Query Mapping

Analyzes how search engines and AI systems answer specific queries. Maps SERP features, content formats, and citation patterns so you can build pages that win placement.

Quick Start

Map the SERP for [query]

Why is [URL] ranking for [keyword]?

What content format should I use to win [query]?

Engine Contract

• Reads: target queries, current URL if optimizing, competitive landscape
• Writes: SERP feature map, content format recommendation, and optimization checklist
• Promotes: winning formats, schema opportunities, and AI citation patterns to hot cache
• Next handoff: signal packet with format recommendations and content specs

Instructions

Run four phases:

1. Deconstruct — identify all SERP features: organic results, featured snippets, People Also Ask, videos, images, knowledge panels, local pack, shopping, AI overview
2. Format — for each feature, note the winning content format (list, table, paragraph, video, comparison, how-to)
3. Source — analyze which domains are cited in AI overviews or featured snippets and what structural patterns they use
4. Blueprint — recommend exact structure, schema type, and content format to compete for each feature

Example

User: "Map query 'best project management software for startups'"

Output:

• Featured snippet: comparison table (Capterra, G2)
• People Also Ask: 4 questions, list and paragraph formats dominate
• AI overview: cites 3 comparison posts with structured pros/cons lists
• Recommendation: Build a comparison table with 6 tools, add FAQ schema, include pros/cons micro-sections

Deliverables

• SERP feature inventory
• Winning format analysis
• AI citation source list
• Content blueprint per feature

Next Best Engine

• Primary: content-engine — build the winning format
• Alternatives: ai-citation-optimizer, snippet-crafter