Yuyyxz

Corpus Hub contributor since 2026-10-30

Yuyyxz'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

13files

2,080lines

★ 5GitHub stars on repo

Totals across every corpus @Yuyyxz 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 kling-prompt-engineering corpus

Yuyyxz/kling-prompt-engineering: 🎬 Director-grade prompt engineering guide for Kling AI video generation. 可灵AI提示词工程--导演式视频生成指南。

Look up how kling-prompt-engineering implements ai-video, camera-language, chinese, with answers cited to file and line.
Reuse a worked example: the commit “两批本地迁移推送：技能渐进加载 + 模型事实单一数据源 + 分镜结构化层” (13 files · Python, shell).
Answer from kling-prompt-engineering's real Python source instead of memory (AI, prompts and agents).

Example questions

Where does kling-prompt-engineering handle “两批本地迁移推送：技能渐进加载 + 模型事实单一数据源 + 分镜结构化层”?
How does kling-prompt-engineering implement ai-video?
What does skills do in kling-prompt-engineering?

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

Search the GitHub repository Yuyyxz/kling-prompt-engineering with XERJ (https://hub.xerj.org/corpus/yuyyxz--kling-prompt-engineering).
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/Yuyyxz/kling-prompt-engineering kling-prompt-engineering && git -C kling-prompt-engineering checkout 66c68309a2acbabe3dd74d031198add37fb94c17
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./kling-prompt-engineering --url http://127.0.0.1:9200 --prefix kling-prompt-engineering --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 yuyyxz--kling-prompt-engineering · AI, prompts and agents
Related corpora: promptify, wysking--postgrad-study-engine, hydope/shortsmash, raojiacui/prompt-lens
AI search and retrieval with XERJ · Case study: reference coding for agents

Selected work

GitHub ★ 5

Yuyyxz/kling-prompt-engineering

Director-grade prompt engineering guide for Kling AI video generation. 可灵AI提示词工程:: 导演式视频生成指南。

On GitHub: 42 commits · created 2026-07 · last push 2026-10-30

Languages: Python 93%, Shell 7%

66c68309a2 两批本地迁移推送：技能渐进加载 + 模型事实单一数据源 + 分镜结构化层

selected commit: 13 files · 2,080 lines · Python, shell · skills, scripts, the project root

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

live on the hub · licence clearedcorpus yuyyxz--kling-prompt-engineeringAIMITai-videocamera-languagechinesedirectorfilmmakingimage-to-video agreed 2026-10-30

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

Included with the author's permission (email, 2026-10-30), under each repository's own licence, with attribution. Own more repositories? Sign in with GitHub and add them. Want something removed? Reply to the email, withdraw it on /add, or open an issue on xerj-org/xerj.