Analyze Topic Demand

Workflow contract for topic demand across SEO keywords, Google Trends, AI answers, and conversations.

Overview

Workflow endpoints run their primitives in parallel and return each primitive's full output, labeled per source. Pricing is calculated from the primitives that ran successfully plus the selected model rates: failed or skipped steps are not charged.

Reference

POST/v1/workflows/topic-demand

$0.49 · flat per call

Parameters

`topic`required	string	Topic, keyword, category, or audience demand to analyze.
`country`optional	string	ISO-2 country code for localized SEO keyword data. Default: `"us"`.
`timeframe`optional	string	Trend window for demand checks. Default: `"past_12_months"`.
`models`optional	array of enum (chatgpt \| claude \| perplexity \| gemini \| google_ai_overview)	Optional model subset. Omit to query the default surfaces (chatgpt, perplexity, gemini). Pass ["perplexity"] or ["perplexity","claude"] when the user names specific surfaces or wants to reduce cost. The full set is chatgpt, claude, perplexity, gemini, google_ai_overview — to query all of them, set fullSweep instead of listing them.
`fullSweep`optional	boolean	Query all five AI surfaces instead of the three default ones, adding claude and google_ai_overview. Costs more per call. Use it when the user wants complete cross-model coverage, is comparing surfaces against each other, or asks specifically about Claude or Google AI Overviews. Ignored when models is given.

Request

curl https://www.cite42.dev/api/v1/workflows/topic-demand \
  -X POST \
  -H "Authorization: Bearer $CITE42_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"topic":"generative engine optimization","timeframe":"past_12_months"}'

Response

{
  "status": "workflow_result",
  "workflow": "analyze_topic_demand",
  "summary": "Measure demand across search, trends, AI answers, and audience conversations.",
  "input": {
    "topic": "generative engine optimization",
    "timeframe": "past_12_months"
  },
  "results": [
    {
      "endpoint": "/v1/trends",
      "tool": "cite42_trends",
      "why": "Check interest over time and rising queries.",
      "data": {
        "term": "generative engine optimization",
        "trend": "rising",
        "interestOverTime": [
          {
            "date": "2026-07-13",
            "value": 72
          }
        ],
        "risingQueries": [
          "geo vs seo",
          "geo agency"
        ],
        "topQueries": [
          "what is geo"
        ]
      },
      "ok": true
    }
  ],
  "suggestedPrompt": "Summarize demand and recommend the strongest topic angle."
}