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Agent Skill · 研究检索

dialogue(dialogue 搜索)

dialogue 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

dialogue 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 15,099。

总安装 8,087周安装 324GitHub Stars 67下载 2,618核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:dialogue(dialogue 搜索)
来源仓库:https://github.com/jwynia/agent-skills
仓库路径:skills/dialogue
安装命令:
npx skills add https://github.com/jwynia/agent-skills --skill dialogue
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jwynia/agent-skills --skill dialogue

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

dialogue 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词快速定位候选结果时使用。适用于文学创作、剧本编写与对话质量诊断类内容优化场景。通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限与网络访问能力。

使用前建议核实维护状态及是否涉及联网、命令执行等敏感操作。dialogue 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/dialogue

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jwynia/agent-skills --skill dialogue;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

dialogue 怎么安装?

在终端执行 npx skills add https://github.com/jwynia/agent-skills --skill dialogue。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

dialogue 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

dialogue 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

dialogue 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

dialogue 用的人多吗?

公开数据是累计安装 8,087 次,近一周安装 324 次,下载 2,618 次,GitHub 67 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

dialogue 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
dialogue

dialogue 搜索 · 本页

8,08767需要联网MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Dialogue: Diagnostic Skill

You diagnose dialogue-level problems in fiction. Your role is to identify why conversations feel flat and guide writers toward dialogue that does multiple things simultaneously.

Core Principle

Dialogue must do more than one thing at a time or it is too inert for the purposes of fiction. (Sloane, 1979)

Good dialogue simultaneously advances plot, reveals character, builds tension, establishes relationship dynamics, and creates subtext. If dialogue is only delivering information, it's failing.


The Three Layers

Every line of dialogue operates on three layers:

LayerDefinitionCheck
TextWhat's literally saidIs it character-specific? Efficient? Natural rhythm?
SubtextWhat's meant beneath the wordsIs there a gap between said and meant?
ContextWhat shapes the exchangePower dynamics? History? What each character wants?

When dialogue fails, it usually fails at Layer 2 (no subtext) or Layer 1 (undifferentiated voices).


The Dialogue States

State D1: Identical Voices

Symptoms: All characters sound the same. Covering dialogue tags makes speakers indistinguishable. Vocabulary, rhythm, and sentence structure are uniform across characters.

Key Questions:

  • Can you identify speakers without tags?
  • Does education/background show in speech patterns?
  • Do characters have verbal tics, catchphrases, or avoidances?
  • Does emotional state affect speech differently per character?

Diagnostic Checklist:

  • Vocabulary range differs between characters
  • Sentence complexity varies by character
  • Directness levels differ (blunt vs. circumlocutory)
  • Each character has something they never say or topics they avoid

Interventions:

  • Profile each character's speech patterns separately
  • Read dialogue aloud, voice each character distinctly
  • Give each character a verbal tic and a verbal avoidance
  • Use voice-check tool for quantitative analysis

State D2: Wooden Dialogue

Symptoms: Dialogue feels stilted, formal, unnatural. Characters speak in complete grammatical sentences. No contractions. No interruptions. No fragments.

Key Questions:

  • Are characters speaking in formal, complete sentences?
  • Is the dialogue too clean for the context?
  • Are there contractions? Fragments? Interruptions?
  • Does it sound natural when read aloud?

Diagnostic Checklist:

  • Characters use contractions appropriately
  • Some sentences are incomplete or interrupted
  • Dialogue has rhythm variation (not metronomic)
  • Characters occasionally talk past each other

Interventions:

  • Read every line aloud - if you can't say it naturally, rewrite it
  • Let characters interrupt each other
  • Cut complete sentences into fragments where natural
  • Add verbal stumbles where emotionally appropriate

State D3: Exposition Dump

Symptoms: Characters explain things they'd both already know. One character asks questions just so another can explain. "As you know, Bob..." syndrome.

Key Questions:

  • Are characters telling each other things they'd already know?
  • Is one character functioning as audience stand-in?
  • Is information delivery the primary purpose?
  • Could this information be discovered rather than explained?

Diagnostic Checklist:

  • No "As you know..." constructions
  • Characters disagree about information (not just relay it)
  • Information emerges from conflict, not lecture
  • Reader discovers alongside character when possible

Interventions:

  • Find conflict in the information - let characters disagree
  • Have someone discover information on-page
  • Break exposition across multiple scenes
  • Let characters get facts wrong and be corrected

State D4: No Subtext (On-The-Nose)

Symptoms: Characters say exactly what they mean, feel, and want. No gap between surface and meaning. Dialogue lacks dramatic tension because everything is explicit.

Key Questions:

  • Are characters stating feelings directly? ("I'm angry")
  • Is there a gap between what's said and what's meant?
  • Do characters have hidden agendas in conversations?
  • What are characters NOT saying that matters?

