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Agent Skill · 研究检索

meta-ads-analysis(元广告分析)

meta-ads-analysis 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。

meta-ads-analysis 是研究检索类 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,按安装量在研究检索类的 73,675 个 Skill 里排第 26,883。

总安装 3,491周安装 144GitHub Stars 公开资料未说明下载 1,140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
1.2.0

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-analysis(元广告分析)
来源仓库:https://github.com/elias-didoo/meta-ads-analysis
安装命令:
openclaw skills install meta-ads-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-analysis

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。

深入分析元广告活动绩效,提供指标、漏斗、趋势和异常分析。适用于需要了解营销活动效果时快速定位关键数据。meta-ads-analysis 属于研究检索类 Skill,可作为该场景下的辅助能力补充。通过关键词或任务场景检索候选结果,结合来源仓库核验具体用法。安装前确认权限范围和维护状态,注意是否触发联网或文件读写。

建议参考原始 README 检查命令执行和输出格式限制。

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-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-analysis 怎么安装?

在终端执行 openclaw skills install meta-ads-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-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-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-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-analysis 用的人多吗?

公开数据是累计安装 3,491 次,近一周安装 144 次,下载 1,140 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-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
meta-ads-analysis

元广告分析 · 本页

3,491—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-analysis
description
[Didoo AI] Analyzes Meta Ads campaign performance in depth — metrics, funnel, trends, and anomalies. Use when user wants to understand how a campaign is performing, identify weak points, or get data before receiving recommendations. Outputs structured analysis only; never provides recommendations. Triggers on: \"analyze\", \"deep dive\", \"why is performance\", \"diagnose\", \"full audit\".
homepage
https://didoo.ai/blog
metadata

Required Credentials

CredentialWhere to GetUsed ForOAuth Scope
META_ACCESS_TOKENMeta Developer Console → Graph API Explorer → Generate TokenAll Meta Marketing API callsads_read (read-only, least-privilege)
META_AD_ACCOUNT_IDAds Manager URL: adsmanager.facebook.com/act_XXXXXXXXXIdentifying which account to query—

When to Use

Loaded when user wants to understand how their Meta Ads campaign is performing — either a specific aspect (audience, creative, overall) or a full diagnostic. Can run standalone or as prerequisite for meta-ads-recommendation.


Step 0: Understand the Campaign

Before pulling any data, get context on what this campaign is trying to do. Ask 1–2 quick questions if not already clear from conversation:

  • "Is this an always-on campaign, or tied to a specific promotion?"
  • "Are you testing new things, or trying to scale what's already working?"

Keep it conversational. If META_ACCESS_TOKEN or META_AD_ACCOUNT_ID is not available, tell the user exactly what is needed and do not proceed with API calls.


Step 1: Gather Campaign Structure

Ask the user for their Meta Ads account access. Use the Meta Marketing API to fetch:

Campaign level

  • Campaign name, ID, status (is it ACTIVE?)
  • Objective (what counts as a "result" — leads, purchases, clicks?)
  • Budget type (CBO = campaign-level budget optimization, or ABO = adset-level)
  • Bid strategy, daily budget, start date

Adset level

  • Adset name, ID, status
  • Optimization goal (this determines what "results" means for this adset)
  • Targeting countries, budget, bid amount

Ad level

  • Ad name, ID, status
  • Which adset it belongs to

Store this as campaign_context. Reuse across the session — don't re-fetch.


Step 2: Confirm Time Range and Attribution Window

Always confirm the time period and attribution window before pulling performance data:

  1. Time range: "What time period would you like to analyze? (e.g., last 7 days, last 30 days, or a specific date range)"
  2. Attribution window: "What attribution window are you using? Default in Meta is 7-day click. For e-commerce, 1-day click often gives a clearer signal. For lead gen, 7-day click is usually better."
Campaign typeRecommended attribution window
E-commerce / purchase1-day click
Lead generation7-day click
App installs7-day click
Brand awareness28-day view

Convert to YYYY-MM-DD,YYYY-MM-DD format. Default granularity:

  • ≤14 days → daily
  • 15–60 days → weekly

Step 3: Route the Analysis

User is asking aboutWhat to analyze
Overall / general healthCampaign-level metrics, no breakdown
Audience / country / platform / age / genderAdset or ad level with breakdowns
Creative / which ad is betterAd-level metrics
Everything / full diagnosticAll three in sequence
Follow-up on existing dataUse data already in session — don't re-fetch

Step 4: Pull and Interpret Performance Data

Use the Meta Marketing API to fetch metrics for the relevant level and time range.

