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。
What XERJ indexed
Snapshot
The whole repository at commit 66c68309a2 (2026-10-30). master is 3 commits ahead.
Selected work
“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, 2,080 lines in skills, scripts, the project root.
Licence
The repository
LICENSE file checked at the pinned commit; the author agreed to inclusion.
The XERJ corpus
The author agreed by email on 2026-10-30. Same terms as the repository. Answers name the repo, the commit and the file:line.
selected for the XERJ Corpus Hublicence clearedsuggested use: adapt with attribution
ai-videocamera-languagechinesedirectorfilmmakingimage-to-videokling-aiprompt-engineering
Example questions
- How does kling-prompt-engineering implement ai-video?
- 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”?
- What does skills do in kling-prompt-engineering?
Inside the indexed corpus
- Languages by size: Python 93.2%, Shell 6.8%.
- On GitHub since 2026-07-14, last push 2026-10-30, 42 commits on master.
- The pin is 3 commits behind master; the corpus answers from the pinned code, not the newest.
Licence on GitHub and in the corpus
GitHub reported MIT for Yuyyxz/kling-prompt-engineering on 2026-10-31, and the LICENSE file at commit 66c68309a2 was reviewed as MIT. They match, so answers from this corpus carry the same terms as the live repository.
Contributors
Yuyyxz (@Yuyyxz) has 1 selected repository on the hub.
Using XERJ with kling-prompt-engineering
- RAG without a vector database: one hybrid index The hub files it under AI, prompts and agents.
- ripgrep vs a code index for coding agents: 30 tasks
- Best MCP servers for local code search in 2026, compared
- Best grep alternative for AI coding agents (2026)
The prompt
Paste it into your AI agent. It clones Yuyyxz/kling-prompt-engineering 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.
Related
YuyyxzAI, prompts and agents corporawysking--postgrad-study-engineellpromptifyhydope/shortsmashraojiacui/prompt-lenssyxscott/academic-paper-polish
Stats: GitHub API, fetched 2026-10-31. Selected work and consent: the XERJ registry.