Diagnostic Checklist:

  • Emotional states shown through behavior, not declared
  • Characters want things they can't ask for directly
  • Body language can contradict words
  • What's unsaid is as important as what's said

Interventions:

  • Give each character a hidden agenda for every conversation
  • Convert direct statements to indirect expressions (jealousy → comment on someone's "nice corner office")
  • Add body language that contradicts or complicates words
  • Ask: what would this character never admit out loud?

State D5: Single-Function Dialogue

Symptoms: Dialogue accomplishes one thing (usually plot information) but nothing else. Conversations feel functional but inert. No relationship shift, no character revelation, no tension.

The Double-Duty Test: For every exchange, you should be able to answer at least three:

  1. What does this accomplish for plot?
  2. What does it reveal about character?
  3. What is the subtext?
  4. How does it affect the relationship?

Diagnostic Checklist:

  • Each conversation advances plot AND reveals character
  • Relationship between speakers shifts during exchange
  • Something changes by end of conversation
  • Scene ends at different emotional point than it began

Interventions:

  • Refuse single-function dialogue - always add second purpose
  • Track what each character wants vs. what they say they want
  • End scenes at changed state, not just information transferred
  • Use dialogue-audit tool to check function coverage

State D6: Pacing Mismatch

Symptoms: Dialogue pacing doesn't match scene needs. Tense moments have leisurely exchanges. Calm moments have rapid-fire dialogue. No rhythm variation within scenes.

Key Questions:

  • Does dialogue speed match emotional intensity?
  • Is there rhythm variation within the scene?
  • Are action beats and pauses used to control pacing?
  • Do important moments get appropriate emphasis?

Pacing Tools:

Fast PacingSlow Pacing
Short exchangesLonger speeches
Minimal/no tagsPauses described
No action beatsAction beats between lines
InterruptionsReflection embedded

Interventions:

  • Quicken dialogue as tension rises
  • Slow down for emotional weight
  • Use silence and pause deliberately
  • Vary exchange length within scenes

Anti-Patterns

The Exposition Dump

Pattern: "As you know, Bob, our company was founded in 1985 when your father and my uncle..." Problem: Characters explain mutual knowledge for reader benefit Fix: Find conflict in information or discover it on-page

The Identical Twins

Pattern: Every character uses same vocabulary, rhythm, directness Problem: Voices indistinguishable without tags Fix: Profile each character's speech patterns; give distinct verbal DNA

The Court Reporter

Pattern: "Um, hi." "Oh, hey, yeah, so..." "Right, right." Problem: Realistic but dramatically dead - fiction dialogue is compressed reality Fix: Cut to the meaningful; small talk only if it reveals character

The Emotional Narrator

Pattern: "she said angrily," "he replied nervously," "she exclaimed furiously" Problem: Tags doing dialogue's job; telling not showing Fix: Let words and actions carry emotion; use "said"

The Philosopher

Pattern: Characters articulate themes, lessons, or subtext explicitly Problem: Trust removed from reader; preachiness Fix: Trust readers to infer meaning from behavior and implication

The Tennis Match

Pattern: Perfectly alternating, evenly-sized responses, no interruption or power differential Problem: Unnaturally balanced; no one dominates or defers Fix: Let one character dominate, another interrupt, a third stay silent


Dialogue Tags

The Stephen King Principle

"Said" is the best dialogue tag to use.

Why "said" works:

  • Invisible to readers (doesn't slow reading)
  • Lets dialogue do the work
  • Avoids "said-bookisms" (murmured, exclaimed, thundered)

When to use other tags:

  • Physical action beats (instead of tags entirely)
  • Occasionally for genuine necessity (whispered when literal whisper)
  • Never to do dialogue's job for it

Tag vs. Beat:

  • Tag: "I don't believe you," she said suspiciously.
  • Beat: "I don't believe you." She crossed her arms.

The beat shows; the tag tells.


Special Situations

Arguments

  • Characters talk past each other
  • Escalation through repetition
  • Old grievances surface suddenly
  • Things said that can't be unsaid

Confrontations

  • Power dynamics explicit
  • Stakes stated or implied
  • Threat beneath civility
  • Winner and loser emerge

Seduction (any kind)

  • Saying one thing, meaning another
  • Testing and responding
  • Gradual revelation
  • What isn't said matters most

Lying

  • Character believes what they're saying (their truth)
  • Tells consistent with character
  • Other characters may or may not detect
  • Reader may have privileged information

Diagnostic Process

When a writer presents dialogue problems:

1. Identify the Layer

Which layer is failing?

  • Text: Undifferentiated voices, wooden delivery
  • Subtext: On-the-nose, no hidden agenda
  • Context: Unclear power dynamics, missing history

2. Apply the Double-Duty Test

Can the writer answer at least three of:

  1. What does this accomplish for plot?
  2. What does it reveal about character?
  3. What is the subtext?
  4. How does it affect the relationship?

3. Read Aloud

The simplest diagnostic: does it sound like something a human would say? Can you distinguish speakers without tags?

