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Create a Google Sheet

create_sheet

Create a new Google Spreadsheet in the user’s Drive and optionally fill it with rows — e.g. export a swipefile, ad list, or performance report. Pass rows as an array of row arrays (first row = headers). Returns the spreadsheet id + URL. Needs Google Drive connected (Settings ▸ Connectors ▸ Google Drive — one connection covers Drive, Sheets and Docs).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNorows to write — array of row arrays; first row = headers
titleNospreadsheet title

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the annotations (which already indicate a non-read-only operation), it discloses the optional fill behavior, the row-array layout including header treatment, the returned spreadsheet id + URL, and the Drive connector requirement. No contradiction with annotations.

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?

Four tight sentences that front-load the core behavior, then add only the needed formatting, return, and connection details. No filler or repetition.

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

Completeness4/5

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

For a simple 2-parameter tool with no output schema, the description covers return value, row format, and auth prerequisite. It is slightly incomplete only in not naming the sibling tools for appending/updating an existing sheet.

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 coverage is 100% and both rows and title are already described in the schema; the description mostly restates 'array of row arrays, first row = headers' in natural language. It adds little information that an agent couldn't already derive from 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?

States a specific action ('Create'), an exact resource ('new Google Spreadsheet in the user's Drive'), and gives concrete example payloads ('swipefile, ad list, performance report'). Saying 'new' plus 'Spreadsheet' separates it from create_doc and from update/append sheet tools.

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?

Gives clear contexts for use: creating a fresh spreadsheet and optionally exporting row data, and a concrete prerequisite ('Needs Google Drive connected'). It doesn't explicitly say when to prefer append_to_sheet or update_sheet instead, so it misses the explicit exclusions needed for a 5.

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

A3.8/5.0
Disambiguation3/5

The descriptions are exceptionally detailed and cross-reference one another (e.g. post_edit vs finish_video vs edit_video), which genuinely helps, but 168 tools still contain tight clusters—video creation/editing, scheduling, and post-publishing—where misselection is easy. Many tools also reference hidden companions not in the visible set, adding ambiguity.

Naming Consistency4/5

The overwhelming majority follow a clear verb_noun snake_case convention (post_to_x, search_x, list_x, create_x, update_x). Minor deviations like store_get, billing_status, error_detail, and the hermoso_ prefix break the pattern slightly but do not obscure it.

Tool Count1/5

At 168 tools this is far beyond the 50+ threshold, and regardless of how broad the platform's purpose is, the sheer number makes the set hard to navigate. The server mitigates with groups and find_tools/call_tool, but the count itself is extreme.

Completeness4/5

The set covers a full marketing lifecycle—research, planning, creation, publishing, scheduling, measurement, billing, and file management—with no major workflow gaps. Some referenced tools like list_shopify_products and manage_meta_post are not in the visible list, but find_tools and call_tool are explicitly designed to close that gap.