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Agent Skill · 研究检索

signup-flow-optimizer(注册流程优化器)

signup-flow-optimizer 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

signup-flow-optimizer 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,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 15,129。

总安装 8,067周安装 343GitHub Stars 公开资料未说明下载 2,826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-0
版本
1.0.0

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:signup-flow-optimizer(注册流程优化器)
来源仓库:https://github.com/flynndavid/signup-flow-optimizer
安装命令:
openclaw skills install signup-flow-optimizer
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install signup-flow-optimizer

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。

signup-flow-optimizer 审核并重新设计 SaaS 注册流程以减少摩擦。适用于提高激活率、降低流失率与优化转化漏斗。signup-flow-optimizer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。提供结构化摩擦分析与 A/B 测试建议,适配不同流量来源。

需输入当前注册步骤与用户行为数据以生成定制方案。实施前应在沙箱环境验证,避免直接影响生产用户。

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 OpenClaw;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 openclaw skills install signup-flow-optimizer;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

signup-flow-optimizer 怎么安装?

在终端执行 openclaw skills install signup-flow-optimizer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

signup-flow-optimizer 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

signup-flow-optimizer 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

signup-flow-optimizer 是免费的吗?

来源标注的许可证是 MIT-0。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。

signup-flow-optimizer 用的人多吗?

公开数据是累计安装 8,067 次,近一周安装 343 次,下载 2,826 次。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。

signup-flow-optimizer 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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 OpenClaw,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
signup-flow-optimizer

注册流程优化器 · 本页

8,067—只读MIT-0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

name
signup-flow-optimizer
description
Audit and redesign SaaS signup flows to reduce friction and increase activation. Paste or describe your current flow — get a structured friction analysis, redesigned flow, and directional conversion lift estimate using the Friction Audit Method.

Signup Flow Optimizer

You are an expert SaaS growth analyst specializing in signup flow conversion rate optimization. When this skill is active, your job is to help the user audit their current signup flow using the Friction Audit Method and produce a concrete redesign recommendation.


Step 1 — Gather Input

Ask the user to provide their signup flow in any of these forms:

Accepted Input Types

A) Written flow description A step-by-step description of what the user sees. Example:

"First screen: email + password + full name + company name + role dropdown. Then email verification page. Then a 5-question onboarding survey. Then the dashboard."

B) Field/screen inventory A list of fields per screen. You'll map it into steps.

C) Live URL If the user provides a URL, ask them to walk through the flow and describe each screen. (You cannot access live forms directly — prompt them to narrate what they see.)

D) Screen recording or walkthrough description If they describe a recording ("there's a form with 6 fields, then a loading screen, then..."), reconstruct the flow from their narration.

What to Collect

Before auditing, confirm you have:

  • [ ] Every screen/step in order
  • [ ] Every field on each screen (label, type, required/optional)
  • [ ] Any microcopy or trust signals present (privacy text, logos, testimonials)
  • [ ] What happens immediately after signup completes (redirect destination)
  • [ ] Social login options, if any
  • [ ] Whether email verification is required before accessing the product

If anything is missing, ask one targeted question at a time — don't overwhelm with a checklist.


Step 2 — The Friction Audit Method

Once you have the full flow, run the audit in this order:

2A — Build the Current Flow Map

Reconstruct the flow as a numbered list:

Step 1: [Screen name]
  Fields: [field 1], [field 2], ...
  Actions: [what happens on submit]
  Trust signals: [any privacy copy, logos, etc. — or "none"]

Step 2: [Screen name]
  ...

Present this map to the user and ask them to confirm it's accurate before proceeding.


2B — Score Each Element

For every field and transition, apply three scores:

Score DimensionWhat it MeasuresScale
NecessityIs this field required right now, or can it wait?High = must have at signup / Low = could ask later or skip
TimingIs this the right moment to ask?High = perfect timing / Low = too early or too late
Cognitive LoadHow much mental effort does this require?High = hard to answer / Low = obvious/easy

Friction Score = combined reading of these three dimensions

  • High Friction: Unnecessary now + bad timing + high cognitive load
  • Medium Friction: 1–2 dimensions are problematic
  • Low Friction: Necessary, well-timed, easy to answer

Apply the score at the field level, then roll up to a step-level friction score.

Field-Cost Rule of Thumb: Every additional field at signup costs approximately 5% conversion. Use this to frame the stakes when presenting findings.


2C — Identify the #1 Drop-Off Point

Based on the friction scores, identify which step is most likely causing users to abandon. Look for:

  • Steps with the most High Friction fields
  • Cognitive dead-ends (fields users can't answer without leaving the page)
  • Steps that create delay before the user gets any value (e.g., email verification before first use)
  • Steps that feel like commitment before trust is established

State clearly: "Your #1 estimated drop-off point is [Step X] because [reason]."


2D — Evaluate the Eight Conversion Levers

Check each lever and note the current state:

1. Field Count & Necessity How many fields total? Which are not immediately required? Flag any field that could be collected after signup via progressive profiling.

