mcp

answer_query

Read-onlyIdempotent

Use answer_query to get a grounded answer to a query about Google developer products. This tool has limited quota. This tool will synthesize information from the corpus to generate an answer to the query. answer_query grounds answers using the same corpus as search_documents. This tool returns the generated answer_text and a list of document names (references) used to generate the answer. Use get_documents with the document names to fetch the entire document content if needed.

If you get a 429 out of quota error, use search_documents instead.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes	Required. The query to answer.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`answerText`	No	The answer to the query.
`references`	No	Output only. The resource names of the documents used to generate the answer.

TDQS

A4.4/5.0

Behavior4/5

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

While annotations already declare readOnly/idempotent behavior, the description adds valuable context about limited quota and the synthesized answer process, including return of references. This goes beyond structured data, especially the rate-limit disclosure.

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?

The description is moderately sized but each sentence contributes: purpose, quota warning, grounding, return values, and fallback. It is front-loaded with the primary action and contains no fluff.

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 simple one-parameter schema, existing output schema, and annotations, the description provides a complete operational picture, including error handling via quota fallback and reference retrieval. It fully addresses the low-complexity tool.

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?

The schema covers the single query parameter at 100% with a clear description. The tool description reinforces the domain ('Google developer products') but adds no additional syntax or formatting details 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's function with a specific verb ('get a grounded answer') and resource ('query about Google developer products'). It distinguishes from siblings by noting the corpus relationship to search_documents and the reference-fetching role of get_documents.

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?

Explicit guidance is provided: 'Use get_documents...' and 'If you get a 429 out of quota error, use search_documents instead.' This clearly indicates when to use the tool versus alternatives.

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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TDQS

A4.4/5.0

Disambiguation5/5

Each tool has a clearly distinct role: answer_query generates a synthesized answer, search_documents returns chunks and metadata, and get_documents retrieves full documents. The descriptions explicitly clarify when to use each, minimizing ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern: answer_query, get_documents, search_documents. The naming is uniform and predictable.

Tool Count5/5

Three tools is a well-scoped set for a documentation retrieval server. Each tool serves a distinct and necessary function without redundancy or bloat.

Completeness5/5

The tool surface covers the full documentation workflow: search, retrieve full content, and get grounded answers. Since the domain is read-only documentation access, there are no obvious missing operations.

Resources

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