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product_publish_from_brief

Publish B2B product listings from minimal seller briefs, with AI generating titles, highlights, and details, and return draft product IDs and missing fields.

Instructions

Publish a product from a minimal brief — the seller provides only facts; Claude enriches the rest.

Provide brief inline or a brief_path (JSON file, confined to allowed dirs). The brief needs: brief (short description), category_id, images (main 4–6 + detail), price ({unit, moq, tiers}), and facts (place_of_origin, material). Claude writes the title, highlights, detail modules, FAQs, custom parameters, and picks the descriptive category attributes from the schema's allowed options. Returns the draft product_id, missing_required, ai_filled (what was auto-generated), and warnings (e.g. fewer than 4 main images — AI cannot generate real product photos). Defaults to draft=True.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
briefNo
draftNo
brief_pathNo
account_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
errorNo
responseNo
warningsNo
ai_filledNo
error_typeNo
product_idNo
biz_successNo
filled_fieldsNo
missing_requiredNo
needs_more_main_imagesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare the write/open-world/non-idempotent profile, so the description only needs to add what they don't cover. It does add real value: `brief_path` is confined to allowed directories, draft defaults to true, and warnings can be raised when fewer than 4 main images exist because AI cannot generate real photos. The enumerated return fields are largely redundant with the output schema, keeping this short of a 5.

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?

Front-loaded with the purpose, then input modes, then brief contents, then outputs — a sensible information hierarchy with no filler sentences. It is dense for a single paragraph, but every clause contributes.

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 complex AI-enrichment tool the description covers input modes, required brief fields, defaults, and failure warnings, and an output schema exists to carry return details. The only notable gaps are the unexplained `account_key` and the absence of any note about authorization prerequisites or repeat-call behavior.

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

Parameters4/5

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

Schema description coverage is 0% and `brief` is an untyped object, so the description carries the full burden — and it does, spelling out the required brief keys (description, category_id, images, price with unit/moq/tiers, facts with place_of_origin/material). It also clarifies `brief_path` and the `draft` default. `account_key` is left unexplained, which prevents a top score.

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 ('Publish a product') plus the defining scope ('from a minimal brief — the seller provides only facts; Claude enriches the rest'). This scope is exactly what separates it from the sibling product_publish, so an agent can route between them 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 Guidelines3/5

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

It explains how to supply input (inline `brief` or `brief_path`) and what the brief must contain, which is genuine usage context. However, it never says when to choose this tool over product_publish or product_render_draft, nor any precondition such as authorization or schema lookup. Usage is implied rather than stated.

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