Response Fields

This page explains the data returned by the LLM Scraper. Each field is briefly described, with an example where relevant, so teams can quickly understand and integrate the response.

Response Fields

Top-Level Fields

Field	Description	Example
traceID	Unique identifier for the request. Used for debugging, support, and internal tracking.	"traceID": "121da7f7-c8c8-42bc-980e-a1f0a07961e8"
timestamp	ISO-8601 timestamp indicating when the request was processed.	"timestamp": "2026-04-13T14:16:13.543Z"
request_duration	End-to-end request duration in seconds (from request received to response returned).	"request_duration": 18.56
process_duration	Total internal processing time in seconds. This includes the full request lifecycle.	"process_duration": 18.56
scraper	Scraper name by LLM Engine	"scraper": "Gemini"

Note request_duration is included within process_duration. For example, if request_duration is 18.56 and process_duration is 18.56, the overall time experienced by the client is 18.56 seconds.

---

Response Object

The main parsed output from the LLM.

---

prompt

The original prompt sent to the LLM for this request. This field is always returned as part of the response for traceability and debugging.

Example

"prompt": "what are the leading SEO tips in 2026"

---

text_markdown

Markdown-formatted version of the response, preserving structure such as headings, lists, emphasis, and inline citations.

This field represents the primary readable output of the LLM, including formatting and citation markers as returned by the model.

---

Example

"text_markdown": "In 2026, SEO has shifted from \"ranking for keywords\" to \"optimizing for visibility across the AI ecosystem.\"\n\n### 1. Generative Engine Optimization (GEO)\n* **Answer-First Formatting:** Lead your articles with a concise, 2-3 sentence direct answer.\n* **Modular Content:** Use clear headings, bulleted lists, and tables.\n* **Schema Markup Everything:** Use FAQ, HowTo, and Product schema to help AI understand your data."

---

text (plain text)

Plain-text version of the response with formatting removed. Useful for storage, indexing, or systems that don't support Markdown.

Example

"text": "In 2026, SEO has shifted from ranking for keywords to optimizing for visibility across the AI ecosystem. With Google's AI Overviews and search assistants like ChatGPT and Claude siphoning up to 60% of clicks for informational queries, the strategy is no longer just about being #1—it's about being the cited source."

---

citations_found

Boolean indicating whether the model output included citations.

Example

"citations_found": true

---

citations

Flat list of citation objects extracted from Gemini.

Each citation includes:

• id

• title

• url

• description

• section: "citations" or "more"

Example

"citations": [
  {
    "id": 1,
    "url": "https://www.mandr-group.com/the-future-of-seo-how-ai-is-changing-content-strategy-in-2026/",
    "title": "The Future of SEO: How AI Is Changing Content Strategy in 2026 - M&R Marketing",
    "description": "In 2026, don't just optimize your digital presence to reach the top of Google's results page.",
    "section": "citations"
  },
  {
    "id": 2,
    "url": "https://thistle.media/how-will-googles-ai-search-sge-reshape-seo-strategies-by-2026/",
    "title": "How Will Google's AI Search (SGE) Reshape SEO Strategies by 2026? - Thistle Media",
    "description": "Visibility is no longer just about ranking first; it's about being referenced, cited, and trusted by AI systems.",
    "section": "citations"
  }
]