Kyungwon Kang
Kyungwon Kang'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.
Totals across every corpus @Gudegi 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 KangEngine corpus
Gudegi/KangEngine: C++/Python engine for character motion, robotics simulation, and visualization
- Look up how KangEngine implements computer-graphics, physics-simulation, robotics, with answers cited to file and line.
- Reuse a worked example: the commit “REFACTOR(render) : separate app updates from frame rendering (replace…” (25 files · Python, C++).
- Answer from KangEngine's real Python source instead of memory (API design and specification).
- How does KangEngine implement computer-graphics?
- What does python do in KangEngine?
Search the GitHub repository Gudegi/KangEngine with XERJ (https://hub.xerj.org/corpus/gudegi--kangengine). 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/Gudegi/KangEngine KangEngine && git -C KangEngine checkout 140889c1eb4989d2ad6884287fac922d1704a49c 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./KangEngine --url http://127.0.0.1:9200 --prefix kangengine --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 gudegi--kangengine · API design and specification
Related corpora: plan-and-act, DexForce/EmbodiChain, Hebbian-Robotics/hflow
Search an OpenAPI spec from an agent · Case study: reference coding for agents
Selected work
Gudegi/KangEngine
The corpus is the whole repository at the pinned commit, not only the files of the selected commit.
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.
Sign in with GitHub or Hugging Face to see more: every selected commit in full (commit date, every folder, licence review state, pin) and the pack builds of each corpus.
[](https://hub.xerj.org/contributors/Gudegi)
Included with the author's permission (email, 2026-10-23), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.