Dluck

Corpus Hub contributor since 2026-10-21

Dluck'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

50files

4,538lines

★ 10GitHub stars on repo

Totals across every corpus @Dluckxx 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 wrenyard corpus

wrenyard/wrenyard: Local-first agent orchestration with a unified CLI, runtime, Pet, and Desktop app

Look up how wrenyard implements agent-orchestration, ai-agents, electron, with answers cited to file and line.
Reuse a worked example: the commit “restructure the ledger into turns, steps, actions …” (50 files · TypeScript).
Answer from wrenyard's real TypeScript source instead of memory (AI, prompts and agents).

Example questions

How does wrenyard implement agent-orchestration?
What does packages/features do in wrenyard?

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

Search the GitHub repository wrenyard/wrenyard with XERJ (https://hub.xerj.org/corpus/wrenyard--wrenyard).
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/wrenyard/wrenyard wrenyard && git -C wrenyard checkout f27bbab0eeb800ec5463735fcc13f5ce50200121
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./wrenyard --url http://127.0.0.1:9200 --prefix wrenyard --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 wrenyard--wrenyard · AI, prompts and agents
Related corpora: atoma-run--atoma, protovalidate, markus-global/markus, milind-soni/OpenMausBot
AI search and retrieval with XERJ · Case study: reference coding for agents

Selected work

GitHub ★ 10

wrenyard/wrenyard

f27bbab0ee refactor(session): restructure the ledger into turns, steps, actions …

selected commit: 50 files · 4,538 lines · TypeScript · packages/features, apps/desktop, apps/daemon

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

selected · in licence reviewcorpus wrenyard--wrenyardAIMITagent-orchestrationai-agentselectrongolangtask-graphtypescript 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/Dluckxx/badge.svg)](https://hub.xerj.org/contributors/Dluckxx)

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.