MetCode

A command line AI tool

A new way for AI to search for data
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What XERJ indexed

Snapshot

Whole repository

The whole repository at commit 659fa9f063 (2026-10-23).

Selected work

Edwin-Metcalf
@Edwin-metcalf

“refactred /agent into agent.go compact.go and normalize.go”. 3 files, 380 lines in internal/agent.

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

The prompt

Paste it into your AI agent. It clones Edwin-metcalf/MetCode at the pinned commit and indexes it on your machine.

Search the GitHub repository Edwin-metcalf/MetCode with XERJ (https://hub.xerj.org/corpus/edwin-metcalf--metcode).
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/Edwin-metcalf/MetCode MetCode && git -C MetCode checkout 659fa9f06353d9497fcce86a97d03631aae384ac
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./MetCode --url http://127.0.0.1:9200 --prefix metcode --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

Selected work and consent: the XERJ registry.