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Git history can show where code changes pile up, which files move together, and how widely project knowledge is shared. In a September 23, 2026 article, Kenji Rasmussen—the builder and maintainer of the gitfault CLI—used those signals to assess six familiar open-source repositories. His results are useful as prompts for investigation, not as definitive grades of software quality: the score has not been independently validated as a predictor of defects.
What git history can—and cannot—tell you
A repository’s commit log is more than a record of activity. Looking at the size of files alongside how often they change can surface hotspots: areas where maintenance work, bug risk, or merge friction may be concentrated. Repeated changes to the same files can also reveal coupling, even when those files are not obviously connected in the code. Finally, examining contributor activity across areas can suggest whether knowledge is broadly shared or concentrated among a small group.
These are signals for a maintainer to investigate, not proof that a project has defects or poor design. A busy file may be central and well-tested; a low-activity file may be stable or simply neglected. Rasmussen’s article does not establish that gitfault’s health score predicts defects, and the six-project comparison is not an independently validated ranking.
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The figures below are snapshots reported in Rasmussen’s 2026 article, not measurements independently reproduced here. The article’s health grades, scores, bus factors, commit totals, and hottest-file labels should be read as the author’s gitfault analysis—not as grades issued by the projects themselves.
#1 Best Overall
| Repository | Language | Commits reported | Health score reported | Bus factor reported | Hottest file reported |
|---|---|---|---|---|---|
| sharkdp/bat | Rust | 3,307 | B · 73 | 8 | tests/integration_tests.rs |
| pallets/click | Python | 2,158 | B · 71 | 2 | src/click/core.py |
| psf/requests | Python | 4,839 | C · 68 | 2 | tests/test_requests.py |
| pallets/flask | Python | 3,815 | C · 62 | 1 | CHANGES.rst |
| expressjs/express | JavaScript | 5,676 | C · 61 | 1 | lib/response.js |
| junegunn/fzf | Go | 3,627 | C · 55 | 1 | src/terminal.go |
Bat has the highest reported score in this set, B · 73; fzf has the lowest, C · 55. Those labels are meaningful only within the author’s analysis and its chosen method. The article excerpt does not establish the score formula, thresholds, observation window, or how repository size, renames, and merge commits were handled, so the numbers should not be treated as directly comparable quality measurements beyond the reported snapshot.
Why bat’s busy test file looks different
Rasmussen reports tests/integration_tests.rs in bat as its hottest file, with 216 revisions and 72 authors, and reports a bus factor of 8 for the repository. The interpretation is more encouraging than a simple “hot file equals risk” rule: a frequently changed integration test suite touched by many contributors may indicate that testing work is shared across the project.
Rank #2
- Used Book in Good Condition
As Rasmussen puts it, “When the busiest file in a project is the thing that proves the project works, that’s usually a good smell.” That is an interpretation of this particular signal, not a general guarantee that a heavily revised test file means a project is healthy.
What fzf’s hotspot says—and does not say
The article reports src/terminal.go in fzf at 758 revisions and approximately 22,000 lines of churn, alongside a bus factor of 1. Rasmussen suggests this combination could make the file worth reviewing for additional tests or planned refactoring. It does not, by itself, show that fzf is badly built: a central, complex component can attract sustained work in a well-maintained project.
Rank #3
Why raw change counts can mislead
Flask illustrates why frequency alone is not enough. Rasmussen says src/flask/app.py remains hot, with 136 revisions and about 5,400 lines of churn, and describes its author pool as relatively small. The article’s reported hottest file for Flask is CHANGES.rst, a reminder that a changelog or manifest can rank highly by raw activity without being a large code hotspot. The useful question is not merely “Which file changed most?” but whether substantial, repeated changes overlap with concentrated knowledge.
How to reproduce the author’s gitfault workflow
Rasmussen describes gitfault as a zero-configuration CLI that can be installed through pipx, uvx, or Homebrew. The author says it reads Git history rather than source code, works offline, supports any language, and requires neither language-specific plugins nor machine learning. Those are product claims from the tool’s builder, not independently tested findings.
Rank #4
The article demonstrates commands for these tasks:
- Inspect a repository overview and health score.
- Find files that repeatedly change together.
- Review contributor ownership and bus factor.
- Target a repository for analysis.
- Export an interactive HTML report.
The captured article details do not specify the exact command syntax, score formula, or defaults for those analyses. Anyone using the results to guide maintenance decisions should consult gitfault’s own documentation for the current commands and methodology, then inspect the underlying files and contributor history directly.
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For maintainers, a hotspot or low bus-factor result is best treated as a review queue. Check whether the activity represents feature development, bug fixes, generated changes, or routine release bookkeeping. Look at whether tests cover the relevant behavior, whether multiple people can explain and change the area, and whether the apparent concentration persists over a meaningful time window.
Best Value
Rasmussen’s comparison is a compact demonstration of what repository history can prompt you to ask. It does not establish a timeless ranking of six projects, nor does a single score replace reading code, tests, release practices, and project context.
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