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Google Sheets MCP by InsightfulPipe

by com.insightfulpipe
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Google Sheets Data Query

query_data
Read-only

Query Google Sheets data (Step 3 (FINAL) of workflow).

REQUIRED: Complete these steps first using query_contexts:

  1. request='accounts' - Get workspace_id, brand_id, spreadsheet_id, sheet_id AND available_requests

  2. request='actions_details' with actions=['query_sheet_data'] - Get detailed body structure

Common actions: query_sheet_data (read/filter data), update_cells (write), get_sheet_peak (preview), add_rows, create_spreadsheet.

Rely on info from steps 1-2 to construct the query body. Follow the schema exactly.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "body": "<body>"
    },
    "name": "query_data"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3/5.0
Behavior1/5

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

Annotations declare readOnlyHint=true, but the description lists 'update_cells (write)', 'add_rows', and 'create_spreadsheet' as common actions. That directly contradicts the read-only annotation and misrepresents the tool's side-effect profile.

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 definition is front-loaded with the purpose and required steps, and the numbered list is easy to scan. The common-actions list is somewhat extraneous and contributes to the contradiction, but the text is not bloated.

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

Completeness3/5

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

Output schema exists, so return values need not be explained, and the description covers the prerequisite workflow. However, it leaves the body semantics to another tool and is internally inconsistent about whether write actions are permitted, so it is not complete enough for confident 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?

The sole parameter is an untyped body object with 0% schema description coverage. The description only says to get body structure from query_contexts and follow the schema; it adds no field-level semantics itself.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource ('Query Google Sheets data') and identifies the workflow step, so the primary purpose is clear. It does not explicitly differentiate from the execute_action sibling and lists non-query actions, which keeps it from a top score.

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 explicit prerequisites and ordered steps using query_contexts before invocation, which is strong usage context. It does not state when to prefer execute_action or when not to use this tool, so no exclusions are provided.

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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