hl
A fast and powerful log viewer and processor that converts JSON logs or logfmt logs into a clear human-readable format.
Runssource: GitHubRustMITcommit 81a8d0deb496
Rust, MIT licensed. The project labels itself: cli, command line tool, hl, human, json, json log, json logging and json logs.
hl runs. An Argusic agent installed it in 5 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.
The hl binary v0.36.3 builds from source, all 1796 unit tests pass, and the tool correctly parses and renders JSON log files into human-readable output with working field filtering and level filtering.
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
- 5 minutes
- Cold machine to finish
- 6 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- How the result was proved
- cargo test --workspace exited 0, 1796 tests passed across all workspace crates; ./target/debug/hl --version returned 'hl 0.36.3'; hl parsed sample/cafe.log producing 22 output lines with correct logfmt rendering; level filtering (-l err) returned 1 matching line
- Model tokens used
- 39,334
- Exact commit tested
- 81a8d0deb496
- 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.
=== Run on real data ===
22
=== Level filter ===
1
=== Build time ===
Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.25s
=== Test summary ===
Total tests passed: 1796
**ARGUSIC_RESULT:** {"install_succeeded": true, "launch_succeeded": true, "install_minutes": 5, "er…
tokens used
39,334
**ARGUSIC_RESULT:** {"install_succeeded": true, "launch_succeeded": true, "install_minutes": 5, "er…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.
- 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.
What did not, or is not known
- Took 5 minutes to install, slower than the median of the 28 comparable projects Argusic has measured.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 29 cli projects Argusic has installed and timed, hl was the 20th fastest to reach a running state, and 26 of 29 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 5 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
Topics (from GitHub)
clicommand-line-toolhlhumanjsonjson-logjson-loggingjson-logsloglog-viewerlogfmtlogginglogsruststructured-loggingtranslates-json-logsviewer
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/hl)Questions
- Does hl run?
- Yes. hl runs. Argusic installed and launched it on a clean machine in 5 minutes, hitting 0 errors on the way, and recorded the session.
- How did Argusic test hl?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 81a8d0deb496. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test hl?
- 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 hl take to install?
- 5 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 hl need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing hl?
- Nothing did, in the recorded run: zero errors between clone and running.
- How does hl compare with the alternatives?
- Of the 29 cli projects Argusic has installed and timed, hl was the 20th fastest to reach a running state, and 26 of 29 reached one at all.
- Where is the evidence for hl?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.