Project Tango

Draft Product Copy

draft_product_copy

Fetches a product by SKU and generates structured marketing copy—headline, short and long descriptions, bullet points, and SEO tags—tailored to its category and tags.

Instructions

Looks up a product by SKU and generates structured, high-conversion marketing copy (headline, short and long description, key bullet points) plus SEO tags tailored to that product's category and tags.

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": {
      "sku": "<sku>"
    },
    "name": "draft_product_copy"
  }
}

Input Schema

Name	Required	Description	Default
`sku`	Yes	The exact product SKU to generate marketing copy for, e.g. 'TCH-AB-001'.

Output Schema

Name	Required	Description	Default
`sku`	Yes
`copy`	Yes
`seoTags`	Yes
`productId`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.2.0Nov 10, 2026

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the shape of the generated output and that the copy is tailored to the product's category and tags, and the verbs 'looks up' and 'draft' imply a non-destructive read/generate flow. However, it never states whether the draft is persisted, what happens if the SKU is unknown, or that generation may be slow/costly — real gaps for a mutation-adjacent tool with zero annotation coverage.

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?

A single well-formed sentence with the lookup-and-generate action front-loaded and the output list appended as a compact parenthetical. Every clause earns its place with no filler or repetition.

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

Completeness4/5

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

For a one-parameter tool with full schema coverage and an output schema (so return values need no explanation), the description covers the essential action and output content adequately. It is only slightly incomplete on usage routing and persistence/error behavior, which keeps it at 4 rather than 5.

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?

There is a single parameter and schema description coverage is 100%, with the schema already documenting the SKU format and an example value. The description only restates that the SKU identifies the product to generate copy for, adding no format or constraint detail beyond the schema. 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 states a concrete verb and resource: it looks up a product by SKU and generates marketing copy, then enumerates the artifacts produced (headline, short/long description, bullets, SEO tags). That is far more specific than the name alone and clearly sits apart from the inventory/order siblings. It stops short of explicitly naming an alternative tool, so it lands at 4 rather than 5.

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 only implied: an agent can infer you call this when you need marketing copy for a SKU. There is no statement of when to prefer it over siblings (e.g., versus list_all_products for raw product data) and no prerequisites such as the SKU needing to exist. That is the definition of a minimum-viable 3.

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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