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figma-slides-mcp

figma-slides-mcp

by luan007
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

Get Cell Content

get_cell_content

Retrieve the text content from a specific cell in a Figma Slides table by providing the table ID, row, and column numbers.

Instructions

Read text of a table cell

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": {
      "tableId": "<tableId>",
      "row": "<row>",
      "col": "<col>"
    },
    "name": "get_cell_content"
  }
}

Input Schema

NameRequiredDescriptionDefault
colYes
rowYes
tableIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. This description only states the basic operation and does not disclose return format, error handling, or edge cases like out-of-bounds coordinates. It adds no behavioral context beyond what the tool name already suggests.

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 a single, front-loaded sentence with no unnecessary words. It is concise and easy to parse, appropriately sized for the simplicity of the tool.

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?

Given the tool has three required parameters, no annotations, and no output schema, the description is too sparse to be complete. It fails to explain parameter semantics, return values, or usage context, leaving significant gaps that could confuse an agent attempting to invoke the tool correctly.

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

Parameters1/5

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

Schema description coverage is 0%, so the description is responsible for compensating, but it does not explain any parameters. It does not clarify whether row/col are zero-indexed, what format tableId expects, or what the return value looks like. This leaves the agent without meaningful parameter guidance.

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 'Read text of a table cell' uses a specific verb (read) and resource (table cell), making it clear what the tool does. It also distinguishes itself from the sibling 'set_cell_content' by clearly indicating a read operation rather than a write operation.

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 description implies usage when you need to read text from a cell, but it does not explicitly state when to use this tool over alternatives, nor does it provide exclusions. It is a self-contained read operation, but there is no mention of alternatives or when-not-to-use, so it relies on implication.

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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