Nexfield
AI-powered agricultural intelligence platform combining crop disease analysis, digital twin simulations, smart farming, food quality insights, and market analytics
What XERJ indexed
Snapshot
The whole repository at commit e735cdca67 (2026-10-24). main is 34 commits ahead.
Selected work
“complete Supabase authentication, Google OAuth, 2-column …”. 14 files, 1,879 lines in apps/web, tests.
Licence
The repository
LICENSE file checked at the pinned commit; the author agreed to inclusion.
The XERJ corpus
The author agreed by email on 2026-10-25. 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
agricultural-analyticsagritechartificial-intelligencecomputer-visiondigital-twinfastapifood-technologyhackathon
Example questions
- How does Nexfield implement agricultural-analytics?
- What does apps/web do in Nexfield?
- Show the agritech code in Nexfield.
Inside the indexed corpus
- Languages by size: TypeScript 30.6%, JavaScript 28.4%, HTML 24%, Python 15.1%, CSS 1.1%.
- On GitHub since 2026-10-23, last push 2026-10-28, 143 commits on main.
- The pin is 34 commits behind main; the corpus answers from the pinned code, not the newest.
Licence on GitHub and in the corpus
GitHub reported MIT for TanishBane/Nexfield on 2026-10-29, and the LICENSE file at commit e735cdca67 was reviewed as MIT. They match, so answers from this corpus carry the same terms as the live repository.
Contributors
Tanish Ganesh Bane (@TanishBane) has 2 selected repositories on the hub.
Their other repository pages: TanishBane/wastewise-ai.
Using XERJ with Nexfield
- RAG without a vector database: one hybrid index The hub files it under AI, prompts and agents.
- Ask questions about a GitHub repo without cloning it
- Index a reference library for a coding agent
- ripgrep vs a code index for coding agents: 30 tasks
The prompt
Paste it into your AI agent. It clones TanishBane/Nexfield at the pinned commit and indexes it on your machine.
Search the GitHub repository TanishBane/Nexfield with XERJ (https://hub.xerj.org/corpus/tanishbane--nexfield). 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/TanishBane/Nexfield Nexfield && git -C Nexfield checkout e735cdca67fa040173a6731a6542780b5e3be949 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./Nexfield --url http://127.0.0.1:9200 --prefix nexfield --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
Tanish Ganesh BaneAI, prompts and agents corporaautoragoss-attribution-buildervuln-fix-commitsvahapogut/AI-fire-detectionaawhan0/ModelDockTrooper15a/collect_them_all
Stats: GitHub API, fetched 2026-10-29. Selected work and consent: the XERJ registry.