DeepCode

"DeepCode: Open Agentic Coding (Agent Harness & Loop Engineering & Multi-Agent Orchestration)"

Runssource: GitHubhomepagePythonMITcommit c0a6a3cb595f

Python, MIT licensed. The project labels itself: agentic coding, harness engineering and llm agent.

DeepCode runs. An Argusic agent installed it in 2 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.

The Python package is installed and builds, the CLI reports version 2.1.0, the app-server runtime probe passes, and the full test suite (1586 tests) passes.

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 90.7 of 100 (the mean of this project's run scores).

At a glance

verdict
Runs
Argusic Score
90.7 / 100
cost of the verifying run
$0.02 (measured)
recorded runs
3
last tested
stars
16,622
forks
2,163
open issues
17
watchers
129
size
85 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
2 minutes
Cold machine to finish
3 minutes
Errors hit and fixed
0 hit, 0 fixed with no human help
How the result was proved
deepcode --version returned 'DeepCode 2.1.0'; deepcode-app-server --verify-runtime returned '{"ok":true}'; pytest ran 1586 passed, 19 skipped, 0 failed.
Model tokens used
45,705
Exact commit tested
c0a6a3cb595f
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

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 3, 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.

tests/test_workflow_interactions.py::test_interaction_registry_lifecycle_has_no_plugin_semantics PA…
tests/test_zhipu_thinking_wire.py::test_glm_requests_carry_a_thinking_body[high-enabled] PASSED [ 9…
tests/test_zhipu_thinking_wire.py::test_glm_requests_carry_a_thinking_body[low-enabled] PASSED [ 99…
tests/test_zhipu_thinking_wire.py::test_glm_requests_carry_a_thinking_body[none-disabled] PASSED [ …
tests/test_zhipu_thinking_wire.py::test_auto_leaves_the_choice_to_the_model[None] PASSED [ 99%]
tests/test_zhipu_thinking_wire.py::test_auto_leaves_the_choice_to_the_model[auto] PASSED [ 99%]
tests/test_zhipu_thinking_wire.py::test_zhipu_matches_the_deepseek_wire_shape PASSED [100%]
================= 1586 passed, 19 skipped in 76.50s (0:01:16) ==================
All checks succeeded cleanly. No errors were encountered at any stage.
tokens used
45,705
All checks succeeded cleanly. No errors were encountered at any stage.

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 2 minutes.
  • 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.
  • Measured 3 times, so the result is not a one-off.

Of the 9 agentic-coding projects Argusic has installed and timed, DeepCode was the 4th fastest to reach a running state, and 8 of 9 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.
  • A quick evaluation: it was running 2 minutes after the clone.
  • Following its own README: the documented path worked with nothing to fix.

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 Runner3/3Runs with mocks72.000.05
Argusic Runner2/3Runs100.000.02
Argusic Runner1/3Runs100.000.04

Topics (from GitHub)

agentic-codingharness-engineeringllm-agent

Embed the badge

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

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

Questions

Does DeepCode run?
Yes. DeepCode runs. Argusic installed and launched it on a clean machine in 2 minutes, hitting 0 errors on the way, and recorded the session.
How did Argusic test DeepCode?
On a fresh, disposable machine, with every command recorded and the repository pinned at commit c0a6a3cb595f. 3 attempts are recorded, and the full method is on the methodology page.
What did it cost to test DeepCode?
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 DeepCode take to install?
2 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 DeepCode need a GPU?
Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing DeepCode?
Nothing did, in the recorded run: zero errors between clone and running.
How does DeepCode compare with the alternatives?
Of the 9 agentic-coding projects Argusic has installed and timed, DeepCode was the 4th fastest to reach a running state, and 8 of 9 reached one at all.
Where is the evidence for DeepCode?
All 3 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