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Agent Skill · 效率

meta-ads-lead-gen-analysis(元广告潜在客户发掘分析)

meta-ads-lead-gen-analysis 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

meta-ads-lead-gen-analysis 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 15,151。

总安装 3,189周安装 137GitHub Stars 公开资料未说明下载 1,118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
1.1.0

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:meta-ads-lead-gen-analysis(元广告潜在客户发掘分析)
来源仓库:https://github.com/elias-didoo/meta-ads-lead-gen-analysis
安装命令:
openclaw skills install meta-ads-lead-gen-analysis
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 meta-ads-lead-gen-analysis

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

专门用于元潜在客户开发活动的深度分析报告模块。当 CPL 升高或导联质量模糊不清时启用诊断。聚焦线索来源、表单设计与落地页转化瓶颈分析。meta-ads-lead-gen-analysis 属于效率类 Skill,可作为该场景下的辅助能力补充。要求具备访问 Lead Ads 详细日志的权限。

建议配合原始案例理解典型问题与优化方向对应关系。

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 meta-ads-lead-gen-analysis;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

meta-ads-lead-gen-analysis 怎么安装?

在终端执行 openclaw skills install meta-ads-lead-gen-analysis。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

meta-ads-lead-gen-analysis 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。

meta-ads-lead-gen-analysis 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。

meta-ads-lead-gen-analysis 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。

meta-ads-lead-gen-analysis 用的人多吗?

公开数据是累计安装 3,189 次,近一周安装 137 次,下载 1,118 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。

meta-ads-lead-gen-analysis 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。

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。
  • 需要处理效率类任务、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。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
meta-ads-lead-gen-analysis

元广告潜在客户发掘分析 · 本页

3,189—需要联网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
meta-ads-lead-gen-analysis
description
[Didoo AI] Specialized analysis module for Meta lead generation campaigns. Use when CPL is elevated, lead quality is unclear, or you need to diagnose why leads aren't converting downstream. For general campaign analysis, use meta-ads-analysis.
homepage
https://didoo.ai/blog
metadata

Required Credentials

CredentialWhere to GetUsed ForOAuth Scope
META_ACCESS_TOKENMeta Developer Console → Graph API Explorer → Generate TokenFetching campaign and form integration dataads_read (read-only)
META_AD_ACCOUNT_IDAds Manager URL: adsmanager.facebook.com/act_XXXXXXXXXIdentifying which account to query—

When to Use

When running lead generation campaigns and standard e-commerce analysis logic doesn't apply. Specifically for:

  • CPL is higher than expected or target
  • Lead volume is healthy but conversion rate to closed deals is low (quality problem)
  • LPV rate looks fine but form submit rate is unknown
  • CAPI may not be sending offline lead data back to Meta
  • Not sure if the problem is the ad, the audience, or the form itself

Lead gen has fundamentally different metrics than e-commerce — standard CVR and LPV benchmarks don't apply. Use this skill instead of applying e-commerce logic to lead gen campaigns.


Key Differences from E-commerce Analysis

MetricE-commerce BenchmarkLead Gen BenchmarkWhy It Differs
LPV Rate> 70% is healthy> 50% is healthyMany leads browse without intent to submit
Form Submit RateN/A> 20% is healthyForm friction is the primary drop-off point
CPLVaries by industryThe primary metricWhat you're actually paying for
CVR (post-click)Purchase rateLead-to-qualified rateMeta can't see what happens after form submit
Attribution1-day or 7-day click7-day click usuallyLonger window for consideration

Step 1: Gather Lead Gen Specific Data

Pull these metrics at the campaign and adset level:

  • Spend, impressions, CTR
  • LPV Rate (Landing Page View rate = landing page views / link clicks)
  • Form Submit Rate (if available — requires CAPI or form integration)
  • CPL (cost per lead)
  • Frequency
  • Lead volume vs. prior period

Also ask the user:

  • What does a "good lead" look like for their business?
  • What's their lead-to-close rate historically?
  • Are they using CAPI to send offline lead data back to Meta?

