sponge
A powerful and easy-to-use Go development framework that enables you to effortlessly build stable, reliable, and high-performance backend services with a "low-code" approach.
Runssource: GitHubhomepageGoMITcommit beef9eecdc5e
Go, MIT licensed. The project labels itself: ai assistant, ai generated code, cloud native, code generation, custom templates, developer tools, development framework and gin.
sponge runs. An Argusic agent installed it in 23 minutes and hit 2 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Sponge v1.16.1 is installed with all 12 plugins, the code-generation engine runs on port 24631 serving the UI, and all 29 test suites pass.
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.
What went wrong, in the agent's own words
The agent's own words, worst first, never rewritten into advice.
- Go (golang) not installed in container2 minutes
- protoc binary not installed by sponge init2 minutes
- Install time
- 23 minutes
- Cold machine to finish
- 24 minutes
- Errors hit and fixed
- 2 hit, 2 fixed with no human help
- How the result was proved
- curl -H 'Accept: text/html' http://localhost:24631/ returned HTTP 200 with Sponge UI HTML; sponge -v returned v1.16.1; go test on internal/... and pkg/... returned all ok
- Model tokens used
- 100,347
- Exact commit tested
- beef9eecdc5e
- 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.
- Go 1.23.0 was not available in the container (`go: not found`); downloaded `go1.23.0.linux-amd64.… - Set `GOROOT`, `GOPATH`, `GOBIN` and `PATH` accordingly. - `go install github.com/go-dev-frame/sponge/cmd/sponge` built the sponge binary at `$GOBIN/sponge`. - `sponge init` downloaded all dependency plugins (protoc-gen-go, protoc-gen-go-grpc, protoc-gen-va… - `protoc` was missing after init; downloaded `protoc-31.1-linux-x86_64.zip`, extracted with Python… **Launch verification:** - `sponge run` started the code generation engine on port 24631. `curl -H "Accept: text/html" http:… - Command output: `Code generation engine service running v1.16.1. Access http://localhost:24631 in… **Test verification:** - `go test -count=1 -short github.com/go-dev-frame/sponge/internal/...` — 9 passed, 3 packages had … - `go test -count=1 -short github.com/go-dev-frame/sponge/pkg/...` — 20 passed, all packages passed. - No test failures encountered.
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.
- Installed in 23 minutes.
- Recovered from all 2 errors without a human stepping in, which says the failures are documented well enough to solve.
- 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
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
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
Topics (from GitHub)
ai-assistantai-generated-codecloud-nativecode-generationcustom-templatesdeveloper-toolsdevelopment-frameworkgingo-spongegrpcgrpc-gatewaylow-codemicroserviceprotobufrestful-apispongeweb
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/sponge)Questions
- Does sponge run?
- Yes. sponge runs. Argusic installed and launched it on a clean machine in 23 minutes, hitting 2 errors on the way, and recorded the session.
- How did Argusic test sponge?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit beef9eecdc5e. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test sponge?
- The run that produced this verdict cost $0.11: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does sponge take to install?
- 23 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 sponge need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing sponge?
- 2 things broke in the recorded run, and 2 were fixed without human help. Each one, and the time it cost, is listed on this page.
- Where is the evidence for sponge?
- 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.