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SarthakS97

sheetsdb-mcp-server

by SarthakS97

smart_add_data

Checks existing headers first, then adds data to Google Sheets as JSON import or new rows based on header presence.

Instructions

Step 1: ALWAYS call get_keys first to check headers. Step 2: Based on keys result, either import_json (no headers) or create rows (has headers). This tool requires get_keys to be called first in the same conversation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
headersYesHeaders obtained from get_keys tool - REQUIRED parameter from previous get_keys call
endpointYesThe SheetsDB API endpoint
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It mentions the dependency on get_keys and the conditional use of import_json or create_rows, but does not describe side effects, output, error behavior, or what happens if get_keys is not called. The transparency is minimal and does not meet the burden.

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 three concise sentences with a clear numbered step structure. It front-loads the critical prerequisite ('ALWAYS call get_keys first') and every sentence contributes to usage guidance. No wasted words.

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

Completeness2/5

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

Despite having no output schema and no annotations, the description does not explain what smart_add_data returns or how it executes the add operation. It over-relies on sibling tool names and does not fully describe the tool's own behavior, leaving significant gaps for an agent to invoke it correctly.

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 67% and the schema provides solid descriptions for data, headers, and endpoint, including the source of headers from get_keys. The description adds no additional parameter details, but the schema largely covers semantics, so a baseline score of 3 is appropriate.

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

Purpose3/5

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

The description focuses on a two-step workflow involving get_keys and choosing between import_json or create_rows, but never explicitly states that smart_add_data itself adds data to the endpoint. The purpose is implied as a smart router, but the verb+resource is not clearly articulated, making it vague rather than tautological.

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?

Provides explicit usage instructions: 'ALWAYS call get_keys first' and 'requires get_keys to be called first in the same conversation.' It clearly distinguishes when to use import_json (no headers) vs create_rows (has headers), naming the exact alternatives and the decision condition. This fully guides tool selection.

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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