The ads a company is running
ads_creatives is a $0.20 GET request on the Wuthering AI API. List an advertiser's creatives with first-seen and last-seen dates. It answers complete JSON, and a call that fails is not charged.
Endpoint
GET /v1/ads_creatives
Price per successful call
$0.20
Failed calls
Not charged
curl 'https://wutheringai.com/v1/ads_creatives?advertiser_id=…&token=YOUR_TOKEN'
What does ads_creatives return, and when should you call it?
Return the ad creatives an advertiser is running, each with the dates it was first and last seen, its format, and a preview image URL.
The dates are the point: an ad running continuously for ninety days or more has survived the advertiser's own performance review, which makes its message a tested claim rather than a guess. Sort by run length before reading anything.
IMPORTANT: the `title` field is the ADVERTISER'S NAME, never the ad headline. The headline exists only as pixels inside preview_image, so reading the actual copy means fetching and transcribing that image.
Returns: creative_id, format, first_shown, last_shown, url, preview_image, preview_url, title (advertiser name).
Takes an advertiser_id or that advertiser's domain, never a category keyword: there is no way to ask this tool who advertises on a term. Run wuthering_ads_advertisers first and pass the id it returns, which is both more precise and the only path that works from a brand name.
Use to find which messages a competitor has proven work, and to date how long each has run. Don't use it to discover who advertises in the first place, which is wuthering_ads_advertisers, and don't read title as the ad headline.
What parameters does ads_creatives take?
ads_creatives accepts 7 parameters, none of them required. Array values are comma-separated on the query string.
| Parameter | Type | Required | Description |
|---|---|---|---|
| advertiser_id | string | no | Advertiser id from wuthering_ads_advertisers, in the form AR followed by digits. |
| target | string | no | Advertiser's registrable domain, for example 'acme.com', if you have no advertiser id. |
| platform | string | no | Restrict to one surface. Defaults to all surfaces.One of: all, google_play, google_maps, google_search, google_shopping, youtubeDefaults to all |
| ad_format | string | no | Restrict to one creative format. Defaults to all formats.One of: all, text, image, videoDefaults to all |
| location_code | number | no | Numeric location code to scope results to. Defaults to 2840 (United States). Search volume and competition vary sharply by country, so set this when the question is about a specific market.Defaults to 2840 |
| language_code | string | no | ISO language code for results, for example 'en' or 'de'. Defaults to 'en'.Defaults to en |
| limit | number | no | Maximum rows to return (1 to 120, default 40). Ask for the fewest that answer the question: every row is billed and spends the caller's context.Defaults to 40 |
Which playbooks call ads_creatives?
7 of the research playbooks name ads_creatives in their method. Each is free to read and says where in the sequence the call belongs.
- Is there real demand for this?Test an idea against the cheapest evidence that could kill it — search demand, sustained ad spend, posted salaries, and the words buyers use — and return a verdict with the number that decides it.
- Where is the unoccupied position in this category?Map the category around one domain as an idea maze — the forks it has already run, who took each branch, which walls are still walls and which have moved — then return the one open position with the offer that takes it: buyer, bundle, price metric and message, decided together.
- Who are we really up against?Work April Dunford's positioning sequence from public evidence: the alternatives a prospect would actually use, what only you do, the value that follows, who cares most, and the category that makes all of it obvious.
- What do we charge, and does the money work?Anchor price against what competitors actually charge and meter on, size willingness to pay from what the problem costs today, then run CAC, LTV and payback across three scenarios.
- Where do the next 1,000 customers come from?Score every plausible channel against the product's own characteristics, measure the reachable demand and the cost of entry for each, and commit to one with its CAC and its ceiling stated.
- Is this company actually growing?Read one company's trajectory from public evidence: branded demand year over year, the acquisition engine underneath it, whether that demand was earned or bought, and what payroll says ships next — then name the questions only a data room can close.
- What would prove us wrong?Turn a belief the plan depends on into an explanation that cannot be bent to fit any result, name the rival explanations that would produce the same evidence, and pay only for the observations that would come out differently under each.
Reference for ads_creatives · last updated · published by Wuthering AI