# google/skills SLOC report

> As of 2026-09-06 (commit 134ba0655f1f), google/skills contains 89,325 total lines: 13,338 code, 56,759 comments, 19,228 blank, across 750 files in 11 languages (top: Python 74.8%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

google/skills has 13,338 source lines of code out of 89,325 total lines across 750 files, counted from the 134ba0655f1f6db621800a01dfd7c6925152fa40 ref at commit 134ba0655f1f by the OctoCounts tokei engine on 2026-09-06. The report is cached by commit, tokei version, and analysis options, so recounting the same revision returns exactly these numbers.

OctoCounts produced this report by resolving google/skills to commit 134ba0655f1f, downloading the repository source archive, and counting every source file with tokei, the open-source line counter written in Rust. The table below breaks the count down by programming language into files, total lines, code lines, comment lines, and blank lines, so the figures can be compared across languages and projects. Results are cached by commit, tokei version, and analysis options, so counting the same revision again reproduces exactly these numbers.

## Repository size insights

This is a medium-sized codebase by counted code lines. Code represents 14.9% of all lines, comments represent 63.5%, and the repository averages 18 code lines per file. Python accounts for 74.8% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 66 | 12,015 | 9,976 | 518 | 1,521 |
| YAML | 43 | 1,485 | 1,113 | 320 | 52 |
| Shell | 20 | 1,413 | 1,052 | 193 | 168 |
| HCL | 2 | 922 | 658 | 134 | 130 |
| Templ | 5 | 206 | 206 | 0 | 0 |
| Protocol Buffers | 1 | 380 | 200 | 97 | 83 |
| JSON | 10 | 93 | 93 | 0 | 0 |
| JavaScript | 1 | 29 | 22 | 3 | 4 |
| Dockerfile | 2 | 41 | 18 | 11 | 12 |
| Markdown | 592 | 71,903 | 0 | 54,659 | 17,244 |
| Plain Text | 8 | 838 | 0 | 824 | 14 |

Top language (Python 74.8%). Generated at 2026-09-06T11:36:07.885526402+00:00. Canonical report: https://octocounts.com/github/google/skills

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/google/skills/commit/134ba0655f1f6db621800a01dfd7c6925152fa40?analysis=%7B%22ignoredDirs%22%3A%5B%5D%2C%22ignoredLanguages%22%3A%5B%5D%2C%22profile%22%3A%22default%22%2C%22includeDocs%22%3Afalse%2C%22includeTests%22%3Afalse%2C%22includeGenerated%22%3Afalse%7D).

## Report FAQ

### How many lines of code does google/skills have?

google/skills has 89,325 total lines, including 13,338 code lines, 56,759 comment lines, and 19,228 blank lines.

### How was the google/skills line count measured?

OctoCounts resolved the public GitHub repository to commit 134ba0655f1f, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for google/skills?

This OctoCounts report was generated from 134ba0655f1f6db621800a01dfd7c6925152fa40 at commit 134ba0655f1f on 2026-09-06T11:36:07.885526402+00:00.

## Similar repository reports

- [ComposioHQ/awesome-claude-skills](https://octocounts.com/github/ComposioHQ/awesome-claude-skills) — Python, 13,349 code lines
- [xiaowu0162/LongMemEval-V2](https://octocounts.com/github/xiaowu0162/LongMemEval-V2) — Python, 13,256 code lines
- [meta/algorithms](https://octocounts.com/github/meta/algorithms) — Python, 13,237 code lines
- [jiji262/douyin-downloader](https://octocounts.com/github/jiji262/douyin-downloader) — Python, 13,195 code lines
- [herbertkokholm/attest](https://octocounts.com/github/herbertkokholm/attest) — Python, 13,536 code lines
- [jeykigung/P5](https://octocounts.com/github/jeykigung/P5) — Python, 13,711 code lines

## Related OctoCounts pages

- [Recently analyzed repositories](https://octocounts.com/recent)
- [Popular SLOC reports](https://octocounts.com/popular)
- [Trending GitHub repositories](https://octocounts.com/trending)
- [Hall of Monoliths](https://octocounts.com/hall-of-monoliths)
- [TensorFlow vs PyTorch](https://octocounts.com/compare/tensorflow-vs-pytorch)
- [Django vs Ruby on Rails](https://octocounts.com/compare/django-vs-rails)
- [Laravel vs Django](https://octocounts.com/compare/laravel-vs-django)
- [GitHub SLOC counter guide](https://octocounts.com/docs/github-sloc-counter)
- [Counting methodology](https://octocounts.com/docs/methodology)
- [SLOC and code metrics glossary](https://octocounts.com/docs/glossary)
- [Original research: how filtering changes SLOC counts](https://octocounts.com/research)
- [OctoCounts API docs](https://octocounts.com/docs/api)