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Carbone MCP

Carbone MCP

Official
by carboneio
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TypeScript
Hybrid

List Categories

list_categories
Read-onlyIdempotent

Retrieve all template categories in your Carbone account to organize templates and use their names as filters when listing or uploading.

Instructions

List all template categories currently in use in your Carbone account. Categories act like folders for organising templates (e.g. "invoices", "legal", "hr"). Use the returned names as the category filter in list_templates or upload_template.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
categoriesYesTemplate category names in use.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.0.0
    • changedOutput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Changed1 schema field changedv1.2.2
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "categories": {
+      "description": "Template category names in use.",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "categories"
+  ],
+  "type": "object"
+}
  3. First observedv1.1.2

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare this as a read-only, idempotent, non-destructive, closed-world operation, so the safety profile is covered. The description adds genuine domain context beyond that — categories behave like folders, with concrete examples ('invoices', 'legal', 'hr') — though it says nothing about auth requirements or result size.

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?

Three short sentences, each earning its place: what the tool returns, what a category conceptually is, and how to consume the output. The purpose is front-loaded with no preamble.

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?

An output schema exists, so return-value documentation is unnecessary, and the description still explains how to use the returned names. For a zero-argument list tool with full annotations, nothing an agent needs is missing.

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 there is nothing for the description to disambiguate; the baseline for a parameterless tool is 4.

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?

States a specific verb and resource ('List all template categories') and scopes it to the caller's Carbone account. It is clearly distinguishable from siblings like list_templates and list_tags because it names the domain object it enumerates.

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?

Explicitly routes the agent forward: 'Use the returned names as the category filter in list_templates or upload_template,' naming the downstream tools. It lacks an explicit when-not-to-use condition, but the usage context is unambiguous.

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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