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SheetForge MCP

SheetForge MCP

by iHeldan
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

inspect_formula

Read-only

Analyze a formula string to identify functions, cell references, and risky patterns before applying changes.

Instructions

Inspect a formula string for functions, references, and risky signals.

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": {
      "formula": "<formula>"
    },
    "name": "inspect_formula"
  }
}

Input Schema

NameRequiredDescriptionDefault
formulaYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.0

TDQS

A3.6/5.0
Behavior3/5

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

The description adds some context beyond the readOnlyHint annotation by specifying what is inspected, but it does not disclose what the output looks like, what counts as a 'risky signal', or how errors are handled. The annotation already covers safety, and the description adds a modest layer of behavioral context.

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 sentence, front-loaded with the action and object, and contains no redundant words. It is appropriately short and to the point.

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

Completeness3/5

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

For a simple one-parameter, read-only tool, the description gives a basic understanding of the tool's function. However, the lack of an output schema and the vague term 'risky signals' leave gaps about the return format and the precise nature of the analysis, so it is not fully complete.

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

Parameters2/5

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

The schema has no description for the 'formula' parameter (0% coverage), so the description must compensate. However, it only states 'formula string', which essentially repeats the parameter name and type without adding format examples or acceptable values. This adds minimal semantic value.

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 the specific verb 'Inspect' and the resource 'a formula string', and enumerates what is examined: 'functions, references, and risky signals'. This distinguishes it from siblings like validate_formula_syntax and apply_formula, making the purpose unambiguous.

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 when to use the tool—when you need to analyze a formula for functions, references, and risky signals—but it does not provide explicit context about when not to use it or mention alternative tools. The use case is inferable but not explicitly delineated.

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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