emotional-dialogue

emotional-dialogue is a skill for Claude Code, Codex from ageerle/ruoyi-ai. It costs 30 tokens per session (2,294 once invoked), scanned A, original, MIT.

A writing guide for building emotional scenes from what each person wants, avoids, says, and does. It explains how dialogue should include responses, misunderstandings, and small choices that change a relationship.

In plain words
What is it for?
Use it to write dialogue, relationship scenes, acting directions, character reactions, and timed performances for storyboards or scripts.
Why use it?
Scenes can feel forced when characters simply explain themselves, instantly reconcile, or react without a clear trigger. This keeps emotions connected to visible actions and information each character actually knows.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to write dialogue, relationship scenes, acting directions, character reactions, and timed performances for storyboards or scripts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ageerle/ruoyi-ai/emotional-dialogue
About the project

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.

ageerle/ruoyi-ai · 5,756 stars · on GitHub · doc.ruoyiai.chat

Install

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.

Any agent
npx skills add ageerle/ruoyi-ai --skill emotional-dialogue
Clone the repo
git clone --depth 1 https://github.com/ageerle/ruoyi-ai

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for emotional-dialogue

README.md
[![agentmods](https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/emotional-dialogue/github.svg)](https://agentmods.dev/skills/ageerle/ruoyi-ai/emotional-dialogue)
Your own site
<a href="https://agentmods.dev/skills/ageerle/ruoyi-ai/emotional-dialogue"><img src="https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/emotional-dialogue/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.

agentmods 80×15 button for emotional-dialogue

Your own site · 80×15
<a href="https://agentmods.dev/skills/ageerle/ruoyi-ai/emotional-dialogue"><img src="https://agentmods.dev/badge/skills/ageerle/ruoyi-ai/emotional-dialogue.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,294 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00030 $0.02294
Opus 5.5 $0.00012 $0.00918
Sonnet 5.5 $0.00006 $0.00459
Haiku 4.5 $0.00003 $0.00229

Measured 12d ago against content hash 048f76efb0ab, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

emotional-dialogue 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.

ruoyi-modules/ruoyi-chat/src/main/resources/short-drama/skills/emotional-dialogue/SKILL.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

情感与对白

剧本阶段

先区分每个人眼前要办的事、难以承认的需要和不愿被触碰的旧伤。配角也有自己的生活与顾虑,不是替主角解释真相的工具。 关系戏必须有双向回应:试探或请求→对方抵抗、误解或回避→说话者改换说法或行动→关系发生有限变化。正文直接写出可说出口的对白,不能以“二人交谈,理解了彼此”代替。 话题可以是零钱、座位、饭菜、物品去留;潜台词从上下文及回应成立,不把每句话写成人生金句。允许答非所问、改口、普通的幽默,但不能每句都省略或结巴。 情感转折需先有具体触发,再有抵抗,最后由一个有代价的小选择证明。帮助别人不自动抵消对家人的亏欠;理解、原谅、悲伤消失是不同事情。不能靠配角劝一句、遗书揭密、突然绝症或煽情旁白强行和解。 同一道具可以在不同关系阶段承担不同意义,但不要反复凝视道具代替交流。沉默必须是人物在听、忍住回应、决定留下等可识别行为,不用空转凑时长。 信息边界逐人核对:一句话提到的旧事必须有本人经历或前文告知作依据;创作资料里知道的事不等于角色知道。若配角回应毕业典礼等旧伤,先写主角实际说出该事,禁止读心。 交易动作逐笔核对付款人、收款人、金额、已付/未付;“记了金额”不等于“已收到钱”。不要为了制造推辞戏凭空增加退款、垫付或换手,动作与对白必须一致。 在输出前算术核对各场预计秒数之和与用户总时长,不能只在大纲声称达标;短小开场不能分配90秒。场次数服从时空和关系变化,不为七场把同一对话拆成多次往返。 大纲每场只交代“带着什么情绪进入→被哪件具体事触动→怎样回应→带着什么未解决的问题离开”;正文不附创作分析,保留行动和对白。用户事实优先,不照搬参考电影情节或台词。

台词精修与声音表演

已认可大纲但反馈台词生硬时,固定核心事件与时间线,先修角色口吻和双向表演,不擅自重做主线。为主要角色写清当前诉求、顾忌、与说话对象的地位差和信息边界;同一角色对上司、同行、孩子的说法应随关系改变。历史人物不全说文言,平民不默认粗俗;跨时代角色可在提问、改口和少量词汇中显出差别,不用连续现代梗代替人物。

