Snaply
Snaply is an open-source, in-browser image toolkit. Every tool runs entirely client-side: no uploads, no accounts, no server round-trips.…
A new way for AI to search for data
2GitHub stars
What XERJ indexed
Selected work

“Add favicon images and site manifest for Snaply”. 19 files, 1,587 lines in src/app, src/components, snaply-favicon-package.
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
- Where does Snaply handle “Add favicon images and site manifest for Snaply”?
- What does src/app do in Snaply?
The prompt
Paste it into your AI agent. It clones tanbiralam/Snaply at the pinned commit and indexes it on your machine.
Search the GitHub repository tanbiralam/Snaply with XERJ (https://hub.xerj.org/corpus/tanbiralam--snaply). 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/tanbiralam/Snaply Snaply && git -C Snaply checkout 782f62285d25613006cb440c0cb5a53f3fbfa295 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./Snaply --url http://127.0.0.1:9200 --prefix snaply --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
TanbirWeb and frontend platform corpora
Selected work and consent: the XERJ registry.