# akitaonrails/ai-memory SLOC report

> As of 2026-09-20 (commit 353841d91618), akitaonrails/ai-memory contains 218,024 total lines: 184,689 code, 19,179 comments, 14,156 blank, across 504 files in 15 languages (top: Rust 95.6%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

akitaonrails/ai-memory has 184,689 source lines of code out of 218,024 total lines across 504 files, counted from the 353841d91618d20b110b208de284a74d0b960379 ref at commit 353841d91618 by the OctoCounts tokei engine on 2026-09-20. 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 akitaonrails/ai-memory to commit 353841d91618, 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 84.7% of all lines, comments represent 8.8%, and the repository averages 366 code lines per file. Rust accounts for 95.6% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Rust | 207 | 197,359 | 176,489 | 8,629 | 12,241 |
| Shell | 89 | 4,934 | 3,677 | 868 | 389 |
| SQL | 64 | 2,739 | 1,589 | 851 | 299 |
| BASH | 3 | 1,238 | 811 | 308 | 119 |
| PowerShell | 82 | 883 | 775 | 77 | 31 |
| TOML | 19 | 1,130 | 661 | 370 | 99 |
| HTML | 7 | 412 | 380 | 4 | 28 |
| YAML | 4 | 324 | 125 | 182 | 17 |
| Nix | 1 | 146 | 73 | 56 | 17 |
| Pacman's makepkg | 1 | 80 | 55 | 17 | 8 |
| Dockerfile | 1 | 79 | 40 | 34 | 5 |
| JavaScript | 1 | 6 | 6 | 0 | 0 |

Top language (Rust 95.6%). Generated at 2026-09-20T16:47:41.585171508+00:00. Canonical report: https://octocounts.com/github/akitaonrails/ai-memory

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/akitaonrails/ai-memory/commit/353841d91618d20b110b208de284a74d0b960379?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 akitaonrails/ai-memory have?

akitaonrails/ai-memory has 218,024 total lines, including 184,689 code lines, 19,179 comment lines, and 14,156 blank lines.

### How was the akitaonrails/ai-memory line count measured?

OctoCounts resolved the public GitHub repository to commit 353841d91618, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for akitaonrails/ai-memory?

This OctoCounts report was generated from 353841d91618d20b110b208de284a74d0b960379 at commit 353841d91618 on 2026-09-20T16:47:41.585171508+00:00.

## Similar repository reports

- [pacifio/atlas](https://octocounts.com/github/pacifio/atlas) — Rust, 186,787 code lines
- [Labpics-Team/lab-colors](https://octocounts.com/github/Labpics-Team/lab-colors) — Rust, 189,130 code lines
- [boa-dev/boa](https://octocounts.com/github/boa-dev/boa) — Rust, 171,331 code lines
- [Ammar-Alnagar/Helios-Engine](https://octocounts.com/github/Ammar-Alnagar/Helios-Engine) — Rust, 206,091 code lines
- [vercel-labs/agent-browser](https://octocounts.com/github/vercel-labs/agent-browser) — Rust, 161,459 code lines
- [microsoft/oxidizer](https://octocounts.com/github/microsoft/oxidizer) — Rust, 210,538 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)
- [Rust vs Go](https://octocounts.com/compare/rust-vs-go)
- [Electron vs Tauri](https://octocounts.com/compare/electron-vs-tauri)
- [Deno vs Node.js](https://octocounts.com/compare/deno-vs-node)
- [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)