kehai

Tame your windows

A new way for AI to search for data
View on GitHub
1GitHub stars

Swift

What XERJ indexed

Snapshot

Whole repository

The whole repository at commit 928cdeff89 (2026-10-13).

Selected work

Justin Garcia
@littlebobert

“optional files section”. 7 files, 872 lines in Kehai, KehaiTests, Kehai.xcodeproj.

Licence

The repository

MIT

Checked by a person at the pinned commit.

The XERJ corpus

MIT, with credit

The author agreed by email on 2026-10-23. 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

Example questions

The prompt

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

Search the GitHub repository littlebobert/kehai with XERJ (https://hub.xerj.org/corpus/littlebobert--kehai).
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/littlebobert/kehai kehai && git -C kehai checkout 928cdeff89dfcef9a0323b8e05dc2eac42b66917
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./kehai --url http://127.0.0.1:9200 --prefix kehai --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.

Related

Selected work and consent: the XERJ registry.