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Agent Skill · 研究检索

email-response-simulation(电子邮件回复模拟)

email-response-simulation 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。

email-response-simulation 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;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 46,660。

总安装 768周安装 32GitHub Stars 93下载 256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
unknown

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:email-response-simulation(电子邮件回复模拟)
来源仓库:https://github.com/extruct-ai/gtm-skills
仓库路径:skills/email-response-simulation
安装命令:
npx skills add https://github.com/extruct-ai/gtm-skills --skill email-response-simulation
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/extruct-ai/gtm-skills --skill email-response-simulation

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。

email-response-simulation 模拟真实收件人阅读视角对邮件进行批判性评估。适用于 Tier 1 潜在客户邮件的质量把关与可信度增强。识别 LinkedIn 爬取痕迹等致命破绽并提供针对性修改建议。输出反馈聚焦心理感知层面,需配合其他优化手段共同提升转化效果。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/email-response-simulation

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/extruct-ai/gtm-skills --skill email-response-s…;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

email-response-simulation 怎么安装?

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

email-response-simulation 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。

email-response-simulation 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。

email-response-simulation 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

email-response-simulation 用的人多吗?

公开数据是累计安装 768 次,近一周安装 32 次,下载 256 次,GitHub 93 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。

email-response-simulation 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
email-response-simulation

电子邮件回复模拟 · 本页

76893需要联网未明确有提醒

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

Copy Feedback

Simulate a real prospect reading your cold email. Build their world, then roast the email through their eyes.

Related Skills

email-generation → email-response-simulation → campaign-sending

Run this for Tier 1 prospects only — the ones worth individual attention. For Tier 2, use templates from email-generation directly.

Scraping Tell Detection

During the simulation, check the email for signals that reveal the data was scraped from LinkedIn or a database. These are instant credibility killers — the prospect recognizes them and mentally files the email as automated spam.

Common tells to flag:

  • Titles left in names — "Hey Dr. Martinez" or "Hi Prof. Chen" screams LinkedIn scrape. Real humans say "Hey Carlos"
  • Over-formal name usage — using full name ("Dear Jonathan Smith") instead of first name
  • LinkedIn headline as job title — if the email references a title that's clearly copy-pasted from LinkedIn (e.g. "As a Serial Entrepreneur | Angel Investor | Speaker")
  • Stale data — referencing a role or company the prospect has already left

Flag these as High severity risk flags in Phase 4. Any scraping tell detected should be called out in the Emotional Reaction (Phase 3, Pass 1) as an immediate red flag.

When to Use

  • After email-generation produces a draft for a Tier 1 company
  • When you want to validate whether a specific person would reply
  • When you're training your instinct for a new audience before automating
  • When the user says "would [name] reply to this?" or "roast this email"

Environment

Provider selection and credentials are handled in Phase 1 of the workflow. If LinkedIn data is not available from the Extruct people table, a deep research provider is needed — the skill will ask which one to use.

Inputs

InputRequiredSource
Draft email textyesUser pastes or from email-generation output
Prospect nameyesFrom contacts CSV or user input
Prospect companyyesFrom contacts CSV or user input
Prospect job titleyesFrom contacts CSV or user input
Prospect LinkedIn URLstrongly recommendedFrom people-search output
Hypothesis matchedrecommendedFrom list-segmentation output
Extruct people table dataoptionalLinkedIn Data column from people-search

Workflow

Phase 1: Data Enrichment and World Building

Gather as much public data as possible, then simulate the prospect's full world.

Step 1a: Scrape public data

If LinkedIn data is available from the Extruct people table (linkedin_data column), use it directly. Otherwise, run research queries via the chosen deep research provider (from Environment).

Query 1 — Professional identity:

"Research [Name], [Title] at [Company]. Find their LinkedIn About section, career history, previous companies and roles, education, and any professional accomplishments. Include their full career arc — where they started, how they got to this role. Look at LinkedIn, company bios, conference speaker pages, and press mentions."

Query 2 — Public voice and positions:

"Has [Name] from [Company] written or said anything publicly? Look for LinkedIn posts, blog posts, podcast appearances, conference talks, interviews, or published articles. What topics do they engage with? What language do they use? Include direct quotes if available."

Query 3 — Company and role context:

"What is [Company] doing right now? Recent news, strategic initiatives, funding, product launches, or hiring signals from the last 12 months. What challenges would a [Title] at this type of company be dealing with? What does their team likely look like?"

Step 1b: Simulate their world

Using the research, build a vivid simulation of this person's professional reality. Go deep — the goal is to predict how they think, not just what they do.

## World Simulation: [Name]

### Daily Reality
- **What their day looks like:** [Meetings, priorities, where they spend time]
- **Tools they live in:** [CRM, Slack, email volume, dashboards]
- **What keeps them up at night:** [The 1-2 problems they can't solve yet]

### Psychology and Decision-Making
- **Decision style:** [Data-driven / gut / consensus-seeker / authority-based]
- **Communication preference:** [Terse / detailed / formal / casual / story-driven]
- **Risk appetite:** [Early adopter / wait for proof / only buys market leaders]
- **Trust signals:** [What makes them trust a vendor — referrals, data, case studies, free trial]

### Inbox Behavior
- **Email volume:** [Estimate — 50/day? 200/day?]
- **Cold email tolerance:** [Opens most? Deletes by subject? Has assistant filter?]
- **Reply-blocking mindset:** [What makes them NOT reply even if interested]
- **What triggers a reply:** [Specific enough to feel researched, not so specific it feels creepy]

Phase 2: Professional Reality

Define the parameters that determine whether your email hits or misses.

