Marketing · Step
AI answer check
Checks how often AI answers name your brand.
What it does
One step of the Improve search visibility playbook. Goose runs it when you ask for the playbook.
The skill file
What your AI app reads when it runs this skill.
citation-check
Reads: search/questions.md; ../improve-search-visibility/references/citation-protocol.md; the last run record's per-question snapshot (../improve-search-visibility/references/run-memory.md); the canonical brand facts from the brain (for accuracy checks on brand questions); the tracked competitor list.
Does:
- Free pass (step 1): ChatGPT, AI Overview and AI Mode in the host's own browser (private window, signed out; stop on any CAPTCHA or refusal and mark the surface), and the host's web search for who ranks, labelled "web search". Paid top-up (step 3, only after the one yes): Google's exact page one through
gooseworks:data_call_provider(providerscrapecreators, path/v1/google/search, the query and region), inside the ceiling (thespend-gateskill (../spend-gate/SKILL.md) proxy branch), stopping at it. No browser → the minimum paste set, offered in the first message. - Run — ChatGPT once per question and three times for the key questions; AI Overview and AI Mode once each when Google allows; Google page one once per question in the top-up; pasted: 5 questions (up to 4 key questions + at least one brand question), ChatGPT twice, AI Overview and AI Mode once each. New chat per question, memory off, never the brand name in non-brand prompts. Wait for each answer to finish (protocol's wait rule); unfinished answers are retried once, never scored as misses.
- Only this run's observations count. An earlier run's answers are the baseline from the last run record (
../improve-search-visibility/references/run-memory.md): shown as "last checked " beside today's reading and compared only like with like (same question version, same route and location, the noise rule there), never counted in today's numbers or tables. A surface not checked today says "not checked today". - Record every run with the full field list; save verbatim answers. Note whether ChatGPT searched (sources shown) — answers without search come from training memory.
- Classify every cited URL by source type. For brand questions, list each stated fact and compare it to the brain: correct / wrong (quote both) / not on file.
- Score each row (named k of N, won/partial/lost/no-brand answer, prominence, stable or unstable), then mention rate per surface and stage, own-citation rate, third-party coverage and share of voice against the brands the engines named. Won = ≥ ⅔ of runs; unstable = some but not all; one run is never stable.
Writes: the rows table used by the report and the verbatim runs file (search/visibility/<date>-runs.md, not imported); every charge is logged by the spend gate, and the report states credits charged against the ceiling in the gate's own words.
Never: reports one run as fact; passes an organic or API read off as what buyers see in the AI apps; ranks the brand "#2 in ChatGPT".

