Paid ads review

Produce a read-only, evidence-based paid-media performance review across connected platforms or supplied exports.

How to use it

Claude Code

Run the line below. It pulls the whole folder into ~/.claude/skills/paid-ads-review.
Describe your job in plain words. Claude Code follows the skill from there.

Claude Code — installs the whole folder, not just SKILL.md

npx degit nowork-studio/notfair-plugin/paid-ads/paid-ads-review#main ~/.claude/skills/paid-ads-review

For one project only, change the path to .claude/skills/paid-ads-review.

Claude (web or desktop app)

On this page open ⋯ → Download .md.
Save it as SKILL.md in a folder, zip the folder, then Customize → Skills → + → Create skill → Upload a skill.
Pick the file and Save. Claude shows the name and description and runs a security scan.
Check the skill is switched on.
Start a new chat and describe your job in plain words. The AI follows the skill from there.

ChatGPT or another app

ChatGPT: make a Project and paste it into Instructions.
Neither? Paste it at the top of a new chat — it works for that chat.

Not working?

Check which app you pasted it into — the steps above name the right one.
Some skills need the paid tier of Claude or ChatGPT.

Step-by-step guide with screenshots · Ask in the forum

Paste into Claude, ChatGPT or Cursor.

Show the full text24 lines

paid-ads-review/SKILL.md24 lines · 2.0 KB

PreviewCode

Outline

RawView on GitHub

name	description	argument-hint
paid-ads-review	Produce a read-only, evidence-based paid-media performance review across connected platforms or supplied exports. Use for weekly or monthly reports, scorecards, performance, CPA, ROAS, CTR, spend trends, pacing, or conversion-tracking health.	<date range, platform, or 'weekly review'>

Paid Ads Review

Read ../shared/operating-contract.md and ../shared/measurement-framework.md. This is read-only.

Assemble comparable evidence

Check which sources are actually connected, request the missing export rather than reporting a failed call, and use the most recent complete equivalent window. For every source, keep currency, conversion definition, attribution window, and reporting lag visible. Verify tracking before treating CPA, ROAS, or revenue as a decision-grade metric.

For live platform accounts, hand data collection and diagnostics to /notfair:google-ads, /notfair:meta-ads, /notfair:paid-ads-x, /notfair:paid-ads-linkedin, /notfair:paid-ads-reddit, or /notfair:paid-ads-tiktok. Keep Amazon and ChatGPT Ads review grounded in a verified connector or supplied platform export.

Report the decision, not a dashboard transcription

Lead with the strongest contributor, the largest risk, and one recommended next action. Include a platform scorecard with spend, qualified conversions, CPA, attributable revenue/ROAS where available, link CTR, and pace against the declared budget. Compare each row to the preceding equivalent period and name the likely driver only when data supports it.

Do not present an unqualified blended CPA or ROAS. If a cross-channel aggregate is useful, label the consistent conversion definition, attribution source, spend-weighted formula, and included channels. Separate confirmed facts from inference and mark absent tracking or data as a blocking limitation.

End with hold, investigate, or one proposed action; route mutations to /notfair:paid-ads-optimize or the relevant platform operator skill.

1	---
2	name: paid-ads-review
3	description: Produce a read-only, evidence-based paid-media performance review across connected platforms or supplied exports. Use for weekly or monthly reports, scorecards, performance, CPA, ROAS, CTR, spend trends, pacing, or conversion-tracking health.
4	argument-hint: "<date range, platform, or 'weekly review'>"
5	---
6
7	# Paid Ads Review
8
9	Read `../shared/operating-contract.md` and `../shared/measurement-framework.md`. This is read-only.
10
11	## Assemble comparable evidence
12
13	Check which sources are actually connected, request the missing export rather than reporting a failed call, and use the most recent complete equivalent window. For every source, keep currency, conversion definition, attribution window, and reporting lag visible. Verify tracking before treating CPA, ROAS, or revenue as a decision-grade metric.
14
15	For live platform accounts, hand data collection and diagnostics to `/notfair:google-ads`, `/notfair:meta-ads`, `/notfair:paid-ads-x`, `/notfair:paid-ads-linkedin`, `/notfair:paid-ads-reddit`, or `/notfair:paid-ads-tiktok`. Keep Amazon and ChatGPT Ads review grounded in a verified connector or supplied platform export.
16
17	## Report the decision, not a dashboard transcription
18
19	Lead with the strongest contributor, the largest risk, and one recommended next action. Include a platform scorecard with spend, qualified conversions, CPA, attributable revenue/ROAS where available, link CTR, and pace against the declared budget. Compare each row to the preceding equivalent period and name the likely driver only when data supports it.
20
21	Do not present an unqualified blended CPA or ROAS. If a cross-channel aggregate is useful, label the consistent conversion definition, attribution source, spend-weighted formula, and included channels. Separate confirmed facts from inference and mark absent tracking or data as a blocking limitation.
22
23	End with `hold`, `investigate`, or one proposed action; route mutations to `/notfair:paid-ads-optimize` or the relevant platform operator skill.
24

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