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kuudoai/kuudo-skills

22 Agent Skills for Amazon sellers and advertisers: Sponsored Products and Brands audits, search-term mining, budget pacing, DSP and Amazon Marketing Cloud, reporting, listing optimization and compliance, product images, repricing, FBA inbound, stockout, refunds, buyer messaging, and profitability. Built for Kuudo's hosted Amazon Ads and Selling Partner MCP servers; price, budget, listing, and shipment writes are previewed and wait for explicit approval.

1.65x

Quality

93%

Does it follow best practices?

Impact

66%

1.65x

Average score across 22 eval scenarios

Securityby

Medium

Suggest reviewing before use

Column mapping hints (non-authoritative)

Amazon Advertising Sponsored Brands Campaigns exports change by report type, API version, and locale. Treat this file as search ideas when scanning headers — confirm every mapping on the user’s artifact.

Semantic roles

Role	Typical ideas (examples only)	Agent action
Campaign key	`campaign`, `campaign name`, `campaignName`, `Campaign`	Prefer stable ID if both ID and name exist for joins
Cost / spend	`cost`, `spend`, `Spend`	Same currency as sales
Sales	`sales`, `attributed sales`, `purchases sales`, `14 Day Total Sales`	Pick one definition per run; document it
Impressions	`impressions`, `Impressions`
Clicks	`clicks`, `Clicks`	Exclude columns that are rates if mis-labeled
Orders	`orders`, `purchases`, `7 Day Total Orders`	Watch attribution window in header
State	`state`, `status`, `campaign status`	Normalize case when filtering enabled
Budget	`budget`, `daily budget`	Optional
NTB orders	headers containing `new to brand` + `order`, or `ntb` + `order`	Locale-specific spacing
NTB sales	`new to brand` + `sales`
Placement / type	`placement`, `top of search`, `video`, `ad type`	Only if present

Nested JSON

Exports from APIs may be { "reports": [ { "rows": [...] } ] } or different. The agent must:

Print top-level keys.
Find the list of row objects or the CSV-equivalent array.
Derive column names from the first row’s keys if records are dicts.

Common pitfalls

Multiple sales columns (1d vs 7d vs 14d): user must choose or default to the window stated in the report name.
Percent formatting: strings like "12.3%" need parsing before math.
Aggregated vs daily grain: if each row is campaign-day, aggregate to campaign for “top campaigns” unless the user wants daily charts.