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Make a pitch for a brand

bring_a_brand

Paste a brand's store or product link: CartViral imports it, makes 3 AI clips of its best product (18 credits) and returns a public page to send the brand, with a "Launch your offer" button that carries this account's referral code (30% of what the brand pays CartViral, for life). Max 10 a day. Offers track sales in Shopify, so pitch Shopify brands.

Input Schema

NameRequiredDescriptionDefault
urlYesThe brand's store or product page URL

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only declare this is a non-readOnly, non-idempotent, open-world write; the description goes well beyond them by disclosing credit cost, daily rate limit, that a public page is published externally, and that the account's referral code is embedded. These are exactly the traits an agent needs before invoking a costly, externally visible operation.

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?

Everything is packed into one dense but front-loaded sentence: action, cost, output, incentive, limit, and targeting each appear once with no repetition. It is slightly run-on and could be split for scannability, but no sentence is wasted.

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 tool that spends credits and publishes an external page, the description covers cost, rate limit, returned artifact, monetization, and ideal target brand type. With one simple parameter and no output schema, an agent has everything required to call it correctly.

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?

Only one parameter and schema coverage is 100%, so the schema already documents it. The description restates it as 'brand's store or product link' but adds no format or validation guidance beyond the schema wording — the expected baseline of 3.

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 concrete verb chain (import link → generate 3 clips → return public pitch page) with a named resource and output. It is unmistakably different from siblings like list_pitches or import_products, and even discloses the cost (18 credits) and the referral mechanics that define the action.

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?

Gives a clear triggering input ('paste a brand's store or product link') and a qualifying condition ('Offers track sales in Shopify, so pitch Shopify brands'), plus a hard cap of 10 a day. It stops short of explicitly naming alternatives (e.g., list_pitches to review existing pitches), so it falls just under full when-to-use guidance.

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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