AdCopilot

Google Sheets: export to a spreadsheet

sheets_export

Writes tables (20 tabs, 5,000 rows at most), or customer_id with gaql (50,000 Google Ads rows), to a new Google Sheets spreadsheet in the person's own Drive or as new tabs of one AdCopilot made (spreadsheet_id). Adds only, never overwrites; text never runs as a formula. It is private: AdCopilot never shares or publishes it.

Tools revision: d80f65c0.

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": {
      "title": "<title>"
    },
    "name": "sheets_export"
  }
}

Input Schema

Name	Required	Description	Default
`gaql`	No
`title`	Yes
`tables`	No
`customer_id`	No
`spreadsheet_id`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 25, 2026

TDQS

A4.2/5.0

Behavior5/5

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

Goes well beyond the annotations by specifying hard limits (20 tabs, 5,000 rows; 50,000 Google Ads rows), append-only semantics ("Adds only, never overwrites"), formula-injection safety ("text never runs as a formula"), and privacy behavior (never shared or published). These are the exact traits an agent needs before writing data into a user's Drive.

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?

Two dense sentences that front-load the core action and limits, with parenthetical parameter hints. Slightly tangled phrasing ("in the person's own Drive or as new tabs of one AdCopilot made") costs a little readability but nothing is wasted.

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?

Return shape is covered by the output schema, and limits, safety, and destination modes are all addressed, which is strong for a 5-parameter export tool. Missing only the meaning of `title` and explicit guidance on mutually exclusive argument combinations.

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

Parameters4/5

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

Top-level schema fields carry no descriptions, so the description must compensate, and it does for customer_id+gaql, tables, and spreadsheet_id. The required `title` parameter is never explained, and the two-mode exclusivity is left implicit, so a small gap remains.

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?

"Writes tables ... or customer_id with gaql ... to a new Google Sheets spreadsheet" gives a specific verb plus resource and enumerates the two input shapes, so an agent knows exactly what the tool produces. It does not name or contrast any sibling, but no sibling in the list performs export, so confusion risk is low.

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?

The description implicitly routes the agent between the two modes (tables for arbitrary data, customer_id+gaql for Google Ads rows) and between the two destinations (own Drive vs. spreadsheet_id for an AdCopilot-made sheet). It gives no explicit when-not or upstream prerequisite, and does not say whether tables and gaql may be combined.

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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