Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my
1---2name: ad-campaign-analyzer3description: Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger…4---56# skills/ad-campaign-analyzer/SKILL.md
A
SKILL.mdAgent skill
Transport
File
Status
Listed
SKILL.md
Install
The skill file stays in the publisher's repository.
Paste the copied command in a terminal. It installs this SKILL.md into that agent.
shterminal
1npx skills add github/awesome-copilot --skill ad-campaign-analyzer -a cursor -y
Paste the copied command in a terminal. It installs this SKILL.md into that agent.
Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.
Download skills/ad-campaign-analyzer/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does ad-campaign-analyzer live?
The publisher keeps it at https://github.com/github/awesome-copilot.
Which agents can use ad-campaign-analyzer?
Claude, Cursor, Codex, and Grok Build can read a SKILL.md you add from the publisher's repository. Grok Bot installs it when you send the skill's GitHub folder link in a chat.
From the publisher
SKILL.md
name
ad-campaign-analyzer
description
Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.
license
MIT
compatibility
Cross-platform. Pure reasoning skill over user-provided campaign exports (CSV, paste, or screenshot from Google, Meta, or LinkedIn) — no external tools, network calls, or API keys.
Take raw campaign performance data and turn it into clear decisions. This skill doesn't just summarize metrics — it diagnoses problems, identifies winners, checks statistical significance, and tells you exactly what to cut, scale, and test next. Then it goes further: it compares channels on equal terms, finds where you're over-spending vs under-spending relative to results, and produces a concrete budget reallocation plan.
Core principle: Most startup founders check their ad dashboard, see a ROAS number, and either panic or celebrate. This skill gives you the nuanced analysis a paid media specialist would: what's actually significant, what's noise, and where your next dollar should go. It also solves the allocation problem — most startups either spread budget too thin across channels (no channel gets enough to learn) or dump everything into one channel (missing cheaper opportunities elsewhere).
When to Use
"Analyze my Google Ads performance"
"Which ads should I kill?"
"Is this campaign working?"
"Where am I wasting ad spend?"
"Optimize my Meta Ads"
"How should I split my ad budget?"
"Should I spend more on Google or Meta?"
"Reallocate my ad spend across channels"
"Where am I getting the best return?"
"I have $X/month for ads — how should I distribute it?"
Phase 0: Intake
Campaign data — One of:
CSV export from Google Ads / Meta Ads Manager / LinkedIn Campaign Manager
Pasted performance table
Screenshots of dashboard (we'll extract the data)
Platform(s) — Google / Meta / LinkedIn / All
Time period — What date range does this cover?
Monthly budget — Total ad spend in this period
Primary goal — What conversion are you optimizing for? (Demos / Trials / Purchases / Leads)
Target metrics — Do you have target CPA or ROAS? (If not, we'll benchmark)
Any known changes? — Did you change creative, budget, or targeting during this period?
Channels currently running — Google Ads, Meta Ads, LinkedIn Ads, Twitter/X Ads, TikTok Ads, other
Funnel data (if available):
Lead → MQL rate
MQL → SQL rate
SQL → Close rate
Average deal size
Channels you're considering but haven't tried — Want to test new channels?
Constraints — Minimum spend on any channel? Platform you must stay on?
Phase 1: Data Ingestion & Normalization
Accepted Data Formats
Source
Key Columns Expected
Google Ads
Campaign, Ad Group, Keyword, Impressions, Clicks, CTR, CPC, Conversions, Conv Rate, Cost, Conv Value
Meta Ads
Campaign, Ad Set, Ad, Impressions, Reach, Clicks, CTR, CPC, Conversions, Cost Per Result, Amount Spent, ROAS
