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Zendesk MCP Server by Fruggr

by fruggr

Compare Article Translations

compare_translations
Read-onlyIdempotent

Compare two article locales to check if the target translation needs updating. Reports freshness, outdated flags, and structural alignment.

Instructions

Compare two locales of the same article to decide whether the target translation needs work, reporting independent signals instead of one ambiguous verdict. (1) Header — a "Freshness" verdict for the target, derived from the two translations' updated_at timestamps: if the source was edited after the target it is "likely behind, review recommended" (with the day gap), otherwise "up to date". This is the primary staleness signal and is always available. (2) Zendesk's own per-translation "outdated" flag for the target ("yes"/"no"/"unknown"), shown as a secondary overlay: it is only set through Guide's native "mark out of date" workflow and NOT by API edits, so a "no" does not by itself mean current — prefer Freshness. (3) A global structure check (section count and heading-tag sequence); on mismatch the header warns the per-index rows may be misaligned. (4) A per-section table matched by index, status "ok" (present in both), "missing" (present in source, absent in target) or "extra" (present in target, absent in source). (5) Per-section source/target word counts, INFORMATIONAL ONLY: a length difference between languages is normal and is deliberately NOT flagged as a divergence — do not read a word-count gap as an edit regression or staleness. Read-only; performs three Help Center GET calls (both translations plus the translations list for the outdated flag).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
article_idYesArticle ID — the numeric id of the Help Center article. Obtain it from list_articles or search_articles.
source_localeYesReference locale to diff against, e.g. "en-us". Usually the article source_locale (from get_article).
target_localeYesTarget locale to compare against source
Behavior5/5

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

Annotations indicate read-only, open world, idempotent, non-destructive. Description confirms read-only nature, specifies three GET calls, and explains limitations (e.g., outdated flag set via native workflow, not API edits). No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Lengthy but well-structured with numbered sections. However, some details (e.g., 'per-index rows may be misaligned') could be simplified without losing clarity. Still, it is organized and readable.

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?

No output schema, but description fully details all return signals: freshness verdict, outdated flag, structure check, per-section table, word counts. Also clarifies that word-count gaps are informational and not divergence indicators.

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 covers 100% of parameters with descriptions. The tool description adds minimal new info beyond the schema, e.g., 'obtain from list_articles or search_articles'. Baseline 3 is appropriate.

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?

Clearly states the tool compares two locales to decide if target translation needs work, listing five distinct signals. It distinguishes from sibling tools like get_article or list_articles by focusing on comparison and staleness detection.

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?

Explicitly describes when to use (compare translations for staleness) and notes it is read-only with three GET calls. Does not explicitly state when not to use or compare to alternatives, but the unique purpose makes this less critical.

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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