AI导哈

测试与安全

ad-negative-keywords

mbfinotti/adver…g-skills

Build and maintain negative keyword lists from search term reports to cut wasted ad spend in paid search - n-gram query mining to surface irrelevant search terms, the right negative match types and exclusion levels (account, shared list, campaign, ad group), and a review cadence that avoids overblocking queries that convert. Use whenever the user mentions a search term or search query report, irrelevant clicks, junk traffic, wasted ad spend, or wants to exclude or block keywords - even if they never say 'negative keywords'. Covers B2B lead gen and B2C/e-commerce; needs the account's query data. Do NOT use for account-wide underperformance with no query-level evidence - use mbfinotti/advertising-skills@ad-account-diagnostic instead.

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安装命令

npx skills add https://github.com/mbfinotti/advertising-skills --skill ad-negative-keywords

SKILL.md

Negative Keywords

Build and maintain a negative keyword list from search term reports, so paid-search budget stops leaking to irrelevant queries - without blocking the queries that convert.

The mechanics - match types, exclusion levels, thresholds, cadence - are identical for B2B lead gen and B2C/e-commerce. Two things differ by segment:

  • Which junk categories dominate (see taxonomy).
  • The decision data: B2B's sparse conversions force click/cost gates, B2C volume allows conversion-based gates.

Evidence gate

  • Never propose specific negative keywords for a live account without its search term report (also called search query report).
  • Missing report → request an export, explain the overblocking review below, and name zero candidate negatives in the meantime.
  • Exception: a brand-new campaign with no history may get a starter exclusion list - label it "pre-launch starter, review against real queries after 7-14 days".

A list invented from imagination has no evidence of what actually matches, and its cost, blocked converting queries, stays invisible.

Clarifying questions

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