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NeuralVerge

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by neuralverge
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TypeScript
Hybrid

run_capterra_categories

Lists Capterra software categories with name, alias, and canonical URL, helping agents retrieve structured category data for software research.

Instructions

List Capterra software categories: name, alias, and canonical URL. Flat 5 points per successful run.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "run_capterra_categories"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.1

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose pricing behavior ('Flat 5 points per successful run'), which is real value beyond the schema, but says nothing about pagination, completeness of the category list, or error behavior on a failed run.

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 short sentences, zero waste, with the resource and returned fields front-loaded and the cost note appended. Nothing to trim.

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?

With no output schema, the description steps in to name the returned fields (name, alias, canonical URL) plus the cost, which is what an agent needs for a zero-parameter listing call. Minor gaps remain around pagination and whether the list is exhaustive.

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?

The tool takes zero parameters, so the baseline of 4 applies; there is no parameter semantics to document and the description correctly avoids inventing any.

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 ('List Capterra software categories') and even names the returned fields (name, alias, canonical URL). An agent can distinguish it from Capterra siblings like run_capterra_category_products or run_capterra_products_search, though the description never explicitly contrasts with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance, no prerequisites, and no mention of the obvious alternative (run_capterra_category_products) for drilling into a category. The catalog-enumeration use case is only implied by the noun 'categories', not stated.

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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