---
name: Paid Ads Optimization
slug: paid-ads-optimization
category: Automation
description: Paid Ads Optimization diagnoses wasted paid-ad spend, pacing, and allocation, then proposes safe evidence-backed optimizations. Use it to investigate waste, negatives, budgets, bid changes, poor CPA/ROAS, underpacing, overspending, or scaling decisions.
github: "https://github.com/nowork-studio/notfair-plugin/tree/main/paid-ads/paid-ads-optimize"
language: TypeScript
stars: 3365
forks: 420
install: "npx degit https://github.com/nowork-studio/notfair-plugin/tree/main/paid-ads/paid-ads-optimize ~/.claude/skills/paid-ads-optimize"
installs_to: ~/.claude/skills/paid-ads-optimize
source_path: paid-ads/paid-ads-optimize/SKILL.md
collection_size: 25
category_size: 1523
collection_url: "https://dirskills.com/collections/nowork-studio/notfair-plugin"
added: 2026-08-17T07:08:19.840Z
last_synced: 2026-08-17T07:08:19.840Z
canonical_url: "https://dirskills.com/skills/paid-ads-optimization"
---

# Paid Ads Optimization

Paid Ads Optimization diagnoses wasted paid-ad spend, pacing, and allocation, then proposes safe evidence-backed optimizations. Use it to investigate waste, negatives, budgets, bid changes, poor CPA/ROAS, underpacing, overspending, or scaling decisions.

**Install:**

```bash
npx degit https://github.com/nowork-studio/notfair-plugin/tree/main/paid-ads/paid-ads-optimize ~/.claude/skills/paid-ads-optimize
```

## README

# Paid Ads Optimization

Read `../shared/operating-contract.md` and `../shared/measurement-framework.md`. Review before changing anything.

## Diagnose before cutting

Verify the conversion signal, period completeness, spend volume, attribution model, and recent account changes. Spend with no recorded conversion can indicate broken tracking or immature data; treat it as a hypothesis until the signal and volume support an intervention. Check landing-page or operational failures before blaming targeting.

Classify the bottleneck as query/audience quality, creative fatigue, delivery/rank, budget constraint, landing-page mismatch, tracking, or economics. Use the specialized Google, Meta, X, or LinkedIn skill for live diagnosis. For other platforms, analyze only the supplied or verified data.

## Rank reversible moves

Prefer this order: exclude an irrelevant query, placement, or audience; pause the narrowest losing unit; adjust budget or bid in a measured step; then consider structural change. For a reallocation, show the current and proposed allocations, the same total budget unless the user approves an increase, and the observable hypothesis.

Do not declare a loser from a few clicks. Set a threshold appropriate to the named target CPA, conversion lag, and channel role. Preserve upper-funnel and assisted-conversion context rather than judging all campaigns on last-click CPA alone.

## Approval and follow-up

Present each exact mutation with scope, current value, proposed value, currency exposure, rationale, and review date. After approval, execute only through the verified platform skill or connector, read back the result, and record the intervention's expected effect and guardrail. Revisit after the declared observation window instead of promising a generic ongoing watch.