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fruggr

Zendesk MCP Server by Fruggr

Update Article Translation

update_article_translation
DestructiveIdempotent

Update the title and body of an article translation in a specific locale. Replaces the full body content — for single-section edits use the dedicated update section tool.

Instructions

Update article content (title, body) in a specific locale. For targeted edits on one or a few sections, prefer update_article_section — this tool replaces the FULL body and re-sends the entire article on each write. Use the article's source_locale (from get_article) for the default language, or another locale for translations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoNew full body (HTML) for this locale. Replaces the entire body — for a single-section edit prefer update_article_section. Omit to leave the body unchanged.
draftNoWhen true, keeps this translation as a draft; when false, publishes it.
titleNoNew title for this locale. Omit to leave the current title unchanged.
localeYesLocale of the translation to update, e.g. "en-us" or "fr". Use the source_locale (from get_article) to edit the default language.
article_idYesArticle ID — the numeric id of the article whose translation to update. Obtain it from list_articles or search_articles.
Behavior4/5

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

Annotations already declare destructiveHint=true, so the bar is lowered. The description adds behavioral context by stating that the tool 'replaces the FULL body and re-sends the entire article on each write,' which explains the destructive nature and re-sending behavior beyond what annotations provide.

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?

The description is two sentences long, front-loading the purpose and then providing usage guidance and behavioral notes. Every sentence adds value with no redundancy or unnecessary detail.

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?

Given the tool's complexity, rich annotations, and clear schema, the description covers all necessary context: when to use, what it does, how it differs from siblings, and a key behavior (full body replacement and re-sending). No gaps remain.

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 100%, so the baseline is 3. The description adds value by contextualizing the locale parameter (use source_locale for default language) and contrasting body with the sibling tool, improving semantic understanding beyond the schema.

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?

The description clearly states the tool updates article content (title, body) in a specific locale. It distinguishes itself from the sibling tool 'update_article_section' by specifying that this tool replaces the full body, making the purpose highly specific and unambiguous.

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

Usage Guidelines5/5

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

The description explicitly advises when to use alternatives: 'For targeted edits on one or a few sections, prefer update_article_section.' It also explains how to handle the default language using source_locale, providing clear context for correct invocation.

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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