Narron

Why a brand's numbers changed between two analyses. Every other tool here reports the CURRENT state. This is the only one that can explain a CHANGE, so use it whenever the question is "why did my score drop / go up since last time" — never answer that from `get_visibility_summary` alone. Read `comparable` FIRST. When it is false, `notComparableReasons` says why the two scores are not on the same scale — `catalog_changed` means the prompt set was edited and the baseline restarted, so the difference is NOT a result about the brand. Say that plainly instead of reporting a decline. Then `regressed` and `improved` name the individual questions and engines that moved (`regressedCount` is the true total when the list is capped), `perception.dimensions` carries the five funnel stages with their deltas, and `topics` / `competitors` carry the rollups. A prompt in `rewordedPrompts` was edited between the runs — a different question, so it has no comparable history. Never present it as a loss. A null delta means "not measured", never zero.

Why ONE question's rank moved — what the answer itself changed. Call this after `compare_runs` names a question that gained or lost ground. The prompt is identical between runs; the ANSWER is not, and this is the only tool that shows what the engine actually said, which brands it named, and which sources it cited each time. `overtakenBy` names the brands positioned ahead of this one NOW that were not ahead before — usually the real answer to "why did my rank drop". `nowAheadOf` is the same in reverse. When `stillVisible` is false the brand fell out of the answer entirely, so there is no rank to be overtaken in and `namedInstead` says who occupies the space. `citations.gained` / `lost` is the actionable half: a customer cannot make a model prefer them, but they can go and exist on the sources it reads. `comparable: false` means the pair was not measured in both runs — say so rather than inferring a cause. Every `answer` is the short stored summary, not the full response.

How AI assistants PERCEIVE a brand, across the five funnel stages. Returns `dimensions` in funnel order — awareness, authority, recommendation, preference, trust — each with `score` (0-100 or null), `measured`, and how many answers it was judged over. Each stage also carries `delta` — the change against the most recent EARLIER run that measured that stage. A null delta means there is no earlier measurement to compare with, never "no change". This is different from `get_visibility_summary`: visibility is how OFTEN the brand appears, perception is WHAT is said about it. A stage with `measured: false` was not evaluated — report it as not measured and never as a score of 0.

Which brands AI assistants name alongside (or instead of) this one. Returns `competitors` ordered by share of voice, each with `domain`, `name`, `shareOfVoice` and `mentions`, plus `brandStats` for the user's own brand so the two can be compared directly.

Every prompt with the brand's text rank and source rank. Use this for "list my prompts with their ranks" and for "where am I ranked?" on a specific question. `get_prompts` answers what is being asked; this answers how the brand did. Returns `prompts` in catalog order, each with `text`, `topic`, `isEnabled`, `textRank`, `sourceRank`, `measured` and `measuredAnswers`, plus `promptCount` and `measuredCount`. `textRank` is the brand's position among the brands NAMED in the answer; `sourceRank` is its position among the sources the answer CITES. 1 is best. Each is the best position reached across the platforms that answered, and the two are independent — a brand can be cited without being named, or named without being cited. `null` is never 0 and never last place. A null `textRank` means the brand was not named; a null `sourceRank` means it was not cited. A row with `measured: false` was never run at all — report that as "not measured yet", never as a poor result.

The questions a brand is measured on, grouped by topic. Returns `topics`, each with a `name` and its `prompts` (`text` plus `isEnabled`), and `promptCount` for the catalog total. Use it for "what are you actually asking the AI about my brand?".

Concrete, stored recommendations for improving a brand's AI visibility. Returns `suggestions` (each with `title`, `category`, `priority` and `description`), `hasSuggestions`, and `hiddenCount` for any the workspace's plan withholds. Use this for "how do I improve?" — do NOT infer advice from scores. When `hasSuggestions` is false, say none have been generated yet rather than composing your own; and when `hiddenCount` is above zero, report only the number, never invent what the withheld ones say.

The topics a brand is measured on, and how it performs on each. Returns `topics`, each with `name`, `visibility` (percent of measured answers naming the brand) and `responses` (how many were measured). Useful for "where am I weak?" questions.

How visible a brand currently is in AI search. Returns `visibilityScore` (0-100), `aiMentions`, `averageRank`, `hasData`, and `platformBreakdown` per AI platform. These are the same numbers the Lens dashboard shows. When `baselineReset` is true the prompt catalog changed, so this score is NOT comparable to the one before it and `visibilityDelta` is null for that reason rather than for lack of history. Say so instead of reporting a change. For "why did it move", call `compare_runs` — this tool reports the current state only.

List the brands in the user's Lens workspace. Use this first — the other tools need a `brandId` from here. Returns `brands`, each with `brandId`, `domain` and `name`.