bpr /

mojito

An implementation of a Mojo-like language in Rust

A new way for AI to search for data

View on GitHub

5GitHub stars

Python

What XERJ indexed

Snapshot

Whole repository

The whole repository at commit b7c9e6bd28 (2026-10-17).

Selected work

Brian Rogoff
@bpr

“Add scripts/smoke, a minute-long VM-and-native run of a corpus cross-…”. 53 files, 902 lines in tests, scripts.

Licence

The repository

MIT

Checked by a person at the pinned commit.

The XERJ corpus

MIT, with credit

The author agreed by email on 2026-10-20. Same terms as the repository. Answers name the repo, the commit and the file:line.

in licence reviewnot in the hub yetsuggested use: adapt with attribution

The prompt

Paste it into your AI agent. It clones bpr/mojito at the pinned commit and indexes it on your machine.

Search the GitHub repository bpr/mojito with XERJ (https://hub.xerj.org/corpus/bpr--mojito).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/bpr/mojito mojito && git -C mojito checkout b7c9e6bd28eb3cd563b06024a2e1ad4428d90b16
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./mojito --url http://127.0.0.1:9200 --prefix mojito --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: MIT. Keep the copyright notice and credit the authors.

Brian Rogoff API design and specification corpora

Selected work and consent: the XERJ registry.