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lucaszarzur

CherryTree MCP Server

by lucaszarzur

read_node

Retrieves a CherryTree node's content by ID or partial name, optionally returning formatting and widget details such as codeboxes, images, tables, and anchors.

Instructions

Read content of a CherryTree node.

Args: node_id: Node unique ID (preferred). node_name: Search by name (partial, case-insensitive). include_formatting: Return rich-text segment details. include_widgets: Return codebox/image/table/anchor details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
node_idNo
node_nameNo
include_widgetsNo
include_formattingNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. 'Read' and 'Return ... details' signal a non-mutating lookup and the include_* flags describe what extra content comes back, but the description does not specify precedence when both node_id and node_name are supplied, behavior for multiple name matches, or what happens when no node is found.

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 compact and front-loaded, with a one-sentence purpose followed by a tight argument list. Every line adds information that is not otherwise present in the schema.

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?

For a read tool with four optional parameters, an output schema removes the need to describe return structure, and all arguments are semantically covered. The main gaps are minor interaction rules: what happens if both node_id and node_name are provided, and whether node_name matching returns one node or multiple.

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

Parameters5/5

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

Schema description coverage is 0%, and the description compensates fully by explaining each parameter: node_id is the preferred unique ID, node_name is a partial case-insensitive search, include_formatting controls rich-text segment details, and include_widgets names the widget types included. This adds real meaning beyond the bare schema types and defaults.

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 opens with a specific verb and resource: 'Read content of a CherryTree node.' That wording distinguishes read_node from sibling tools such as list_nodes and search_nodes by focusing on content retrieval rather than listing or searching.

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 read-only purpose is clear from the verb, so an agent can infer when to use it over mutating siblings, but the description gives no explicit when to use/when not to use guidance and does not point to list_nodes or search_nodes for locating nodes by other criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.