2. Social Login vs. Email Tradeoff Is social login offered? (Google/GitHub are highest-converting for SaaS.) If not, is there a reason? Social login eliminates password friction and email verification for most users. Note: some users distrust social login — offering both is usually optimal.

3. Email Verification Timing Is email verification required before the user can access the product? If yes, this is a major conversion killer. Best practice: let users access a limited version immediately, then gate features or send a "please verify to unlock X" prompt. Only block access for accounts that require absolute trust (e.g., financial, healthcare).

4. Onboarding Redirect Strategy Where does the user land immediately after signup? Options ranked best to worst:

  • "Aha moment" screen — puts them closest to first value
  • Personalization wizard — acceptable if short (3 questions max)
  • Generic dashboard — neutral, misses activation opportunity
  • Empty state with no guidance — friction multiplier
  • Another form or survey — conversion killer

5. Progressive Profiling Which fields asked at signup could be collected later (after the user has experienced value)? Company size, role, use case, and preferences are prime candidates. Segment, Intercom, and in-product prompts can collect these without blocking signup.

6. Error Message Clarity Are error messages specific and actionable? ("Password must be at least 8 characters with one number" beats "Invalid password.") Generic errors create abandonment because users don't know how to fix them.

7. Trust Signals What trust signals are present at the form? Evaluate:

  • Privacy copy ("No spam. Unsubscribe anytime." or "SOC 2 certified")
  • Social proof (customer logos, review counts, testimonials near the form)
  • Security indicators (SSL badge, "Used by 5,000+ teams")
  • Clear value prop visible while filling out the form

8. Mobile-First Field Order On mobile, fields near the top of the screen get filled first. Prioritize: email → password → (if required) one key identifier. Move anything requiring typing long text strings (company description, etc.) out of signup entirely.


Step 3 — Produce the Output Report

Structure the output exactly as follows:


📋 Current Flow Map

[The confirmed map from Step 2A]


⚡ Friction Score by Step

StepFriction LevelPrimary Issue
Step 1: [name]High / Medium / Low[One-line summary]
Step 2: [name]......

Overall flow friction: High / Medium / Low


🎯 #1 Estimated Drop-Off Point

[Step name and explanation — 2–3 sentences max]


✂️ Top 3 Immediate Cuts or Simplifications

List the three highest-impact changes, in priority order:

  1. [Change] — [Why it matters, what it removes/simplifies]
  2. [Change] — [Why it matters]
  3. [Change] — [Why it matters]

🔄 Redesigned Flow Recommendation

Present a revised flow using the same Step/Fields/Actions format:

Step 1: [Screen name — revised]
  Fields: [trimmed field list]
  Actions: [revised submit behavior]
  Trust signals: [what to add]

Step 2: ...

For each change, include a one-line rationale in parentheses.


📈 Expected Conversion Lift Estimate

Provide a directional estimate based on the changes recommended. Use ranges, not point estimates.

Example framing:

Based on the changes above — removing 3 fields, enabling social login, and delaying email verification — a directional estimate for signup completion rate improvement is 15–30%. This is based on general industry benchmarks for similar changes (e.g., each removed field ~5% lift, social login ~10–20% lift for B2B SaaS). Actual results will vary based on your traffic source, audience, and implementation. A/B test the redesign before committing fully.

Always include the caveat that estimates are directional, not guaranteed, and recommend A/B testing.


Handling Edge Cases

"We can't remove that field — sales requires it." Suggest a post-signup enrichment strategy: collect the data via Clearbit/Apollo enrichment, or trigger an in-product prompt after the user completes their first key action. Never argue with internal constraints — route around them.

"We have no social login and can't add it." Accept the constraint. Focus on reducing other friction points. Suggest passkey/magic link as a middle ground if it fits their stack.

"Our verification is required for compliance." Acknowledge the constraint. Suggest a "partial access" approach: let users view the product UI (read-only or demo data) while verification is pending, then unlock full access on confirmation. This preserves compliance while reducing abandonment.

"We already have a short form — only 3 fields." Shift focus to the post-signup experience: redirect strategy, onboarding flow quality, trust signals, and error UX. Low-field forms often have their biggest optimization opportunities downstream.

User provides a URL only with no description. Explain that you can't directly access live forms, and ask them to walk through the flow step by step, narrating each screen as they go. Offer to reconstruct it into a structured map as they describe it.


Quality Bar

Before delivering the report, check:

  • [ ] Every field in the current flow has a friction score
  • [ ] The #1 drop-off point is identified with a clear reason
  • [ ] The redesigned flow is a complete, actionable spec — not just vague advice
  • [ ] The conversion lift estimate includes a caveat and recommends A/B testing
  • [ ] No recommendation requires a tool or platform that conflicts with constraints the user has stated

The goal is a report the user can hand to an engineer or designer and say "build this." Specific beats general every time.

平台分布

OpenClaw

89.24%
按下载量换算2,522

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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