leanrea
One 8 KB skill that replaces REA (Reverse Engineer Anything): plain CLI tools, no MCP. Benchmarked: 38% faster, 35% cheaper.
Could not verifysource: GitHubPythonMITcommit 09ba4aa0217f
Python, MIT licensed.
Argusic could not get leanrea running. An Argusic agent installed it in 2 minutes and hit 1 error and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
The leanrea SKILL.md can be installed via 'npx skills add aicodeking/leanrea' and is copied into ./.agents/skills/leanrea/; the skill file is present and structurally valid
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
Subject data from GitHub, linked at the top of this page. 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.
- skills CLI (npx skills add) requires Node >= 22.20.0, but system Node is v18.19.1; downloaded Node v22.14.0 as a workaround and the install worked2 minutes
- Install time
- 2 minutes
- Cold machine to finish
- 2 minutes
- Errors hit and fixed
- 1 hit, 1 fixed with no human help
- How the result was proved
- npx [email protected] add aicodeking/leanrea (remote) and add /work/repo (local) both completed successfully, copying 8374 bytes of SKILL.md to ./.agents/skills/leanrea/, confirmed via file listing. npx skills list showed the installed skill. skills-lock.json was created with hash a502dd...
- Model tokens used
- 65,692
- Exact commit tested
- 09ba4aa0217f
- 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
- Behaviour against real services
- this run was verified against stand-in services only
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
{
"version": 1,
"skills": {
"leanrea": {
"source": ".",
"sourceType": "local",
"computedHash": "a502dd556ca6e5cf812baa616a89915e9dd07f569d9419c2824376598739e475"
}
}
}
tokens used
65,692Replay 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 2 minutes, faster than the median of the 46 comparable projects Argusic has measured.
- Recovered from all 1 error without a human stepping in, which says the failures are documented well enough to solve.
- Licensed MIT, 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 47 Python projects Argusic has installed and timed, leanrea was the 16th fastest to reach a running state, and 27 of 47 reached one at all.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 2/3 | Did not run | 50.00 | 0.02 | |
| Argusic Runner | 1/3 | Did not run | 50.00 | 0.06 |
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/leanrea)Questions
- Does leanrea run?
- Argusic could not verify that leanrea runs. Argusic installed and launched it on a clean machine in 2 minutes, hitting 1 error on the way, and recorded the session.
- How did Argusic test leanrea?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 09ba4aa0217f. 2 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test leanrea?
- 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 leanrea 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 leanrea need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing leanrea?
- 1 thing broke in the recorded run, and 1 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does leanrea compare with the alternatives?
- Of the 47 Python projects Argusic has installed and timed, leanrea was the 16th fastest to reach a running state, and 27 of 47 reached one at all.
- Where is the evidence for leanrea?
- 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.