RuoYi AI is a full-stack enterprise platform for building AI assistants and agents that combine language models, knowledge bases, visual workflows, and multiple cooperating agents. Developers and organizations use it to manage model providers, retrieve information from documents, connect tools through MCP, and orchestrate agent workflows. The catalogue includes skills for working with RuoYi AI.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ageerle/ruoyi-ai --skill story-causalitygit clone --depth 1 https://github.com/ageerle/ruoyi-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ageerle/ruoyi-ai/story-causality)<a href="https://agentmods.dev/skills/ageerle/ruoyi-ai/story-causality"><img src="https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/story-causality/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ageerle/ruoyi-ai/story-causality"><img src="https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/story-causality.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00011 | $0.00951 |
| Opus 5.5 | $0.00004 | $0.00380 |
| Sonnet 5.5 | $0.00002 | $0.00190 |
| Haiku 4.5 | $0.00001 | $0.00095 |
Grade A, and why
story-causality scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
剧情因果与节奏
用于剧本和大纲。先落实用户确认的故事年份、生活背景、人物目标与信息边界。年份与装修年代分开，旧物不代表故事发生在旧年代。 大纲只写每场的目标、触发、行动、结果和下一场原因及预算；正文只保留必要行动和对白，不混入镜头、机位、逐秒或软件操作参数。 每场新增信息或改变人物选择；合并重复反应，不用空镜、无目的独处或重复告别凑时长。把“清理→触物→回忆的行为→主动听语音”作为因果链，不拆成互不相干的摆拍。 局部修订时不新增已确认故事之外的秘密或反转；用户明确要求重构时可设计新冲突，但仍服从主线和世界观。推测需经人物求证，创作资料里的信息不能自动成为人物已知事实。 按对白、不可重叠动作与自然停顿估时，不能靠字数推出片长；用户时长优先。保留当前接口要求的输出结构。
故事可看性先于分镜扩写
先按用户指定类型和节奏判断开场。商业爽剧、悬疑、冒险的前段须出现可感知的异常、威胁、欲望或未解问题，使人物必须行动；不要求所有题材都用暴力、喊叫或固定秒数的钩子。人物身份、时代背景可在应对中分次交代，不先做完整问答说明会。
整集写清：主角眼前必须做到什么；什么人或条件阻止他；失败失去什么；他做了什么有代价的选择；局面因此怎样改变。因果通顺只是底线，不等于故事有张力。工艺、调查、治理的步骤只保留改变风险、关系或结果的部分，不把一个小工序拉成一集。
技术优势应在人物选择和可见结果中体现，既不能万能答案直接成功，也不能让主角全程问问题、由配角完成所有判断。工匠和普通人有经验、利益与行动能力。反转回答已建立的问题并改变力量关系，不能靠突然冒出的无关坏人、灾难或信息强行刺激。
输出前做一次删场判断：删掉这场，观众失去哪项必要理解、人物选择或情绪变化？若只少一道工序、一段重复说明或一遍确认，合并或删除。不机械固定每几十秒反转。当用户不满意故事时，先重构故事与逐句打磨对白，再投入媒体生成。
修订同时记录保留项与改动项。用户已经认可的画风、演员、服装、字幕、地点时间提示和电影光色继续沿用，不因剧情重写全部抹掉。
人物驱动的场景与修订
人物的身份标签不能代替性格。先看他在眼前压力下守住什么、放弃什么，以及这个选择怎样影响别人；配角也有自己的诉求和可采取的行动。冲突可来自资源、关系、职责或认知差异，不强加坏人、吵架或暴力。
每场先确认人物带着什么目标进入、遇到什么阻力、如何改变做法、离场时局面怎样变化，再写正文。变化可以是信任、风险、信息或行动机会，不要求每场反转。修订先比较场内的选择与后果，反复使用同一策略却没有新回应时合并重复节拍。进入点靠近必要事件，结束点落在改变及其反应上，保留理解所需铺垫，不延长无变化的过程。
沿项目已有状态推进前提、大纲、人物关系、场景、正文和修订；阶段结论进入现有剧本与版本记录，不额外要求用户填写知识库或改接口。返修只回到有问题的阶段，不无故推翻已定故事。具体题材、美术、时长和对白由当前项目决定。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago Changed · +20 lines 20c6ebe29004
- 15d ago First seen · 13 lines · 11 tokens per session scan A 409751ae316b
story-causality is a skill published in the GitHub repository ageerle/ruoyi-ai (5,756 stars, last pushed 3d ago), licensed MIT. It adds 11 tokens to every session and 951 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-01.
Other skills, from other repositories
wegent-knowledge
Knowledge base management and search tools for Wegent. Provides capabilities to list, create, update, and search knowledge bases and documents using RAG retrieval. Use this skill when the user wants to manage knowledge bases, documents, or search for information programmatically.
knowledge-org
A guide to organising large bodies of knowledge so an AI system can navigate relationships, summaries, and layers instead of searching only flat text chunks. It covers tree indexes, knowledge graphs, file-like structures, incremental updates, and long-term memory layouts.
rag-pipeline
A guide to RAG, a method where a system retrieves relevant passages from an external knowledge base before an AI model writes an answer. It covers splitting documents, searching by meaning or exact words, combining results, and measuring retrieval quality.
memory-rag-poisoning-detection
Detect persistent-memory poisoning and RAG/knowledge-base contamination via dialogue testing. Use when the agent has long-term memory, a user/preference store, or writes to a retrievable knowledge base.
beautiful-article
A tool for turning source material—such as a web page, PDF, DOCX, Markdown file, text, screenshot, or pasted content—into a single offline HTML article.
web-design-engineer
Build or redesign polished browser-rendered visual artifacts with HTML/CSS/JavaScript/React: pages, dashboards, prototypes, slide decks, animations, UI mockups, and data visualizations. Use for visual front-end creation, design-system exploration, design critique, or explicit browser acceptance / QA of a web artifact.…