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 video-continuitygit 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/video-continuity)<a href="https://agentmods.dev/skills/ageerle/ruoyi-ai/video-continuity"><img src="https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/video-continuity/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/video-continuity"><img src="https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/video-continuity.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 | $0.00020 | $0.00564 |
| Opus 5.5 | $0.00008 | $0.00226 |
| Sonnet 5.5 | $0.00004 | $0.00113 |
| Haiku 4.5 | $0.00002 | $0.00056 |
Grade A, and why
video-continuity 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
视频连续性
同一连续场景须维护道具外观与摆放清单：眼镜框形与材质、垫布颜色、纸箱数量和开合、手机壳不能逐镜重新设计。 已装箱的工具、箱子与桌上遗物，未被人物搬走就必须继续存在；画外道具仍保留相对位置，不把工作台恢复成空净场景母图。新来的饭盒只能占用空位，不能替换原有道具。 首帧是可选参考。选择使用时，已审阅关键帧优先于旧版视觉草稿，动作从实际画面状态展开；没有首帧或明确关闭参考时，从已批准资产与起始构图规划展开，不要求先补图。场景母图仅约束建筑与光线，未设计的道具移动、换手、消失均禁止。 手机语音只从手机传出，收听者闭口倾听，不对口型；声音原文与发言人不得改写。无对白镜头只保留自然环境与动作声，不添加旁白解释感情。
屏幕与实物操作
手机型号、镜头数量、刘海形状、保护壳及持物手均由固定资产决定。微信旧语音通过点击聊天中的语音条播放；不是来电，不长按录音，不凭空出现独立重播键。播放前、播放中、结束状态必须写清，屏幕文字优先使用原始UI素材。 放手机须依次经过降低、背壳接触台面、松指、收手。写清屏幕朝向；不得一边握着一边已经躺在桌面，禁止翻面或穿桌。 食物、容器和筷子跨镜分别锁定数量、材质、开盖状态与所在桌面。跨桌必须有取走和放下的可见动作，或明确时间省略；不能通过切镜让物件瞬移。 电脑软件植入必须满足输入文件确实存在、上传后提交、等待后出结果、结果引发人物行动的顺序。不得以结果页冒充上传页；清晰文字和点击使用真实素材或确定性合成。 背景音乐由合成阶段统一混入，人物对白与手机语音镜头不额外生成音乐，避免两套配乐叠加。
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 33598ab2195e
- 15d ago First seen · 19 lines · 20 tokens per session scan A bec7421fe318
video-continuity is a skill published in the GitHub repository ageerle/ruoyi-ai (5,756 stars, last pushed 3d ago), licensed MIT. It adds 20 tokens to every session and 564 once invoked, about $0.0001 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.…