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Append rows to a sheet

append_google_sheet_rows

Add rows after the last row that holds data — the usual way to add records to a tracker. Values are interpreted as if typed, so numbers and dates parse and a value starting with = becomes a live formula; pass valueInput RAW to store text exactly as given.

Input Schema

NameRequiredDescriptionDefault
rangeYesThe tab or table to append to, e.g. "Invoices" or "Invoices!A:E"
valuesYesRows of cell values
mailboxYesEmail address of the connected Gmail/Google Workspace mailbox to act on. Call list_authorized_mailboxes to see available options.
valueInputNo
spreadsheetIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare the non-read-only, non-destructive, closed-world profile, so the description goes further by disclosing the value-coercion behavior: numbers and dates parse and a leading '=' becomes a live formula. That is genuine behavioral context beyond structured data, though the response shape (rows appended, range written) is not mentioned.

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?

Two sentences with zero filler; the core append semantics come first and the value-interpretation caveat follows. Every clause carries actionable information.

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 5-parameter mutation tool with no output schema, the definition covers placement, value interpretation, and the RAW escape hatch, and the mailbox parameter routes to list_authorized_mailboxes. Only the result payload and the fact that pre-existing rows are untouched are left implicit.

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?

Schema coverage is 60% and the valueInput enum has no schema description, but the description compensates by explaining that values are parsed as if typed and that RAW stores text exactly as given — meaningful semantics the schema omits. The undocumented spreadsheetId is largely self-evident, and mailbox/range are covered in the schema.

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?

States a specific verb and resource with positional semantics ('add rows after the last row that holds data'), which cleanly separates it from the overwriting update_google_sheet_range sibling. It never names the alternative tool outright, so an agent must infer the append-vs-update distinction.

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 usual way to add records to a tracker' implies the intended use case, and the value-input guidance hints at the RAW alternative. However, no sibling tool is named and no explicit when-not-to-use condition (e.g., use update_google_sheet_range to modify existing cells) is given.

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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