ProofPass

Change product master data

update_product

DestructiveIdempotent

Changes master data of a product of the connected account: name, article number, GTIN, UFI, description, search words. Only the fields given change; an empty string clears a field. On a public product the change is visible at once, as after "Speichern" in the dashboard, and the previous values are not kept. Visibility, category, documents and deletion stay in the dashboard.

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": {
      "product_id": "<product_id>"
    },
    "name": "update_product"
  }
}

Input Schema

Name	Required	Description
`ufi`	No	UFI, e.g. N1Q0-30DW-K00N-4VKE
`gtin`	No	GTIN/EAN with 8, 12, 13 or 14 digits
`name`	No	New product name
`keywords`	No	Search words, comma separated: old names, colours, pack sizes
`language`	No	Language of the answer: "de" (German, default), "en" (English) or "pl" (Polish). Product and account answers are written in German and English; content without a translation comes in German.
`product_id`	Yes	Product id, as list_my_products returns it
`description`	No	Two or three sentences on what the product is for
`article_number`	No	Article number

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 14, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Annotations already flag destructiveHint=true and idempotentHint=true, but the description earns credit by explaining concretely what that means: partial-update semantics (only supplied fields change), empty string as an explicit clear signal, immediate visibility on public products, and no retention of previous values (no undo). This is exactly the operational context annotations cannot convey.

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?

Three sentences, front-loaded with the mutable-field list, then update semantics, then the scope boundary. No filler; the "Speichern" dashboard analogy efficiently conveys immediate-visibility behavior in one phrase.

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 an 8-parameter mutation tool with full schema coverage and no output schema, the description supplies everything an agent needs beyond structured fields: diff semantics, clearing behavior, immediacy/no-history of the change, and the boundary against dashboard-only actions.

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 the baseline is 3 and the schema already documents each field's format and limits. The description does add two non-obvious semantics the schema cannot express — supplied-fields-only diffing and empty-string clearing — but it says nothing about product_id or how the language parameter affects the answer.

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 ("Changes master data of a product") and enumerates exactly which fields are mutable: name, article number, GTIN, UFI, description, search words. The closing sentence carves out what is NOT this tool's job (visibility, category, documents, deletion), so an agent can distinguish it from dashboard-bound or read-only siblings without opening a 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?

Gives clear when-to-use context plus explicit exclusions (visibility, category, documents, deletion must go through the dashboard), which prevents misrouted edit attempts. It does not name a sibling tool as the alternative for those excluded operations, so it stops short of full routing 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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