Jordi

Corpus Hub contributor since 2026-10-21

Jordi's work was selected for the XERJ Corpus Hub, the open reference memory AI coding agents search before they write code. When an agent meets the same problem, it gets this implementation back as a worked example, with the author and the repository attached.

1corpus

1selected commit

3files

350lines

★ 2GitHub stars on repo

Totals across every corpus @jbt95 appears in; a commit selected for two corpora counts once. Files and lines count the selected commits; each corpus indexes the whole repository at its pinned commit.

What an agent can do with the leadline corpus

jbt95/leadline: Deterministic function-level complexity analysis for Java, JavaScript, TypeScript, and TSX: built as a feedback loop for humans, CI, and…

Look up how leadline implements agentic-ai, ai, cli, with answers cited to file and line.
Reuse a worked example: the commit “carry test ids and symbol keys in the test map” (3 files · Rust).
Answer from leadline's real Rust source instead of memory (AI, prompts and agents).

Example questions

Where does leadline handle “carry test ids and symbol keys in the test map”?
How does leadline implement agentic-ai?
What does crates/analysis do in leadline?

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

Search the GitHub repository jbt95/leadline with XERJ (https://hub.xerj.org/corpus/jbt95--leadline).
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/jbt95/leadline leadline && git -C leadline checkout df7b69a8ef9d37537f938a40cf424959c303dbf9
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./leadline --url http://127.0.0.1:9200 --prefix leadline --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 jbt95--leadline · AI, prompts and agents
Related corpora: chroma, fabric, devcell-sh/devcell, codecoradev/uteke
AI search and retrieval with XERJ · Case study: reference coding for agents

Selected work

GitHub ★ 2

jbt95/leadline

df7b69a8ef feat(analysis): carry test ids and symbol keys in the test map

selected commit: 3 files · 350 lines · Rust · crates/analysis, crates/report

The corpus is the whole repository at the pinned commit, not only the files of the selected commit.

selected · in licence reviewcorpus jbt95--leadlineAIMITagentic-aiaiclicomplexitymcprust agreed 2026-10-21

Not installable yet: this corpus is not in the hub registry until its licence review passes, so xerj corpus add and xerj ask cannot fetch it. It becomes installable when this card says live in the hub.

[![XERJ Corpus Hub contributor](https://hub.xerj.org/contributors/jbt95/badge.svg)](https://hub.xerj.org/contributors/jbt95)

Included with the author's permission (email, 2026-10-21), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.