至少检查一段完整交锋:对方是否抵抗、保留或误解,使说话者改变措辞或实际行动;不能只让配角轮流回答主角问题。将可拍的动作写进正文,例如收回一张账单、按住它、实际付钱,比“露出复杂表情”更能表达关系。听者在听、藏、试、忍或决定,不能全员停住等待台词。

去AI味不等于统一短句、频繁省略号、句句笑话或人人答非所问。按角色连读全部台词后,再连读同场对话;同时检查口吻可辨和回应自然。删掉编剧式主题总结,保留人物当下会说的普通话。导演参考需转写为可执行的方法和场景选择,不能只追加导演姓名与“电影感”。这些文本检查不代替成片声音试听。

对白至少经历意图稿与口语精修两个阶段。先明确此人此刻试图向谁索取、隐瞒、试探、拒绝或安抚什么,再写可直接说出口的原话。检查对方上一句话如何改变本句;不能让人物依次替编剧解释情节。

按人物教育、职业、关系、胆量及眼前压力区分词汇和句长,不用全员整齐短句、概念总结、对仗口号或结尾升华。连续两句都在下结论时,改为具体物件、被打断的行动、回避或争取。主角的机敏通过针对性回应体现,不靠每句金句。

去掉人名后检查核心角色的说法是否能互换;若能,调整意图和语气,而非机械增加方言词。方言来自身份和语境,保持可懂;短幽默服务关系或压力变化。

文字自然与音频自然分别审阅。每句表演写对话对象、当下目的、重音和必要停顿,不使用全员同一温暖清朗的朗读语气,也不堆情绪标签。沿用已授权且已确认的同角色声音参考;ASR只确认内容与时间,不能证明声音不机械。未试听时明确记录,不标为声音验收通过。

分镜与表演阶段

对白承担人物当下的行动:争取、拒绝、试探、遮掩或安抚要有对象,上一句的回应应影响下一句的做法。背景信息放在眼前交锋确实需要的位置,不让双方解释彼此已经知道的事实。潜台词从言行差异中成立,不把内心分析追加为解说。主要对白遮住人名后仍应有可辨的措辞与回应习惯,但不以统一方言、短句或口头禅制造区别。

表演先给人物目标与刺激,再写少量有落点的行为。倾听者可以仍在顶住门、护住物件或判断对方的反应;不让全员停下等台词,也不把每个情绪拆成眨眼、抿嘴、抬头的固定动作串。保留演员在同一目标下自然调整的余地。修订既有分镜时原对白、说话人及顺序保持;发现台词问题先记审阅意见,不能在视频指令中偷偷另写一套台词。

保留原文关键对白及回应顺序。source_text包含本镜真正说出的原话;timing.spoken_text只含实际发音,不含角色名、舞台提示。预算包括倾听反应,不能为塞满15秒删掉关系变化。 规划时为出镜人物提供performance_beats数组,每项{name,acting}。acting简明写出“被哪句原话/动作触发→此刻试图对谁做什么→可见回应→镜末仍保留什么情绪”。发言人与倾听者分别设计,不能同场所有人套同一句眼含热泪。 无对白镜头也应有来自原文的行为动机;没有人物的屏幕插入镜performance_beats为空数组。不得给录音中的父亲添加出镜表演。 亲密对话优先稳定机位与视线关系,允许把说话声延续到对方倾听画面;不强制每句反打,也不因情绪高潮自动推近、流泪或配悲伤钢琴。多人口型能力未经验证时,拆成一个主要说话人的镜头,不让双方同时开口。

Read the full file on GitHub · 59 lines

Changes

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.

  1. 12d ago Changed · +23 lines 048f76efb0ab
  2. 15d ago First seen · 36 lines · 30 tokens per session scan A 2d62f3fa28ee

Subscribe to this mod's changes

emotional-dialogue is a skill published in the GitHub repository ageerle/ruoyi-ai (5,756 stars, last pushed 3d ago), licensed MIT. It adds 30 tokens to every session and 2,294 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.

Related

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.

wecode-ai/Wegent · 51 tokens

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.

bojieli/ai-agent-book · 96 tokens

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.

bojieli/ai-agent-book · 125 tokens

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.

Tencent/AI-Infra-Guard · 48 tokens

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.

ConardLi/garden-skills · 226 tokens

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.…

ConardLi/garden-skills · 96 tokens