects Argusic has measured.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 12 ai-agent projects Argusic has installed and timed, openclaw-nerve was the 8th fastest to reach a running state, and 9 of 12 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 by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 1/3 | Runs with mocks | 92.00 | 0.09 |
Topics (from GitHub)
ai-agentclaudeclawbotdashboardmission-controlopen-sourceopenaiopenclawopenclaw-dashboardopenclaw-uiself-hostedvoiceweb-ui
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/openclaw-nerve)Questions
- Does openclaw-nerve run?
- openclaw-nerve runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 12 minutes, hitting 1 error on the way, and recorded the session.
- How did Argusic test openclaw-nerve?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 312e27333e14. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test openclaw-nerve?
- The run that produced this verdict cost $0.09: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does openclaw-nerve take to install?
- 12 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does openclaw-nerve need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing openclaw-nerve?
- 1 thing broke in the recorded run, and 1 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does openclaw-nerve compare with the alternatives?
- Of the 12 ai-agent projects Argusic has installed and timed, openclaw-nerve was the 8th fastest to reach a running state, and 9 of 12 reached one at all.
- Where is the evidence for openclaw-nerve?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.