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Agent Skill · 研究检索

conversion(conversion 搜索)

conversion 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。

conversion 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 67,317。

总安装 247周安装 10GitHub Stars 168下载 78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:conversion(conversion 搜索)
来源仓库:https://github.com/whawkinsiv/claude-code-skills
仓库路径:skills/conversion
安装命令:
npx skills add https://github.com/whawkinsiv/claude-code-skills --skill conversion
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/whawkinsiv/claude-code-skills --skill conversion

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。

conversion 专注于转化率优化,识别用户流失关键节点。强调去除摩擦、加速加载速度、利用社会证明三大杠杆。主张每页应有单一明确目标,避免功能堆砌。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。适用于着陆页、广告落地页等高流量页面的性能调优。

conversion 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/conversion

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/whawkinsiv/claude-code-skills --skill conversi…;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

conversion 怎么安装?

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

conversion 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。

conversion 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。

conversion 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。

conversion 用的人多吗?

公开数据是累计安装 247 次,近一周安装 10 次,下载 78 次,GitHub 168 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。

conversion 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。
  • 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

  • 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
conversion

conversion 搜索 · 本页

247168需要联网未明确通过

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

Conversion Rate Optimization

Every page has one job. If you can't name it, the page is broken. This skill helps you find where users drop off and fix it.

Core Principles

  • Friction is the enemy. Every field, click, and decision point costs conversions.
  • Don't guess — measure. But don't measure everything — measure what drives revenue.
  • Social proof is the most underused conversion lever in SaaS.
  • Speed is a feature. Every 100ms of load time costs ~1% conversion.
  • The best optimization is often removal, not addition.

Finding Your Biggest Bottleneck

Before optimizing, find where users actually drop off.

Step 1: Map Your Funnel

Typical SaaS funnel:
  Landing page visit → Signup page viewed → Account created →
  Onboarding started → Key action completed → Returned next week →
  Upgrade page viewed → Subscription created

Step 2: Measure Drop-Off

Tell AI:

Analyze our conversion funnel:
- Pull the number of users at each step: [list your funnel steps]
- Calculate the drop-off % between each step
- Identify the step with the biggest drop-off — that's our priority
- Show results in a table: Step | Users | Drop-off %

If you don't have analytics yet: Set them up first (see analytics-instrumentation skill). In the meantime, track manually: count signups, count activations, count paying customers. Even rough numbers reveal the biggest leak.

Step 3: Diagnose Why

For the biggest drop-off, evaluate the page/flow using this framework:

  1. CLARITY: Does the user know what to do and why?
  2. MOTIVATION: Is the value of completing this step obvious?
  3. FRICTION: What's making this harder than it needs to be?
  4. ANXIETY: What fears or objections might stall the user?
  5. DISTRACTION: What elements compete with the primary action?

Signup & Registration

  • Minimize fields. Email + password is ideal. Email-only or SSO is even better.
  • Defer everything else to onboarding (company name, role, team size).
  • Show password requirements before the user types, not after they fail.
  • Social login (Google, GitHub) should be visually prominent if your audience uses them.
  • Post-signup, go DIRECTLY to value — not a "check your email" dead end.

Tell AI:

Simplify our signup flow:
- Reduce to email + password (or email-only with magic link)
- Add Google Sign-In as the most prominent option
- After signup, redirect directly to onboarding (not "check your email")
- Defer all profile questions (name, company, role) to later

Pricing Page Optimization

  • Always include a recommended/highlighted tier.
  • Show annual pricing by default with monthly as a toggle.
  • Use price anchoring: show the most expensive plan first or feature the mid-tier.
  • "Free forever" converts better than "free trial" for hesitators.
  • Add FAQ section: "Can I cancel anytime?", "What happens to my data?", "Is there a setup fee?"

Tell AI:

Optimize our pricing page:
- Highlight the recommended tier with a visual badge ("Most Popular")
- Default to annual pricing (show monthly as toggle)
- Add a comparison table showing features by tier
- Add FAQ section below pricing addressing common objections
- Add social proof near the CTA: "[X] teams already use [Product]"

Trial-to-Paid Conversion

  • Reverse trial: Give full access, then downgrade — users feel loss aversion.
  • Show usage vs. plan limits: "You've used 847 of 1,000 API calls this month."
  • Trigger upgrade prompts at the moment of value, not on a timer.
  • Frame limits as growth: "Your team is growing! Upgrade to add unlimited members."

