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Ads competitor

Skill AgriciDaniel/claude-ads/skills/ads-competitor

Research competitor paid-ad presence, messaging, creative, formats, landing pages, keyword and auction signals, transparent ad libraries, and strategic gaps across supported platforms. Use for competitor ads, ad libraries, ad spy, competitive PPC analysis, competitor creative, Google Ads Transparency, Meta Ad Library, or paid-media competitor research.From its SKILL.md

Install
npx -y skills add AgriciDaniel/claude-ads --skill ads-competitor

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

1.2 KB, 165 tokens by cl100k_base, as published. Nobody here has run it

Competitor Ad Intelligence

  1. Confirm named competitors, market, geography, customer, objective, and decision.
  2. Use official transparency libraries, public ads, auction data supplied by the operator, and other terms-compliant sources.
  3. Record capture date, platform, placement, observable creative/message, landing destination, and source URL.
  4. Separate direct observations from inferred audience, spend, performance, or strategy; never present estimates as account facts.
  5. Cluster durable themes, formats, offers, funnel paths, and gaps without copying protected creative or text.
  6. Return evidence-backed opportunities, risks, experiments, and source records.

Respect platform terms, robots and access controls, copyright, trademarks, and privacy. Do not bypass authentication or scrape private account surfaces.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most research analysis skills give in 165 tokens

Counted across 1,213 of the 2,113 authors here whose files we hold, read 2026-09-06

  • Cite sources for every important claimin 47 of 1213, across 38 files
  • Separate facts from inferences and recommendationsin 21 of 1213, across 12 files
  • Write findings to a markdown filein 19 of 1213
  • Label every insight with a confidence levelin 18 of 1213, across 8 files
  • Read product marketing context before asking questionsin 18 of 1213, across 8 files
  • Rank themes by frequency and intensityin 16 of 1213, across 6 files
  • Establish research mode before proceedingin 16 of 1213, across 6 files
  • Segment survey responses by customer tier or tenurein 16 of 1213, across 6 files
  • Categorize support tickets before analyzingin 16 of 1213, across 6 files
  • Weight research sources from the last twelve monthsin 16 of 1213, across 6 files
  • Use at least five data points per segmentin 15 of 1213, across 5 files
  • Extract verbatim quotes for all research findingsin 15 of 1213, across 5 files

Said here and by no other author read

  • Confirm competitors and market objectives
  • Use official transparency libraries and public data
  • Record capture date and platform details
  • Separate direct observations from inferred strategy
  • Cluster durable themes and funnel paths
  • Return evidence-backed opportunities and risks

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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