# Paid Ads Amazon

> 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 performance exports.

- **Type:** Skill
- **Install:** `agentstack add skill-nowork-studio-notfair-plugin-paid-ads-amazon`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [nowork-studio](https://agentstack.voostack.com/s/nowork-studio)
- **Installs:** 0
- **Category:** [Search](https://agentstack.voostack.com/c/search)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [nowork-studio](https://github.com/nowork-studio)
- **Source:** https://github.com/nowork-studio/notfair-plugin/tree/main/paid-ads/paid-ads-amazon
- **Website:** https://notfair.co/

## Install

```sh
agentstack add skill-nowork-studio-notfair-plugin-paid-ads-amazon
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [nowork-studio](https://github.com/nowork-studio)
- **Source:** [nowork-studio/notfair-plugin](https://github.com/nowork-studio/notfair-plugin)
- **License:** MIT
- **Homepage:** https://notfair.co/

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-nowork-studio-notfair-plugin-paid-ads-amazon
- Seller: https://agentstack.voostack.com/s/nowork-studio
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.