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google-workspace-unlimited

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Find Google Workspace tools by keyword when you don't know the exact name. Filter by tags and choose detail level to browse or retrieve schemas.

Instructions

Find this server's Google Workspace tools by keyword (BM25 over names, descriptions, and tags). Use when: you don't know the exact tool name yet. To browse by category use tags; once you have names, use get_schema for parameters, then execute to call them. To search past results rather than tools, use semantic_search. Returns: matching tools as names + descriptions ('brief', default), parameter markdown ('detailed'), or complete JSON definitions ('full'). An empty result means no keyword match — retry with different terms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoFilter to tools with any of these tags before searching
limitNoMaximum number of results to return
queryYesSearch query to find available tools
detailNo'brief' for names and descriptions, 'detailed' for parameter schemas as markdown, 'full' for complete JSON schemasbrief

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv3.0.0
    • changedOutput schema / (root)
      Previous value: -{
      -  "properties": {
      -    "result": {
      -      "type": "string"
      -    }
      -  },
      -  "required": [
      -    "result"
      -  ],
      -  "type": "object",
      -  "x-fastmcp-wrap-result": true
      -}New value: +null
  2. Addedv2.3.2

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does this well by revealing the BM25 ranking mechanism, the three return detail modes, the default 'brief' mode, and the meaning of an empty result ('no keyword match — retry with different terms'). This gives an agent a clear behavioral model beyond what the schema states.

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 compact and well-structured. The primary purpose is stated first, followed by explicit usage guidance, sibling routing, and return behavior. Every sentence earns its place; there is no filler or repetition of schema details.

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?

For a search tool with no annotations and no output schema, the description is thorough: it explains what is searched, when to use it, how to route to alternatives, what the return values look like in each detail mode, and how to interpret empty results. Nothing critical is missing for safe and correct invocation.

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%, so the schema already documents all parameters clearly. The description adds a little context around the detail parameter's output modes, but most of what it says about parameters mirrors the schema. This meets the baseline but does not go substantially beyond it.

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 states a clear verb and resource: 'Find this server's Google Workspace tools by keyword,' and specifies the search mechanism (BM25 over names, descriptions, and tags). It also distinguishes the tool from siblings like tags and semantic_search, so an agent can immediately tell what this tool is for.

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 gives explicit when-to-use guidance: 'Use when: you don't know the exact tool name yet.' It also names alternatives and the conditions for choosing them, such as using tags to browse by category, get_schema for parameters, execute to call, and semantic_search for past results. This is exemplary routing guidance.

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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