Key Metrics to Collect

At campaign or adset level:

  • Spend, impressions, frequency
  • CPM (cost per 1,000 impressions)
  • CPC (cost per link click)
  • CTR (link click rate)
  • LPV rate (landing page view rate = landing page views / link clicks)
  • Results, cost per result
  • Conversion rate (results / landing page views)

At ad level, add:

  • Individual ad performance
  • Creative elements if identifiable

What Each Metric Tells You

MetricDeclining =Growing =
CPMCheaper reachCompetition up
CPC / cost_per_resultMore efficientLess efficient
CTR / LPV rate / conversion_rateProblemHealthy
Results volumeDroppingGrowing
Frequency—Fatigue risk if > 3

Understanding "Results"

The meaning of "results" depends on the optimization goal:

  • LEAD_GENERATION → results = leads
  • LINK_CLICKS → results = link clicks
  • LANDING_PAGE_VIEWS → results = landing page views
  • PURCHASE / CONVERSIONS → results = purchases

Always clarify what "results" means when discussing cost_per_result.

Campaign Structure Matters

  • CBO (campaign-level budget): Evaluate at campaign level first
  • ABO (adset-level budget): Evaluate at adset level
  • Multiple ads in one adset: Evaluate at adset level, not individual ads
  • Active but less than 7 days old + less than 50 results since last significant edit: Treat as still in learning phase — data is unstable
  • Breakdown Effect: Meta optimizes for marginal CPA (cost of the next result), not average CPA. A segment showing higher average CPA may be protecting overall campaign efficiency. Do not judge system decisions by average CPA in breakdown reports alone.

Step 4b: Lead Generation Campaigns

Use meta-ads-lead-gen-analysis instead — it has dedicated LPV benchmarks for lead gen, form friction analysis, CAPI verification, and lead quality diagnosis.

Step 4c: Landing Page Diagnostic

This section has moved to meta-ads-recommendation → Step 4. Landing page diagnosis is now part of the recommendation workflow for better action alignment.

Step 5: Check Ad Relevance Diagnostics

When an ad's cost_per_result is elevated and basic metrics (CTR, LPV rate) don't fully explain it, check the Ad Relevance Diagnostics in Meta Ads Manager.

DiagnosticWhat it measuresLow ranking suggests
Quality RankingPerceived ad quality vs. competitorsImprove creative
Engagement Rate RankingExpected engagement vs. competitorsTest new angles, improve hook
Conversion Rate RankingExpected conversion vs. competitors with same optimization goalCheck landing page or audience-offer fit

Usage rules:

  • Requires 500+ impressions to be available — below that, diagnostics are not meaningful
  • These are diagnostic tools only, not auction inputs
  • When all three rankings are low simultaneously → strong audience-creative mismatch

Step 6: Assess for Problems

Flag these when you see them:

  • Frequency > 3 → Audience fatigue risk
  • CTR less than 1% → Weak creative hook or audience mismatch
  • LPV rate less than 70% → Ad-to-landing-page disconnect
  • cost_per_result rising → Efficiency problem
  • Status is not ACTIVE → Explain impact
  • Learning / Learning Limited → Warn: data not yet stable
  • Spend less than 50% of budget → Delivery problem — audience may be too narrow or bid too low
  • One segment vastly outperforming others → System is correctly finding winners

Step 7: Structure Your Output

  • Campaign Context: one sentence covering objective, budget type, and status.
  • Summary: Spend, impressions, results, cost per result, CTR, CPM.
  • Funnel: Impressions → Link Clicks → Landing Page Views → Results, with rates at each stage.
  • Trend Analysis: Key metrics with direction and what it means for the business.
  • Key Issues: Specific problems and why they matter.
  • Data Notes: Any caveats — learning phase, insufficient data, zero-spend entities excluded.

Tone and Language

  • Match the language the user speaks (English or Chinese)
  • Speak as a professional growth partner — translate numbers into business insights
  • Every judgment must cite specific data. Never say "performance is bad" without a number
  • When data is insufficient, say so: "2 days isn't enough for reliable trends — let's revisit in a week"

Restrictions

  • Analysis only — never output recommendations in this skill
  • Do not recalculate metrics already computed by Meta (CTR, CPM, CPC are already calculated)
  • Never conclude an ad or adset is "underperforming" based on CPA alone without comparing to its own historical baseline and the account average

Session Context — What This Skill Writes

After completing analysis, store the following in session context:

KeyDescriptionExample
funnel_weak_pointsWhere the biggest funnel drop-off occurs"LPV rate 58%, well below 70% benchmark"
trend_signalsDirection of key metrics"CPM up 18% WoW; CTR down 0.4pp"
anomaliesAnything unusual or unexpected"Frequency 4.2 with CPL still at target"
data_qualityWhether there's enough data to act"Only 2 days — too early to judge"
lp_diagnosis_generalIs the problem ad-side or landing page-side?"Ad side — CTR declining, frequency stable"
Routing: If the campaign is Lead Gen, route to meta-ads-lead-gen-analysis and preserve these keys. meta-ads-recommendation reads these keys to produce the action plan.

平台分布

OpenClaw

80.71%
按下载量换算920

安全审计

VirusTotal

未展示

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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