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Search help-center articles

search_documents
Read-onlyIdempotent

Use this when someone asks which help article covers a topic or question on one of their websites. Returns up to 5 matching published articles with id, title, slug and language, matched by meaning in one language (English by default). Not for reading an article's text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesWhat the article should cover, in natural language, up to 500 characters
localeNoLanguage code to search in, e.g. en, it or fr; defaults to en
websiteIdYesWebsite whose help center to search

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
documentsYesClosest matches first. Content chunks, embeddings, scores, prompts and arbitrary metadata are excluded.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedInput schema / properties / locale / description
      Previous value: -"Filter by locale (e.g. en, it, fr)"New value: +"Language code to search in, e.g. en, it or fr; defaults to en"
    • changedInput schema / properties / query / description
      Previous value: -"Semantic search query"New value: +"What the article should cover, in natural language, up to 500 characters"
    • changedInput schema / properties / websiteId / description
      Previous value: -"Organization-owned website id to search"New value: +"Website whose help center to search"
    • addedOutput schema / properties / documents / description
      Added value: +"Closest matches first. Content chunks, embeddings, scores, prompts and arbitrary metadata are excluded."
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and a closed-world hint, so the safety profile is covered. The description adds useful behavior the annotations cannot convey: a hard result cap of 5, semantic rather than keyword matching, restriction to published articles, and single-language matching.

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 tight sentences with no filler: the use case and return shape come first, the scope limit and the negative boundary follow. Every clause carries information an agent needs before calling.

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?

An output schema exists, so return values are already specified, and annotations carry the safety profile. The description nevertheless fills the remaining gaps — result cap, semantic matching, published-only scope, one-language constraint, and the read-vs-read-text boundary — leaving nothing material for an agent to guess.

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% and each of the three parameters is documented in-schema, including the en default for locale. The description only lightly reinforces this ('matched by meaning in one language (English by default)'), so the baseline of 3 is appropriate rather than anything higher.

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 names a specific verb and resource ('search help-center articles') and adds precision: 'Returns up to 5 matching published articles with id, title, slug and language.' It also distinguishes itself from adjacent document tools with 'Not for reading an article's text,' so an agent can separate it from get_document and list_documents.

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?

It gives a concrete triggering condition ('when someone asks which help article covers a topic or question on one of their websites') and an explicit exclusion ('Not for reading an article's text'). The exclusion is implied rather than naming the alternative tool (get_document), so it stops just short of the full when/when-not/alternative pattern.

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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