Yash Jangid

What an agent can do with the kensaku corpus

yjid/kensaku: Search inside documents, code, and even screenshots - instantly and locally. A free, open-source file launcher with OCR, semantic search…

• Look up how kensaku implements desktop, file-search, full-text-search, with answers cited to file and line.
• Reuse a worked example: the commit “harden agent scopes, OCR fallback, and connect writes” (11 files · Rust).
• Answer from kensaku's real Rust source instead of memory (AI, prompts and agents).

• Where does kensaku handle “harden agent scopes, OCR fallback, and connect writes”?
• How does kensaku implement desktop?
• What does src-tauri do in kensaku?

Search the GitHub repository yjid/kensaku with XERJ (https://hub.xerj.org/corpus/yjid--kensaku).
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/yjid/kensaku kensaku && git -C kensaku checkout 2a81686143071934205ad49e63dd053ea565757b
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./kensaku --url http://127.0.0.1:9200 --prefix kensaku --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.

corpus yjid--kensaku · AI, prompts and agents
Related corpora: lightningcss, jsonwebtoken-rust, xcrft/mastermind, vvooki-sys/loomem
AI search and retrieval with XERJ · Case study: reference coding for agents