As of 2026-08-28 (commit ae9c1ae5298e), akitaonrails/ai-memory contains 169,834 total lines: 144,733 code, 13,925 comments, 11,176 blank, across 446 files in 15 languages (top: Rust 95.1%). Counted with tokei via OctoCounts.
OctoCounts produced this report by resolving akitaonrails/ai-memory to commit ae9c1ae5298e, 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.
This is a large codebase by counted code lines. Code represents 85.2% of all lines, comments represent 8.2%, and the repository averages 325 code lines per file. Rust accounts for 95.1% of counted code.
| Language | Files | Lines | Code | Comments | Blanks |
|---|---|---|---|---|---|
| Rust | 170 | 152937 | 137612 | 5798 | 9527 |
| Shell | 87 | 4238 | 3193 | 698 | 347 |
| SQL | 50 | 2200 | 1307 | 635 | 258 |
| PowerShell | 82 | 861 | 756 | 74 | 31 |
| BASH | 3 | 1129 | 729 | 293 | 107 |
| TOML | 17 | 890 | 564 | 236 | 90 |
| HTML | 6 | 292 | 266 | 4 | 22 |
| YAML | 4 | 319 | 125 | 177 | 17 |
| Nix | 1 | 146 | 73 | 56 | 17 |
| Pacman's makepkg | 1 | 76 | 54 | 14 | 8 |
| Dockerfile | 1 | 79 | 40 | 34 | 5 |
| JavaScript | 1 | 6 | 6 | 0 | 0 |
Top language (Rust 95.1%). Generated at 2026-08-28T09:23:58.162293142+00:00.
akitaonrails/ai-memory has 169,834 total lines, including 144,733 code lines, 13,925 comment lines, and 11,176 blank lines.
OctoCounts resolved the public GitHub repository to commit ae9c1ae5298e, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.
This OctoCounts report was generated from main at commit ae9c1ae5298e on 2026-08-28T09:23:58.162293142+00:00.
Other public repositories with an OctoCounts report, ranked by top language and code size similarity: