Paid Ads Optimization

SkillDev tools

Lets your agent analyze paid ad campaigns to find wasted spend and propose budget and bid optimizations.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Paid Ads Optimization skill

About this capability

Diagnose wasted paid-ad spend, pacing, and allocation, then propose safe evidence-backed optimizations. Use for waste, negatives, budgets, bid changes, poor CPA or ROAS, underpacing, overspend, or scaling decisions.

What this skill tells your AI

The instructions your AI receives, as published by nowork-studio/notfair-plugin in paid-ads/paid-ads-optimize/SKILL.md and read by ahel’s review.

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.

Signals

GitHub stars
4k
Forks
478
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
paid-ads-optimize
Source
github.com/nowork-studio/notfair-plugin