Canonical NotFair workflow
Quick answer
- 01What is it?
- Plan and review Amazon Ads with margin-aware ACoS, product, and search-term guardrails. Use for Amazon advertising, Sponsored Products, Sponsored Brands, Sponsored Display, ASIN targeting, Amazon ACoS, or Amazon Ads. It stands out by giving paid media a defined shape, so the agent asks for better context and returns a more usable result.
- 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-amazonSkill 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-amazon/SKILL.md completely, then follow it as the active workflow. Resolve every relative reference from that file against ../../paid-ads/paid-ads-amazon/.
Supporting file: paid-ads/paid-ads-amazon/SKILL.md
Amazon Ads Planning
Read ../shared/operating-contract.md and ../shared/measurement-framework.md. This plugin does not declare a first-party NotFair Amazon Ads MCP mutation surface; use a verified connector or supplied report and deliver a reviewable operator brief.
Start with unit economics
Record the product/ASIN, marketplace, currency, contribution margin, price, inventory constraint, and target ACoS. ACoS is spend divided by attributed ad revenue; it is only good or bad relative to margin and the user's strategic goal. Separate the advertised product from any measured cross-sell before judging performance.
Propose the narrowest learning plan: product scope, campaign intent, automatic discovery or manual term/ASIN hypothesis, budget, negative/exclusion rule, and review window. Treat search-term findings as evidence for targeted negatives or promotion into controlled targeting, not as a reason to remove broad discovery prematurely.
Review and handoff
Report spend, attributed sales, ACoS, ROAS if useful, orders, conversion rate, search-term quality, and inventory risk for a complete comparable window. State reporting lag and attribution source. Mark changes ready_for_review until a verified connector or authorized Amazon Ads operator confirms the exact result.
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-amazon 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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