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Search Intent Agent

Maps consumer search language against a merchant catalog. Surfaces the exact keywords and natural-language questions consumers use, flags ghost products (catalog entries invisible to high-demand searches), and recommends title and landing-page rewrites that match consumer intent.

Endpoint: POST /a2a/intent-agent

Skills

Ghost Product Detection

Identifies products in the merchant catalog whose titles do not match the high-demand keywords consumers are searching for.

Example queries:

  • "Which of my products are invisible to search?"
  • "Find ghost products in my kitchenware catalog"

Keyword Landscape Mapping

Maps the full keyword landscape around a category by aggregating seed, canonical, and intent keyword types.

Example queries:

  • "Map the keyword landscape for home fitness"
  • "What are the top search terms in premium yoga?"

Voice & Natural-Language Question Mining

Surfaces natural-language questions consumers ask in voice and AI search interfaces.

Example queries:

  • "What voice-search questions are trending for kitchen knives?"
  • "Show me natural-language questions about yoga mats"

Product Title Optimization

Suggests product title changes grounded in consumer language and high-SV keyword data.

Example queries:

  • "Rewrite my product titles to match consumer language"
  • "Which titles should I update for better visibility?"

Modality Analysis (Text vs Voice/AI)

Breaks down opportunity by text search vs voice/AI search modality so merchants can invest accordingly.

Example queries:

  • "How much of my demand is voice vs text?"
  • "Which categories have more AI-search traffic?"

Input/Output

  • Input modes: text/plain
  • Output modes: application/json, text/plain