Step 2: CAPI Verification — Critical for Lead Gen

Without CAPI sending offline lead data back to Meta:

  • Meta is optimizing for form submissions, not qualified leads
  • CPL shown may be "form submit cost" not "actual lead cost"
  • The algorithm can't learn which leads actually convert

How to verify CAPI is connected:

  1. Go to Meta Events Manager → select your pixel
  2. Check "About CAPI" — status should be green/active
  3. Ask: are offline leads (calls, CRM-qualified leads) being sent back via CAPI?

If CAPI is NOT connected for offline leads:

  • This is a priority fix — it will lower CPL over 2–3 weeks
  • Recommend a CRM integration or Zapier/Make workflow
  • Or use Meta's Lead Forms (form submission = conversion automatically tracked)

Step 3: Audience Targeting Analysis for Lead Gen

Cold Audiences (Interest-Based Targeting)

  • Interest targeting works for cold audiences
  • Frequency builds fast — limit budget to avoid rapid fatigue
  • Test narrower interest layers (2–3 stacked interests, not broad categories)

Custom Audiences (Retargeting and Lookalikes)

  • Website visitors (pixel): typically highest conversion rate
  • Email lists (matched audiences): strong for existing customer re-engagement
  • Lookalikes (LAL): based on converter audiences, quality depends on seed list quality
  • Test LAL layers 1–3% first — wider LAL = lower quality but more volume

Step 4: Format Output

Lead Gen Health Summary:

  • Spend / CPL / Lead Volume
  • LPV Rate vs. benchmark (> 50% healthy for lead gen)
  • Form Submit Rate (if available)
  • CAPI Status (connected / not connected)

SECTION 1: CAPI Gap (if applicable)

State whether offline lead data is being sent to Meta. Impact: algorithm is optimizing for quantity, not quality.

SECTION 2: Audience Diagnosis

Diagnose targeting based on frequency and CPL — is the audience too broad or well-matched?

SECTION 3: Funnel Stage

Identify the CPL bottleneck stage:

  • LPV < 50% → Ad-to-Form disconnect
  • LPV ≥ 50% but low leads → Form friction (check form fields)
  • LPV and CVR OK but CPL high → Audience mismatch or CAPI not connected
LP Landing Page diagnosis: The full LP disconnect diagnostic (Step 4a–4d) lives in meta-ads-recommendation → Step 4. This skill identifies the funnel stage; recommendation prescribes the fix.

Session Context — What This Skill Writes

After completing analysis, store the following in session context:

KeyDescriptionExample
lp_diagnosisFunnel stage causing the CPL problem"Form friction — submit rate 12%, below 20% benchmark"
capi_statusWhether offline leads are being sent to Meta"Not connected — offline lead data not flowing"
cpl_breakdownWhich stage is the bottleneck"LPV 65% OK; Form submit 11% is the bottleneck"
recommended_fix_priorityRanked fix order"1. CAPI 2. Form fields 3. Audience"
meta-ads-recommendation reads these keys to produce the lead gen action plan.

Key Collision Resolution

⚠️ Key priority: meta-ads-analysis writes lp_diagnosis_general; this skill writes lp_diagnosis (the lead-gen-specific version). meta-ads-recommendation is configured to prefer lp_diagnosis when available — so running both skills in sequence does NOT cause overwriting. The two keys coexist.

Rules

  • Apply lead gen benchmarks, not e-commerce benchmarks
  • Always verify CAPI status before diagnosing CPL issues — missing CAPI is the most common cause of misleading CPL data
  • Do not recommend creative changes if form friction is the bottleneck
  • Do not recommend audience changes if LPV rate indicates a page problem
  • This is analysis only — recommendations route to meta-ads-recommendation

平台分布

OpenClaw

89.43%
按下载量换算1,000

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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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