sparklines

Text-based sparklines for the command line mimicking those of Edward Tufte

A new way for AI to search for data

View on GitHub

129GitHub stars

What XERJ indexed

Snapshot

Whole repository

The whole repository at commit 6987064c7b.

Selected work

Dinu Gherman
@deeplook

Licence

The repository

MIT

LICENSE file checked at the pinned commit; the author agreed to inclusion.

The XERJ corpus

MIT, with credit

The owner added it on hub.xerj.org after signing in with GitHub, on 2026-11-11. Same terms as the repository. Answers name the repo, the commit and the file:line.

selected for the XERJ Corpus Hublicence clearedsuggested use: adapt with attribution

pythoncommand-line-toolgraphsasciisparklinessparkline-graphs

Example questions

How does sparklines implement python?
Show the command-line-tool code in sparklines.

The prompt

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

Search the GitHub repository deeplook/sparklines with XERJ (https://hub.xerj.org/corpus/deeplook--sparklines).
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/deeplook/sparklines sparklines && git -C sparklines checkout 6987064c7b2b460bf04849b26e9ccfa28c5418fe
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./sparklines --url http://127.0.0.1:9200 --prefix sparklines --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.

Dinu Gherman API design and specification corpora Romelium/mpatch voidcosmos/npkill shellroute/shellroute-cli

Selected work and consent: the XERJ registry.