Promptify

Generate ad script (spends credits)

generate_ad_script

Generate a full ad script package for a product: 10 hooks, a scene-by-scene script, and model-native video prompts (Veo/Kling). Costs about 2-3 credits, metered and refunded in full if it fails. This CREATES an ad in the user's Promptify workspace and returns a link to it — it does not render video.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "productTitle": "<productTitle>"
    },
    "name": "generate_ad_script"
  }
}

Input Schema

Name	Required	Description
`format`	No	UGC testimonial \| Unboxing \| Problem → solution \| Street interview \| Before/after \| Founder story
`language`	No	Language to write the ad in. Defaults to English.
`productUrl`	No	Optional product page URL.
`templateId`	No	Optional template id from list_templates — builds the ad on that hook device and beat structure.
`productTitle`	Yes	The product's name.
`productDescription`	No	What it is and who it's for. The more concrete, the better the script.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), it discloses the credit cost (about 2-3), that metering is refunded in full on failure, that a persistent ad object is created in the user's workspace, and that a link is returned. That is exactly the side-effect, cost, and failure-mode context an agent needs before committing a mutation.

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

Conciseness5/5

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

Two dense sentences, front-loaded with the deliverable, then cost, then side effect, then the negative scope boundary. No filler and no repetition of the title.

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

Completeness5/5

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

For a mutating generation tool with no output schema, the description covers what is produced, what it costs, what happens on failure, what side effect occurs, and what is returned (a link). Nothing material for correct invocation is missing.

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 all six parameters are already documented, and the description adds little parameter-level meaning beyond reiterating that templateId ties to list_templates and that richer product descriptions yield better scripts. Baseline 3 applies when the schema carries the parameter burden.

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

Purpose5/5

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

States a specific verb and resource (generate an ad script package for a product) and enumerates the deliverables: 10 hooks, a scene-by-scene script, and model-native video prompts. It also draws a hard boundary against the sibling render_ad by stating it does not render video, so an agent can distinguish the two without opening either schema.

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

Usage Guidelines4/5

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

The 'does not render video' clause implicitly routes the agent to render_ad for actual rendering, and the mention of templateId 'from list_templates' names the prerequisite sibling for that parameter. There is no explicit when-to-use/when-not statement relative to draft_ad_plan or scrape_product, so the guidance is clear but not fully enumerated.

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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