Canonical NotFair workflow
Quick answer
- 01What is it?
- 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. The value is a focused slice of paid media judgment, useful when several similar skills cover the same ground.
- 02Inputs
- Context for paid media: your goals, audience, constraints, and any source material the skill asks for.
- 03Output
- A ready-to-use result for paid media: the analysis, copy, or recommendations the agent produces.
Add this skill
Install as a package
Installs this one skill package for your coding agent, including any supporting files that skill ships with — not every skill in the repository. Read the tutorial.
$ npx skills add nowork-studio/notfair-plugin --skill paid-ads-optimizeSkill instructions
The instruction file for this skill. The skill also includes other files you need to install to use it.
Canonical NotFair workflow
Read ../../paid-ads/paid-ads-optimize/SKILL.md completely, then follow it as the active workflow. Resolve every relative reference from that file against ../../paid-ads/paid-ads-optimize/.
Supporting file: paid-ads/paid-ads-optimize/SKILL.md
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.
Common questions
How do I install Canonical NotFair workflow in Cursor, Claude Code, or Codex?
Run npx skills add nowork-studio/notfair-plugin --skill paid-ads-optimize in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only Canonical NotFair workflow, not every skill in the repository.
Where does Canonical NotFair workflow come from and what license is it under?
Canonical NotFair workflow comes from the nowork-studio/notfair-plugin repository on GitHub. That repository has 3.4K GitHub stars. The skill is published under the MIT license.
Prefer plain text? Read the Canonical NotFair workflow guide as markdown.
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