code2prompt
A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting.
Runssource: GitHubhomepageRustMITcommit ab4fa06f6fdb
Rust, MIT licensed. The project labels itself: ai, chatgpt, claude, cli, command line, command line tool, gpt and llm.
code2prompt runs. An Argusic agent installed it in 3 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.
code2prompt v4.3.0 builds, passes all 113 tests, and the CLI runs correctly, generating formatted prompts from any codebase path.
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
- 3 minutes
- Cold machine to finish
- 10 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- Model tokens used
- 46,673
- Exact commit tested
- ab4fa06f6fdb
- 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.
- How the result was proved
- runs before 2026-09-07 did not record the command used to check the result
- 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.
Compiling arboard v3.6.1
Compiling ratatui-textarea v0.9.2
Compiling tui-tree-widget v0.24.0
Compiling terminal_size v0.4.4
Compiling git2 v0.21.0
Compiling code2prompt_core v4.3.0 (/work/repo/crates/code2prompt-core)
Compiling code2prompt v4.3.0 (/work/repo/crates/code2prompt)
Finished `release` profile [optimized] target(s) in 2m 56s
Everything works perfectly — no errors encountered. Let me compile the final report.
tokens used
46,673
Everything works perfectly — no errors encountered. Let me compile the final 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
- Reached a running state on a clean machine, with the session recorded.
- Installed in 3 minutes, faster than the median of the 36 comparable projects Argusic has measured.
- 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 37 ai projects Argusic has installed and timed, code2prompt was the 11th fastest to reach a running state, and 30 of 37 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 3 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 by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 1/3 | Runs | 100.00 | 0.03 | |
| Argusic Runner | 2/3 | Ran out of time | 0.00 | 0.12 | |
| Argusic Runner | 1/3 | Ran out of time | 0.00 | 0.25 |
Topics (from GitHub)
aichatgptclaudeclicommand-linecommand-line-toolgptllmpromptprompt-engineeringprompt-generatorprompt-toolkitrust
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/code2prompt)Questions
- Does code2prompt run?
- Yes. code2prompt runs. Argusic installed and launched it on a clean machine in 3 minutes, hitting 0 errors on the way, and recorded the session.
- How did Argusic test code2prompt?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit ab4fa06f6fdb. 3 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test code2prompt?
- The run that produced this verdict cost $0.03: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does code2prompt 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 code2prompt need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing code2prompt?
- Nothing did, in the recorded run: zero errors between clone and running.
- How does code2prompt compare with the alternatives?
- Of the 37 ai projects Argusic has installed and timed, code2prompt was the 11th fastest to reach a running state, and 30 of 37 reached one at all.
- Where is the evidence for code2prompt?
- 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.