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Ads from a product URL

ad_from_url

Extract a product from a URL and draft ad angles as an Ad Studio project. With render=true, also renders ad variants for every angle in the chosen formats and aspects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesProduct or landing page URL
titleNoOptional project title
renderNoRender variants right away (uses credits)
aspectsNoAspect ratios to render
formatsNoAd formats to render
languageNoAd language code, e.g. en
avatar_idNoAvatar presenter id; required for the ugc_avatar format

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With only openWorldHint declared, the description usefully discloses the two operating modes (draft-only vs render variants for every angle) and the multiplicative render scope. It stops short of disclosing cost magnitude, whether projects are persistent, or how to track an async render, which the annotations do not cover.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences with the primary action front-loaded and the optional render behavior following. No filler, though it is short enough that the brevity borders on underspecification rather than polished economy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description should say more about what comes back and the follow-up workflow. It never mentions polling a job (get_job) or estimating credit usage (generation_quote), leaving meaningful gaps for a multi-parameter generation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every parameter is already documented (including credits for render and avatar_id's requirement for ugc_avatar). The description's "every angle in the chosen formats and aspects" adds a small cross-parameter semantic but no syntax or format detail beyond the schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verbs ("Extract", "draft") tied to concrete resources (a product from a URL, ad angles as an Ad Studio project), so the core action is unmistakable. It does not, however, explicitly contrast itself with any sibling such as create_reel or generation_quote, leaving differentiation to inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the URL-to-ads workflow and the render=true condition, but there is no explicit when-to-use statement, no prerequisite (e.g., obtaining a quote or credits first), and no named alternative tool. An agent must infer that this is the entry point for URL-based ad generation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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