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Documentation Index

Fetch the complete documentation index at: https://docs.shareofmodel.ai/llms.txt

Use this file to discover all available pages before exploring further.

In generative search, the final answer is only part of the story. LLMs rely on two distinct layers:
  • Sources — domains and URLs used to build the answer (influence)
  • Links — domains and URLs shown in the final output (visibility)
These two layers often differ. Together they shape what is visible and how brands are represented in generative answers. The Sources & Links view helps you see which domains influence answers, which ones reach users, and how brand mentions are framed across engines.

What this view helps you analyse

Main table: domains and URLs at a glance

Main table
Compare domains and URLs across three dimensions.

Role in the answer

The Type column shows whether a domain is:
  • Source — used to build the answer
  • Link — visible in the final output
  • Source & Link — both influencing and visible

Consistency across engines and queries

Use the Engines, Results and Presence rate columns to distinguish one-off appearances from recurring influence.

Brand mentions & sentiment

The My Brand Mentions column flags whether your brand is mentioned in the source content or generated answer (returned by the LLM API).
Mentions embedded directly inside URL strings are not counted.
When a brand is mentioned, sentiment scores qualify how it is framed (range from -1 to +1, with a breakdown of positive, neutral and negative mentions).

Domain details: content patterns

Domain details
Click a domain to see the URLs associated with that source. You can observe:
  • which URLs are used as Sources, Links, or both,
  • how often each URL appears,
  • whether brand mentions are present at URL level,
  • how brand sentiment varies across URLs from the same domain,
  • the underlying content (open URLs directly from the interface).

Results details: linking domains, URLs and queries

Results details
Clicking the Results number opens the queries by engine on which the item appears as a Source and/or Link. You may notice that:
  • the same query behaves differently across engines,
  • a domain is a Source on one engine and a Link on another,
  • some queries rely on Sources without showing Links,
  • the same domain can mention a brand with different sentiment depending on the query or engine.

Reading cues

These are signals to read, not rules.
Content that explains concepts, provides background or supports the model’s reasoning. Common on queries where understanding the topic matters more than pointing to a single reference.
Reflects different source-selection logic and engine preferences for structure, depth or citation. LLM visibility should be read engine by engine, not as a single aggregated signal.
LLMs adapt how they use content based on the nature of the question, rather than applying a fixed rule.

How to use this view effectively

Start by identifying domains that consistently act as Sources, even when they are not visible as Links. These shape how answers are constructed and reveal where influence happens before visibility.

What’s next

Sources vs Links

Conceptual primer on the two layers.

Ranked URLs

Drill into URL-level visibility.