Skip to main content
Glama

wattpad_post_comment

Post a comment on a Wattpad chapter using your authenticated account. Provide the chapter ID and comment text to publish it publicly, with an optional dry-run mode to simulate the request.

Instructions

Publica un comentario en un capitulo con la cuenta autenticada.

EXPERIMENTAL y visible publicamente de inmediato; confirme el texto con la persona antes de enviarlo. Este endpoint NO se capturo del editor: sigue sin verificar.

Returns: str: JSON con el comentario creado o la peticion simulada.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesTexto del comentario.
dry_runNoDevuelve la peticion sin enviarla.
part_idYesID del capitulo donde comentar.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.9/5.0
Behavior4/5

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

The description goes beyond annotations by revealing that the comment is publicly visible immediately, that the endpoint is experimental and not captured from the editor, and that it returns either the created comment or the simulated request (for dry_run). Annotations only indicate readOnlyHint false, destructiveHint false, etc. This additional context is valuable for the agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with the main action stated first, followed by important warnings and the return type. It is well-structured and does not contain unnecessary verbosity, though the warnings add a few sentences that are all relevant.

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?

Given the tool's simplicity (3 parameters, output schema present), the description covers the essential purpose, behavioral warnings, and return type. It does not detail how to obtain part_id, but that is likely handled by other tools. Overall, it provides sufficient information for an agent to call it correctly.

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?

All three parameters are fully described in the input schema (text has length limits, dry_run explains behavior, part_id specifies chapter ID). The description adds no additional parameter meaning beyond what the schema already provides. Since schema coverage is 100%, a baseline of 3 is appropriate.

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 action: 'Publica un comentario en un capitulo' (post a comment on a chapter) with the authenticated account. This distinguishes it from sibling tools like wattpad_list_comments, which reads comments. The purpose is unambiguous and specific.

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 provides cautionary guidance, such as confirming text with the person before sending and warning that the endpoint is experimental and unverified. However, it does not explicitly state when to use this tool versus alternatives (e.g., wattpad_list_comments for reading), nor does it provide when-not-to-use conditions. The guidance is more about caution than usage selection.

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