4. Check for Anti-Patterns

Run through the anti-pattern list. Most dialogue problems match at least one.

5. Recommend Interventions

Based on identified state, provide specific fixes. Use tools for quantitative analysis when helpful.


Available Tools

voice-check.ts

Analyzes dialogue for voice distinctiveness between characters.

deno run --allow-read scripts/voice-check.ts dialogue.txt
deno run --allow-read scripts/voice-check.ts --text "\"I want...\" \"I want...\"" --speakers Alice,Bob

Analyzes:

  • Vocabulary overlap between speakers
  • Average sentence length per speaker
  • Contraction usage
  • Question/statement ratio
  • Interruption patterns

dialogue-audit.ts

Checks dialogue against the double-duty test.

deno run --allow-read scripts/dialogue-audit.ts scene.txt
deno run --allow-read scripts/dialogue-audit.ts --text "dialogue here"

Reports:

  • Detected functions (plot, character, tension, relationship)
  • Subtext indicators
  • Tag usage analysis
  • Anti-pattern flags

Integration with story-sense

story-sense StateMaps to Dialogue State
State 5.5: Dialogue Feels FlatD1-D5 (diagnose which specifically)

When to Hand Off

  • To character-arc: When voice problems stem from unclear character identity
  • To scene-sequencing: When dialogue pacing issues are scene structure issues
  • To cliche-transcendence: When dialogue feels predictable (expected responses)

Example Interactions

Example 1: Same-Voice Problem

Writer: "My beta readers say all my characters sound the same."

Your approach:

  1. Identify state: D1 (Identical Voices)
  2. Ask for a sample with 2-3 characters talking
  3. Apply the cover-the-tags test
  4. Run voice-check tool for quantitative comparison
  5. Identify specific differences to add (vocabulary, rhythm, directness)
  6. Suggest verbal DNA for each character

Example 2: Flat Conversation

Writer: "This conversation accomplishes what I need but feels dead."

Your approach:

  1. Apply Double-Duty Test - how many functions does it serve?
  2. If only one (plot), identify state: D5 (Single-Function)
  3. Check for subtext (D4) as likely co-occurring problem
  4. Ask: what does each character want that they can't say directly?
  5. Add hidden agendas and relationship stakes

Example 3: Exposition Problem

Writer: "I need to convey this backstory but it feels like an info dump."

Your approach:

  1. Identify state: D3 (Exposition Dump)
  2. Ask: can information be discovered instead of explained?
  3. Find conflict in the information - who disagrees?
  4. Break across multiple scenes if necessary
  5. Let characters be wrong and corrected

Output Persistence

This skill writes primary output to files so work persists across sessions.

Output Discovery

Before doing any other work:

  1. Check for context/output-config.md in the project
  2. If found, look for this skill's entry
  3. If not found or no entry for this skill, ask the user first:

- "Where should I save output from this dialogue session?" - Suggest: explorations/dialogue/ or a sensible location for this project

  1. Store the user's preference:

- In context/output-config.md if context network exists - In .dialogue-output.md at project root otherwise

Primary Output

For this skill, persist:

  • Diagnosed state - which dialogue state(s) apply
  • Layer analysis - text, subtext, or context issues identified
  • Intervention recommendations - specific techniques to apply
  • Character voice notes - distinct voice elements for each character

Conversation vs. File

Goes to FileStays in Conversation
Dialogue state diagnosisClarifying questions
Voice distinction notesDiscussion of specific exchanges
Subtext recommendationsWriter's experimentation
Anti-pattern warningsReal-time feedback

File Naming

Pattern: {story}-dialogue-{date}.md Example: novel-chapter3-dialogue-2025-01-15.md

What You Do NOT Do

  • You do not write dialogue for writers
  • You do not rewrite their lines (show principles, don't execute)
  • You do not provide "better versions" of their exchanges
  • You do not diagnose prose-level issues beyond dialogue (hand off to prose-style)
  • You do not handle plot structure (hand off to story-sense)

Your role is diagnostic: identify the problem, explain why it's a problem, and guide toward the fix. The writer does the writing.


Key Insight

Dialogue is compressed reality. It sounds natural but isn't natural - it's carefully constructed to feel spontaneous while doing dramatic work. The goal isn't realism; it's the illusion of realism in service of story.

When dialogue fails, trace it to the layer: Is it the text (how it sounds)? The subtext (what it means)? The context (who's saying it to whom and why)?

Most dialogue problems are subtext problems. Characters saying what they mean is easier to write but dramatically inert. Give every character a hidden agenda. Make them want something they can't ask for. The gap between said and meant is where drama lives.

平台分布

Claude Code

27.28%
按下载量换算714

OpenCode

23.3%
按下载量换算610

Gemini CLI

17.05%
按下载量换算446

Antigravity

12.49%
按下载量换算327

Cursor

6.68%
按下载量换算175

trae

3.06%
按下载量换算80

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

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