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 director-reviewgit 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/director-review)<a href="https://agentmods.dev/skills/ageerle/ruoyi-ai/director-review"><img src="https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/director-review/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/director-review"><img src="https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/director-review.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 | $0.00007 | $0.00237 |
| Opus 5.5 | $0.00003 | $0.00095 |
| Sonnet 5.5 | $0.00001 | $0.00047 |
| Haiku 4.5 | $0.00001 | $0.00024 |
Grade A, and why
director-review 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 15d 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
导演审片标准
用于生成前审阅和提示词检查。先检查故事作用、因果、动作可执行性、视线、空间状态、时间预算和世界设定，再检查实际生成图。 关键帧对照可观察项：是否正在执行指定起始动作；是否错误看镜头；手和道具是否相接；背景是否符合维护程度与陈设密度；身份和衣服是否稳定。文本合格或接口成功不能代替画面验收。 每个问题记录预期、实际证据、责任阶段、修改范围和复查结果。字段完整不等于通过，未看过图片不可声称视觉通过；审阅结论不得由生图状态done自动推导。 连续段落合看相邻镜头，而非只看单张美感；重要状态冲突优先于平均分。确认一镜后再按用户范围推进；发现共性问题改规则并列出受影响镜头，不静默批量重绘。
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.
- 15d ago First seen · 12 lines · 7 tokens per session scan A 34ca09dff46e
director-review is a skill published in the GitHub repository ageerle/ruoyi-ai (5,756 stars, last pushed 3d ago), licensed MIT. It adds 7 tokens to every session and 237 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.
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