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 github-novel-adaptationgit 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/github-novel-adaptation)<a href="https://agentmods.dev/skills/ageerle/ruoyi-ai/github-novel-adaptation"><img src="https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/github-novel-adaptation/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/github-novel-adaptation"><img src="https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/github-novel-adaptation.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 | $0.00000 | $0.00612 |
| Opus 5.5 | $0.00000 | $0.00245 |
| Sonnet 5.5 | $0.00000 | $0.00122 |
| Haiku 4.5 | $0.00000 | $0.00061 |
Grade A, and why
github-novel-adaptation 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 3d 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
说好 · 小说改编与制作资料
改编范围
以用户提供的原著、章节和已确认取舍为依据。先确认当前需要大纲、角色、剧本还是分镜；已有材料可从对应阶段进入，不补造无用的上游文档。
改编方法
长原著按真实章节边界建立索引，记录读到的范围、重要人物、因果事件和改编保留点。关键改动保留来源场次或章节依据；未读段落保持待核对，不能凭书名补情节。 大纲先确定主线目标、障碍、选择和后果，人物关系与场景职责随之确定。每集留下本集变化和下一集继续的原因；悬念需要在后续事件兑现，不将反转间隔、角色档上限或三幕结构设成所有作品的硬门槛。 人物设定区分身份、行为、关系、外观和声音；场景与道具区分固定形态与当时状态。资产清单从已写故事汇总，反向核对没有遗漏剧情关键物，不为丰富画面擅自增添物件。 剧本用动作与对白交替表现人物的决定，不把梗概直接扩成讲解词。对白按人物需求、知情边界和语气精修；尚无录音时将语速估算标明，必要行动与停顿另计，不能只按字数推断片长。
项目交接
保留现有剧本、角色、地点和道具记录作为事实源，原著索引只作辅助。分镜只落实已接受的故事和资产决定，发现上游矛盾先回到对应阶段修订。制作资料按实际集数和镜号关联，不照搬来源的文件名或 JSON schema。
项目接入边界
本技能提供当前阶段的制作方法，沿用项目现有数据、输出结构、模型目录与内容审阅。用户原文、已批准资产和当前项目决定优先；来源示例不是本剧事实。模型参数与参考语法交给本项目实际供应商适配，不从旧手册推定平台能力。 首帧按需使用，不是生成前置条件；不默认补图。视频正文采用连续导演描述，时长预算独立保存为 timing。写作、修订和技能安装不会提交付费图片、视频、配音或音乐任务。附属脚本仅作文本资料。 修订已有分镜保留已批准图片、连续性、素材任务编号和制作版本；当前只处理有问题的阶段。结构检查、任务完成与成片画面、运动和声音验收分别记录。
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 23 lines · 0 tokens per session scan A c7faf1229e1b
github-novel-adaptation is a skill published in the GitHub repository ageerle/ruoyi-ai (5,773 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 612 tokens. 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 2026-10-21.
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.
surfsense-documents
Make or change a Word document (.docx), a PDF, a PowerPoint deck (.pptx) or an Excel workbook (.xlsx) by writing a Python script that surfsenserenderdocument runs, optionally starting from a source's own Word or PowerPoint file. Load it whenever the user asks for one of these, or for a change to one you made.
surfsense-data
Work out numbers from spreadsheet and CSV sources (.xlsx, .csv, .tsv) by writing a pandas script that surfsenseanalyzedata runs: totals, averages, trends, rankings, comparisons, cleaning, and charts that can go into a document. Load it whenever the user asks for figures from a table, or a chart of one.
video
Create polished narrated MP4 videos with Remotion in the sandbox.
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.
Create polished PDF files for requests such as PDFs, resumes, CVs, reports, letters, one-pagers, and printable documents.