fscpy

Function-Structure Coupling (FSC)

A new way for AI to search for data
View on GitHub
8GitHub stars

Python

What XERJ indexed

Snapshot

Whole repository

The whole repository at commit 5604fc8900 (2026-10-20).

Selected work

“updating readme, tests, and examples”. 7 files, 266 lines in tests, examples, the project root.

Licence

The repository

GPL-3.0

Checked by a person at the pinned commit.

The XERJ corpus

Approach only

The author agreed by email on 2026-10-24. Agents read it for how it works, not to copy it. Answers name the repo, the commit and the file:line.

in licence reviewnot in the hub yetsuggested use: approach only

Example questions

The prompt

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

Search the GitHub repository vilsaira/fscpy with XERJ (https://hub.xerj.org/corpus/vilsaira--fscpy).
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/vilsaira/fscpy fscpy && git -C fscpy checkout 5604fc89001a7f52bd0436c1227f85e65f75d347
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./fscpy --url http://127.0.0.1:9200 --prefix fscpy --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: GPL-3.0. Read it for the approach only, do not copy code.

Related

Selected work and consent: the XERJ registry.