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taylorwilsdon

Google Workspace MCP Server - Control Gmail, Calendar, Docs, Sheets, Slides, Chat, Forms & Drive

Debug Table Structure

debug_table_structure
Read-onlyIdempotent

Inspect Google Docs table dimensions, cell positions, content, and insertion indices to fix misplaced data, 'table not found' errors, and plan table population.

Instructions

ESSENTIAL DEBUGGING TOOL - Use this whenever tables don't work as expected.

USE THIS IMMEDIATELY WHEN:

  • Table population put data in wrong cells

  • You get "table not found" errors

  • Data appears concatenated in first cell

  • Need to understand existing table structure

  • Planning to use populate_existing_table

WHAT THIS SHOWS YOU:

  • Exact table dimensions (rows × columns)

  • Each cell's position coordinates (row,col)

  • Current content in each cell

  • Insertion indices for each cell

  • Table boundaries and ranges

HOW TO READ THE OUTPUT:

  • "dimensions": "2x3" = 2 rows, 3 columns

  • "position": "(0,0)" = first row, first column

  • "current_content": What's actually in each cell right now

  • "insertion_index": Where new text would be inserted in that cell

WORKFLOW INTEGRATION:

  1. After creating table → Use this to verify structure

  2. Before populating → Use this to plan your data format

  3. After population fails → Use this to see what went wrong

  4. When debugging → Compare your data array to actual table structure

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
document_idYesID of the document to inspect
table_indexNoWhich table to debug (0 = first table, 1 = second table, etc.)
user_google_emailYesUser's Google email address

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds substantial context about what the tool reveals: exact dimensions, cell coordinates, current content, and insertion indices. It also explains how to read the output, going well beyond the structured annotation data.

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 description is long but well-structured with clear sections and bullet lists. It is front-loaded with the 'ESSENTIAL' tag and immediate use cases. While somewhat verbose, every section provides value for debugging scenarios.

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

Completeness5/5

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

Given the tool's moderate complexity, the description covers when to use it, what to expect in the output, and how to interpret that output. It also aligns with the output schema, making it a complete guide for the agent.

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?

The input schema provides complete descriptions for all three parameters (100% coverage), including the meaning of table_index and user_google_email. The tool description does not add new parameter-level semantics beyond the schema, but the schema alone is sufficient.

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?

The description clearly states this is a debugging tool for table structure, with concrete use cases like 'table not found' errors and mispopulated cells. It distinguishes itself from general inspection tools by focusing on table dimensions, positions, and insertion indices.

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 provides explicit when-to-use scenarios ('USE THIS IMMEDIATELY WHEN:') and workflow integration steps. However, it does not mention when not to use it or explicitly compare against sibling tools like inspect_doc_structure, so it falls short of the highest score.

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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