loop-engineering
Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems that prompt and orchestrate agents (inspired by Addy Osmani and Boris Cherny). Includes loop-audit, loop-init, loop-cost.
Runssource: GitHubhomepageTypeScriptMITcommit 7422449e2297
TypeScript, MIT licensed. The project labels itself: agentic ai, ai agents, ai coding, anthropic, automation, claude, claude code and codex.
loop-engineering runs. An Argusic agent installed it in 8 minutes and hit 2 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Both documented CLIs build and run from a clean copy, 252 validation-gate tests pass with 0 failures, and the repository audits at 100/100 L2.
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.
- loop-audit clean install contained readiness-core without dist/index.js, so TypeScript could not resolve @cobusgreyling/readiness-core and the build failed.3 minutes
- npm ci in tools/mcp-server failed with ENOENT because npm 9 tried to materialize readiness-core inside the linked loop-audit dependency, but the lockfile had no entry for it.2 minutes
- Install time
- 8 minutes
- Cold machine to finish
- 10 minutes
- Errors hit and fixed
- 2 hit, 2 fixed with no human help
- How the result was proved
- Pristine git-archive copy: npm ci plus npm test passed readiness-core 6/6, loop-audit 30/30, mcp-server 28/28, and loop 11/11; scripts/ci-validate-gates.sh passed 252/252 with 'validate gates passed'; scripts/ci-audit-gates.sh passed with reference score 100. Live `node tools/loop/dist/cli.js --version` printed 0.2.0 and `node tools/loop-audit/dist/cli.js /work/repo --json` returned score 100, level L2, exit 0.
- Model tokens used
- 217,352
- Exact commit tested
- 7422449e2297
- 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.
- Official gates: `ci-validate-gates.sh` passed 252/252 tests; `ci-audit-gates.sh` passed with refe… - Live CLI: `loop --version` printed `0.2.0`; `loop-audit /work/repo --json` returned score 100/L2 … tokens used 217,352 The final smoke check is consistent: umbrella version `0.2.0`, auditor/doctor score 100 at L2, and … **Result** The repository now installs and runs from a clean copy. The defects were missing build artifacts in… - Fixed `tools/readiness-core/.gitignore` so its compiled `dist/` ships as the zero-install depende… - Added `@cobusgreyling/readiness-core` to `tools/mcp-server/package.json` and refreshed its lockfi… - Clean-copy tests: `readiness-core` 6/6, `loop-audit` 30/30, `mcp-server` 28/28, `loop` 11/11. - Official gates: `ci-validate-gates.sh` passed 252/252 tests; `ci-audit-gates.sh` passed with refe… - Live CLI: `loop --version` printed `0.2.0`; `loop-audit /work/repo --json` returned score 100/L2 …
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.
- 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.
- Measured 2 times, so the result is not a one-off.
What did not, or is not known
- Took 8 minutes to install, slower than the median of the 37 comparable projects Argusic has measured.
Of the 38 agentic-ai projects Argusic has installed and timed, loop-engineering was the 22nd fastest to reach a running state, and 28 of 38 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 8 minutes after the clone.
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)
agentic-aiai-agentsai-codinganthropicautomationclaudeclaude-codecodexcoding-agentsdevops-automationdevtoolsgithub-actionsgrokllmloop-engineeringmcpprompt-engineering
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/loop-engineering)Questions
- Does loop-engineering run?
- Yes. loop-engineering runs. Argusic installed and launched it on a clean machine in 8 minutes, hitting 2 errors on the way, and recorded the session.
- How did Argusic test loop-engineering?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 7422449e2297. 2 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test loop-engineering?
- The run that produced this verdict cost $0.14: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does loop-engineering take to install?
- 8 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 loop-engineering need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing loop-engineering?
- 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 loop-engineering compare with the alternatives?
- Of the 38 agentic-ai projects Argusic has installed and timed, loop-engineering was the 22nd fastest to reach a running state, and 28 of 38 reached one at all.
- Where is the evidence for loop-engineering?
- 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.