Argusic could not verify that dagger runs. Argusic installed and launched it on a clean machine in 3 minutes, hitting 2 errors on the way, and recorded the session.

How did Argusic test dagger?

On a fresh, disposable machine, with every command recorded and the repository pinned at commit e8f071cc2ab0. 2 attempts are recorded, and the full method is on the methodology page.

What did it cost to test dagger?

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 dagger take to install?

3 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 dagger need a GPU?

Not to start. Argusic reached a running state on a machine with no GPU.

What goes wrong when installing dagger?

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 dagger?

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.

dagger

Automation engine to build, test and ship any codebase. Runs locally, in CI, or directly in the cloud

Could not verifysource: GitHub homepageGoApache-2.0commit e8f071cc2ab0

Go, Apache-2.0 licensed. The project labels itself: agents, caching, ci cd, containers, continuous deployment, continuous integration, devops and docker.

Argusic could not get dagger running. An Argusic agent installed it in 3 minutes and hit 2 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.

Dagger CLI v0.21.9 is installed and responds to help/version commands; 15 Go unit test packages and 13 Python SDK tests pass; the Dagger engine cannot start because no container runtime is available in this environment and user namespaces are blocked.
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 50 of 100 (the mean of this project's run scores).

At a glance

verdict: Could not verify
Argusic Score: 50 / 100
cost of the verifying run: $0.11 (measured)
recorded runs: 2
last tested: 2026-09-26
stars: 16,299
forks: 928
open issues: 190
watchers: 232
size: 253 MB
created: 2019-11-20
last push: 2026-09-26

Subject data from GitHub, linked at the top of this page, refreshed 2026-09-26. 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.

Time lost to each failure while testing dagger, drawn from the recorded run — Every bar is a failure the agent recorded, with the time it cost. Drawn from this run, not from anywhere else.

What went wrong, in the agent's own words

The agent's own words, worst first, never rewritten into advice.

No container runtime (Docker, Podman, containerd) available. The Dagger engine requires a container runtime to start the local engine.15 minutes
Engine binary built from source panics during shutdown: 'cannot create context from nil parent' in dagger/otel-go Close()3 minutes

Install time: 3 minutes
Cold machine to finish: 22 minutes
Errors hit and fixed: 2 hit, 2 fixed with no human help
How the result was proved: dagger version returned 'dagger v0.21.9 (image://registry.dagger.io/engine:v0.21.9) linux/amd64' and 'dagger --help' listed all subcommands. dagger call failed with 'driver for scheme image was not available'. 15 Go packages passed tests. 13 Python tests passed. Engine binary from go build prints version 'v1.0.0-beta.15 linux/amd64' but panics on startup.
Model tokens used: 370,686
Exact commit tested: e8f071cc2ab0
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
Whether it works at all: this run verified nothing, so this page makes no claim either way

The end of the recording

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

ok    github.com/dagger/dagger/core/dotenv  0.004s
ok    github.com/dagger/dagger/core/modelcatalog  0.016s
ok    github.com/dagger/dagger/engine/telemetry/cgroupmetrics  0.016s
ok    github.com/dagger/dagger/engine/session/h2c  0.006s
ok    github.com/dagger/dagger/engine/session/prompt  0.009s
ok    github.com/dagger/dagger/core/workspace  0.043s
=== Go unit test total ===
15
Now I have a complete picture. Here's the report.
tokens used
370,686
Now I have a complete picture. Here's the report.

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 3 minutes, faster than the median of the 11 comparable projects Argusic has measured.
Recovered from all 2 errors without a human stepping in, which says the failures are documented well enough to solve.
Licensed Apache-2.0, as reported by its host.
Measured 2 times, so the result is not a one-off.

What did not, or is not known

An agent with no time limit did not get it running.

Of the 12 agents projects Argusic has installed and timed, dagger was the 4th fastest to reach a running state, and 6 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	2/3	Did not run	50.00	0.11	2026-09-26 05:37 UTC
Argusic Runner	1/3	Did not run	50.00	0.10	2026-09-26 05:15 UTC

Topics (from GitHub)

agents caching ci-cd containers continuous-deployment continuous-integration devops docker graphql workflows

Embed the badge

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

[![Tested by Argusic](https://argusic.com/badge/dagger.svg)](https://argusic.com/subject/dagger)

Questions

Does dagger run?: Argusic could not verify that dagger runs. Argusic installed and launched it on a clean machine in 3 minutes, hitting 2 errors on the way, and recorded the session.
How did Argusic test dagger?: On a fresh, disposable machine, with every command recorded and the repository pinned at commit e8f071cc2ab0. 2 attempts are recorded, and the full method is on the methodology page.
What did it cost to test dagger?: 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 dagger take to install?: 3 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 dagger need a GPU?: Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing dagger?: 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.
How does dagger compare with the alternatives?: Of the 12 agents projects Argusic has installed and timed, dagger was the 4th fastest to reach a running state, and 6 of 12 reached one at all.
Where is the evidence for dagger?: 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.