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Skeptomenos

google-workspace-mcp-advanced

by Skeptomenos

search_messages

Searches Google Chat spaces for messages matching a text query, returning formatted results.

Instructions

Searches for messages in Google Chat spaces by text content.

Returns: str: A formatted list of messages matching the search query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_google_emailYes
queryYes
space_idNo
page_sizeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.10

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations provided, the description must disclose behavior, but it only states that it returns a formatted list. It does not mention pagination, scoping across spaces, authentication requirements, or read-only nature. The 'Searches' phrasing implies non-destructive behavior but is not explicit, and key behavioral details like the meaning of page_size or space_id are omitted.

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 concise and front-loaded with the primary purpose in one sentence. The 'Returns' section adds value by indicating the output is a formatted list, and overall the description is minimally sized with no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 parameters, no annotations, and a non-trivial domain (Google Chat), the description is too thin. It lacks behavior details, parameter explanations, and usage context. While an output schema exists, the description does not cover edge cases (e.g., optional space_id, pagination via page_size) that an agent needs to know for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description is expected to explain parameters. It clarifies that 'query' is text content and 'space_id' relates to Google Chat spaces, but it does not explain 'page_size' or 'user_google_email'. This leaves the agent with incomplete understanding of how to invoke the tool correctly.

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 'Searches for messages in Google Chat spaces by text content', which identifies the specific action (search), resource (messages), and domain (Google Chat spaces). It distinguishes itself from sibling tools like search_gmail_messages and search_docs by explicitly naming Google Chat.

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

Usage Guidelines3/5

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

The description implies usage context (use when you need to find Chat messages by text) but provides no explicit guidance on when not to use it or alternatives. It does not compare with similar tools such as get_messages or search_gmail_messages, leaving the agent to infer the appropriate scenario.

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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