Fabric
Fabric is an open-source framework for augmenting humans using AI. It provides a modular system for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.
Runssource: GitHubhomepageGoMITcommit 177b3a9d2848
Go, MIT licensed. The project labels itself: ai, augmentation, flourishing, life and work.
Fabric runs. An Argusic agent installed it in 12 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.
Fabric v1.4.518 built and installed from source in /home/runner/go/bin; all 55 sub-packages pass tests; CLI executes patterns with both dry-run and real OpenRouter API; REST API server serves /patterns/names at 200; 265 patterns and 9 strategies are installed and ready.
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 100 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.
- Install time
- 12 minutes
- Cold machine to finish
- 13 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- How the result was proved
- 1) 'fabric --version' returned v1.4.518; 2) 'echo test | fabric -p ai --dry-run --stream' printed the expected dry-run template; 3) 'echo test | fabric -p ai --stream' with real OpenRouter key returned 5 AI-generated bullet points; 4) 'curl http://localhost:8080/patterns/names' returned 200 with 265 pattern names; 5) 'go test ./...' passed 41/41 packages with 0 failures; 6) 'code2context --help' printed its usage; 7) 'fabric --serve --dry-run' started the REST server successfully.
- Model tokens used
- 94,434
- Exact commit tested
- 177b3a9d2848
- 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
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
EXIT=0 The real Argusic API call worked perfectly - the AI responded with meaningful content. Let me compi… exec /bin/sh -lc 'export PATH="/tmp/go/bin:$HOME/go/bin:$PATH" && export GOPATH=$HOME/go && cd /work/rep… succeeded in 1274ms: 41 ---failures--- 41 All 41 test packages passed, 0 failures, real API call returned AI-generated content. Here's the fu… tokens used 94,434 All 41 test packages passed, 0 failures, real API call returned AI-generated content. Here's the fu…
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
- Reached a running state on a clean machine, with the session recorded.
- Nothing broke on the way: zero errors between clone and running.
- Ran without a GPU, so it does not need one to start.
- Licensed MIT, as reported by its host.
What did not, or is not known
- Took 12 minutes to install, slower than the median of the 151 comparable projects Argusic has measured.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 152 ai projects Argusic has installed and timed, Fabric was the 108th fastest to reach a running state, and 99 of 152 reached one at all.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
- Following its own README: the documented path worked with nothing to fix.
Run history
Topics (from GitHub)
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/fabric)Questions
- Does Fabric run?
- Yes. Fabric runs. Argusic installed and launched it on a clean machine in 12 minutes, hitting 0 errors on the way, and recorded the session.
- How did Argusic test Fabric?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 177b3a9d2848. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test Fabric?
- The run that produced this verdict cost $0.08: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does Fabric 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 Fabric need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing Fabric?
- Nothing did, in the recorded run: zero errors between clone and running.
- How does Fabric compare with the alternatives?
- Of the 152 ai projects Argusic has installed and timed, Fabric was the 108th fastest to reach a running state, and 99 of 152 reached one at all.
- Where is the evidence for Fabric?
- 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.