aeza-mcp

support_gpt_send_message

Destructive

Sends a support message to GPT so an AI agent can request help with Aeza support tasks.

Instructions

Send message to gpt POST /support/gpt

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "body": "<body>"
    },
    "name": "support_gpt_send_message"
  }
}

Input Schema

Name	Required	Description	Default
`body`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Nov 13, 2026

TDQS

C2.1/5.0

Behavior2/5

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

Annotations already declare destructiveHint=true, openWorldHint=true, non-idempotent, and non-read-only, so the agent knows this is a risky write. The description adds nothing beyond those flags — no indication of what the message affects, whether it triggers an external GPT call with side effects, or what auth/rate constraints apply. For a destructive, open-world mutation the description is nearly silent.

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

Conciseness3/5

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

It is short and front-loaded, but that is under-specification rather than real conciseness. The second line (HTTP verb and path) consumes space without helping an agent decide or invoke the tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a destructive, open-world, non-idempotent tool with a nested parameter at 0% schema coverage and no output schema, the description covers almost none of what an agent needs. It omits the purpose of the GPT endpoint, expected input shape, and any consequence of sending a message.

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

Parameters2/5

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

Schema description coverage is 0%, and the single parameter is an awkward nested object (body.body as a 3–512 character string). The description does not explain what content belongs in that body, whether it is a prompt, a chat message, or structured JSON, leaving the agent to infer the 512-character limit's implications.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Send message to gpt" essentially restates the tool name (support_gpt_send_message) rather than describing what the operation actually accomplishes in the support domain. The only extra content is the raw HTTP path "POST /support/gpt", which is an implementation detail, not a purpose statement. Nothing distinguishes it from siblings like support_send_message or services_send_command.

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?

The description contains no when-to-use guidance, no preconditions, and no mention of when a different sibling tool would be the right choice. An agent must guess whether this targets an AI assistant, a human agent, or an external GPT service.

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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