# K-Dense-AI/scientific-agent-skills SLOC report

> As of 2026-09-01 (commit 1dd0fccf46fc), K-Dense-AI/scientific-agent-skills contains 499,155 total lines: 233,599 code, 176,605 comments, 88,951 blank, across 1,902 files in 10 languages (top: Python 62.9%). Counted with tokei via OctoCounts.

OctoCounts produced this report by resolving K-Dense-AI/scientific-agent-skills to commit 1dd0fccf46fc, 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 large codebase by counted code lines. Code represents 46.8% of all lines, comments represent 35.4%, and the repository averages 123 code lines per file. Python accounts for 62.9% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 542 | 169,349 | 146,896 | 3,257 | 19,196 |
| JSON | 79 | 81,897 | 81,897 | 0 | 0 |
| TeX | 17 | 6,030 | 3,675 | 1,106 | 1,249 |
| YAML | 6 | 925 | 751 | 126 | 48 |
| Shell | 3 | 359 | 262 | 50 | 47 |
| HTML | 1 | 91 | 84 | 0 | 7 |
| TOML | 1 | 26 | 19 | 5 | 2 |
| XML | 5 | 15 | 15 | 0 | 0 |
| Markdown | 1,242 | 240,341 | 0 | 171,959 | 68,382 |
| Plain Text | 6 | 122 | 0 | 102 | 20 |

Top language (Python 62.9%). Generated at 2026-09-01T07:47:16.257957876+00:00. Canonical report: https://octocounts.com/github/K-Dense-AI/scientific-agent-skills

## Report FAQ

### How many lines of code does K-Dense-AI/scientific-agent-skills have?

K-Dense-AI/scientific-agent-skills has 499,155 total lines, including 233,599 code lines, 176,605 comment lines, and 88,951 blank lines.

### How was the K-Dense-AI/scientific-agent-skills line count measured?

OctoCounts resolved the public GitHub repository to commit 1dd0fccf46fc, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for K-Dense-AI/scientific-agent-skills?

This OctoCounts report was generated from main at commit 1dd0fccf46fc on 2026-09-01T07:47:16.257957876+00:00.

## Similar repository reports

- [bytedance/deer-flow](https://octocounts.com/github/bytedance/deer-flow) — Python, 227,906 code lines
- [alexgreensh/token-optimizer](https://octocounts.com/github/alexgreensh/token-optimizer) — Python, 239,419 code lines
- [HKUDS/DeepTutor](https://octocounts.com/github/HKUDS/DeepTutor) — Python, 240,939 code lines
- [alirezarezvani/claude-skills](https://octocounts.com/github/alirezarezvani/claude-skills) — Python, 225,662 code lines
- [python/mypy](https://octocounts.com/github/python/mypy) — Python, 242,271 code lines
- [openai/openai-python](https://octocounts.com/github/openai/openai-python) — Python, 224,862 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)
- [OctoCounts API docs](https://octocounts.com/docs/api)