Tell AI:

Improve trial-to-paid conversion:
- Show usage meters on the dashboard: "X of Y [resource] used"
- When user hits 80% of a limit, show a gentle prompt: "You're growing! Upgrade for unlimited [resource]"
- 3 days before trial ends, show banner: "Your trial ends [date]. Keep everything by upgrading."
- After trial ends, downgrade features but keep their data intact

Form Optimization

  • Multi-step forms convert 20-40% better than single long forms.
  • Show progress: "Step 2 of 3"
  • Start with easy/engaging questions (not name/email).
  • Use smart defaults: pre-select the most common option.
  • Inline validation on blur. Show checkmarks for completed fields.

Tell AI:

Convert our [signup/onboarding] form to multi-step:
- Step 1: The easiest, most engaging question
- Step 2: The information we need to deliver value
- Step 3: Account details (email, password)
- Add progress indicator ("Step 2 of 3")
- Validate inline on blur with green checkmarks
- Use appropriate input types (email, tel, number) for mobile keyboards

Behavioral Triggers

TriggerHow to Use It
Loss aversion"Your free trial ends in 3 days" > "Upgrade now"
Social proof"4,200 teams signed up this month"
AnchoringShow the "before" (manual, slow) vs. "after" (with your product)
Commitment/consistencySmall yes → big yes. Free tool → signup → paid.
Scarcity (use honestly)"3 spots left in this cohort" (only if true)

Tell AI:

Add social proof and behavioral triggers to our [signup/pricing/landing] page:
- Add a live counter or recent activity: "[X] teams signed up this month"
- Add testimonial quotes near the CTA
- Add trust badges near payment forms (SSL, money-back guarantee)
- Frame the CTA as low-commitment: "Start free — no credit card required"

A/B Testing (Simple Version)

You don't need complex testing infrastructure. Here's the bootstrapped founder approach:

When to A/B Test

  • You have at least 100 users/week going through the flow
  • You have a specific hypothesis, not just "let's try something different"
  • The change is significant enough to matter (button color doesn't matter; headline copy does)

How to Run a Test

Tell AI:

Set up a simple A/B test:
- Create a feature flag that splits users 50/50
- Variant A: [current version]
- Variant B: [proposed change]
- Track [conversion event] for both variants
- Run until we have 100+ users per variant (or 2 weeks, whichever is longer)
- Show me the conversion rate for each variant

Reading Results

  • >20% difference: Likely real. Ship the winner.
  • 5-20% difference: Might be real. Run longer or test with more users.
  • <5% difference: Probably noise. Either change doesn't matter or your test needs more volume.

Rule: Don't peek at results daily and stop early. Set a duration and stick to it.


What to Measure

MetricWhat It Tells You
Signup rate (visitor → account)Is your landing page compelling?
Activation rate (account → key action)Is your onboarding working?
Trial-to-paid conversionIs your product delivering enough value?
Time to valueHow fast do users reach "aha"?
Expansion revenue triggersWhat behavior precedes upgrades?

Common Mistakes

MistakeFix
Optimizing low-traffic pagesFocus on your highest-traffic funnel step
A/B testing button colorsTest headlines, CTAs, and page structure instead
Adding more fields "for data"Every field costs conversions. Defer to later.
Ignoring mobile50%+ of traffic is mobile. Test there first.
Complex testing tools at small scaleFeature flags are enough until 1,000+ users/week

Related Skills

  • growth — PLG strategy, activation, and viral loops
  • landing-page — Build and optimize the pages driving conversions
  • pricing — Pricing page optimization and tier design
  • analytics — Track funnel metrics and measure experiments
  • copywriting — Write CTAs and headlines that convert

平台分布

Codex

36.72%
按下载量换算29

Claude

32.45%
按下载量换算25

Cursor

18.81%
按下载量换算15

Gemini CLI

8.39%
按下载量换算7

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。目前只有一个公开来源,建议同时核对源仓库。

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