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Mizar-Contasti

Treeflow MCP Server

treeflow_create_leaf

Create a new node within a branch of a chatbot flow. Choose from supported leaf types—message, input, condition, action, webhook, or trigger context—to extend the conversation logic.

Instructions

Crea un nuevo nodo (leaf) dentro de una rama. Tipos soportados: message, input, condition, action, webhook, trigger_context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
configNoConfiguración JSON del nodo (ej. plantilla de mensaje, opciones, condiciones)
branch_idYesID de la rama
leaf_typeYesTipo de nodo: message, input, condition, action, webhook, trigger_context
canvas_positionNoPosición x, y en el lienzo { x: number, y: number }
Install Server

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It reveals that the operation creates a new node, but it does not disclose side effects, prerequisites like existence of the branch, validation behavior, or return/error semantics. For a mutating tool this is a noticeable gap beyond the basic create action.

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 concise sentence that front-loads the core operation and the list of supported types. There is no filler or redundant content that detracts from clarity.

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?

The schema already documents all parameters, and the description establishes the core purpose and supported types. However, with no output schema and no behavioral annotations, the agent is left to guess about return values, errors, or any side effects. This is moderately complete for a simple create operation but misses some operational context.

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

Parameters3/5

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

The input schema provides descriptions for all four parameters, giving 100% schema coverage, so the baseline is 3. The description only repeats the leaf_type values already present in the schema and adds no extra meaning for config or canvas_position. It does not compensate beyond the schema.

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 states a specific action ('rea un novevo nodo') and a specific resource ('leaf dentro de una rama'), and it lists supported leaf types. This clearly distinguishes it from sibling tools like create_branch, update_leaf, or delete_leaf. An agent can understand exactly what the tool does witout opening the schema.

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 purpose statement makes it clear that this tool is for creating a new leaf node inside a branch, so its usage context is implied. However, it does not explicitly contrast it with alternatives such as update_leaf or list_leafs, and it does not mention when not to use it. The guidance is adequate but left to inference.

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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