## Professional Reality

### KPIs and Motivators
- **Measured on:** [The 2-3 KPIs their boss actually evaluates them on]
- **Career motivator:** [What they're trying to achieve — promotion, build something, stability]
- **Internal politics:** [Who do they need buy-in from? Budget authority?]

### Pain Points (ranked by severity)
1. [Most acute pain — the thing that wastes their time or blocks their goals]
2. [Second pain]
3. [Third pain]

### Relationship to Your Solution
- **Awareness level:** [Never heard of tools like this / aware of category / tried competitors]
- **Current workaround:** [How they solve this problem today without you]
- **Switching cost:** [What would they have to give up or change to use you]

Phase 3: Skeptical Buyer Roast

Now put on the prospect's hat and read the email cold. Two distinct passes:

Pass 1: Emotional Reaction (2 seconds)

This is the gut response — before any rational evaluation. Read the email as if you're this person, scanning your inbox between meetings.

## Emotional Reaction

**Subject line gut feel:** [What they think in 0.5 seconds]
**First sentence gut feel:** [Do they keep reading or move on?]
**Overall vibe:** [Feels like spam / feels like a human / feels like someone who gets my world]
**Immediate red flags:** [Anything that triggers "delete" instinct]

Pass 2: Business Evaluation (10 seconds)

If they made it past the emotional filter, they now evaluate the substance. This is the more calculated read.

## Business Evaluation

**Does this hit my KPIs?** [Yes/no — and which one specifically]
**Priority level:** [Would I deal with this today, this week, this quarter, or never?]
**Bridge quality:** [How strong is the connection between my pain and their solution?]
**Credibility check:** [Do I believe this person/company can deliver?]
**Effort-to-value ratio:** [Is the CTA worth my time? What am I risking by replying?]

Phase 4: Risk Flags and Refinement

Identify specific issues in the copy that reduce reply probability.

## Risk Flags

| Flag | Location | Severity | Issue |
|------|----------|----------|-------|
| [flag type] | [P1/P2/P3/P4/subject] | [High/Med/Low] | [what's wrong] |

Flag types to check:

  • Spam trigger — phrasing that sounds like mass email, not personal
  • Wrong pain — opener references a problem this person doesn't actually have
  • Weak bridge — gap between their pain and your solution is too big or too vague
  • Bad personalization — mentions something generic disguised as personal
  • CTA mismatch — ask is too big (meeting) or too small (nothing) for this prospect
  • Tone clash — email tone doesn't match how this person communicates
  • Credibility gap — proof point doesn't resonate with this type of buyer
  • Length violation — too long for their inbox behavior
  • Scraping tell — name, title, or data reveals it was pulled from LinkedIn or a database (titles left in names, LinkedIn headline as job title, stale role data)

Phase 5: Output

Present the full analysis and rewrite.

## Copy Feedback: [Name] at [Company]

### Verdict
**Would they reply?** [Yes / Maybe / No]
**Reasoning:** [1-2 sentences — the real reason, not a polite version]

### Emotional Reaction Summary
[2-3 sentences — what they feel in the first 2 seconds]

### Business Evaluation Summary
[2-3 sentences — does it hit their KPIs, is the bridge strong]

### Risk Flags
[Table from Phase 4]

### Ranked Changes
1. **[Highest impact]**
   - Current: "[exact text]"
   - Problem: [why it fails for THIS person]
   - Rewrite: "[new text]"

2. **[Second]**
   - Current: ...
   - Problem: ...
   - Rewrite: ...

3. **[Third]**
   ...

### Rewritten Email
[Full email with all changes applied]

Phase 6: Iterate

After presenting, ask:

  • "Want to adjust any of the changes?"
  • "Want to run another prospect through the same email template?"
  • "Ready to finalize?"

Repeat Phases 3-5 until the user is satisfied.

Running One by One vs. Template Training

One by one (primary use): Run this for each Tier 1 prospect individually. The value prop, opener, and CTA should be tailored to their specific role and world.

Template training (secondary use): Even running 3-5 prospects through this process teaches you patterns about the audience. After a few roasts, you'll notice:

  • Which pain points consistently hit
  • Which CTAs work for which seniority
  • Which proof points resonate with which role type
  • What inbox behavior looks like for this ICP

Use these patterns to improve the base template in email-generation for Tier 2 prospects.

Guidelines

  • Never invent persona details. If research doesn't find something, say "unknown" and reason from the role/title instead.
  • Be brutally honest. If the email will be deleted, say so. Sugarcoating wastes the user's time.
  • The emotional reaction is primary. Most cold emails are killed in 2 seconds. The business case only matters if they survive the gut check.
  • Respect the voice rules. All rewrites must stay within the voice constraints from email-generation / email-prompt-building.
  • One email, one prospect. Never run in bulk. The whole point is depth.
  • The bridge is everything. The gap between "their pain" and "your solution" is where most emails fail. If the bridge is weak, no amount of copywriting fixes it — the hypothesis match might be wrong.

Reference

See references/persona-review-template.md for the full output template and red flag checklist.

平台分布

Codex

34.25%
按下载量换算88

Claude

31.5%
按下载量换算81

Cursor

19.42%
按下载量换算50

Gemini CLI

8.88%
按下载量换算23

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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