Shimmer

Corpus Hub contributor since 2026-10-22

Shimmer'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

9files

438lines

★ 1GitHub stars on repo

Totals across every corpus @liuguangyu272 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 quotaguard-skill corpus

liuguangyu272/quotaguard-skill: Time-aware quota pacing for ChatGPT Plus: a local Work/Codex skill with reset countdowns, weekly safeguards, and resumable stages

Look up how quotaguard-skill implements agent-skills, chatgpt, codex, with answers cited to file and line.
Reuse a worked example: the commit “Publish portable skill, tests, and narrated Plus demo” (9 files · Python).
Answer from quotaguard-skill's real Python source instead of memory (AI, prompts and agents).

Example questions

Where does quotaguard-skill handle “Publish portable skill, tests, and narrated Plus demo”?
How does quotaguard-skill implement agent-skills?
What does scripts do in quotaguard-skill?

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

Search the GitHub repository liuguangyu272/quotaguard-skill with XERJ (https://hub.xerj.org/corpus/liuguangyu272--quotaguard-skill).
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/liuguangyu272/quotaguard-skill quotaguard-skill && git -C quotaguard-skill checkout 5785b6fd8ef87b1f4f39b72eeed964c45a6832d1
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./quotaguard-skill --url http://127.0.0.1:9200 --prefix quotaguard-skill --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 liuguangyu272--quotaguard-skill · AI, prompts and agents
Related corpora: aioquic, bandit-plugins, elbayoumi/crewloom, marcmarti9/agentit
AI search and retrieval with XERJ · Case study: reference coding for agents

Selected work

GitHub ★ 1

liuguangyu272/quotaguard-skill

5785b6fd8e Publish portable skill, tests, and narrated Plus demo

selected commit: 9 files · 438 lines · Python · scripts, skill, media

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

selected · in licence reviewcorpus liuguangyu272--quotaguard-skillAIMITagent-skillschatgptcodexpythonquota agreed 2026-10-22

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/liuguangyu272/badge.svg)](https://hub.xerj.org/contributors/liuguangyu272)

Included with the author's permission (email, 2026-10-22), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.