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Ania

by solutions.diatech
OverviewDiscussionsAdmin

Approve a movement

approve_movement

Approves one movement preview (e.g. waving) after the user saw it and liked it. Ania asks the user (confirmation form); without one, the tool returns the question: ask it and call again with user_confirmed: true only after an explicit yes. Never decide for the user.

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": {
      "jobId": "<jobId>",
      "state": "<state>"
    },
    "name": "approve_movement"
  }
}

Input Schema

NameRequiredDescriptionDefault
jobIdYesThe job id from criar_avatar or ver_andamento.
stateYesState id as listed by ver_andamento.
languageNoThe user's language as a BCP-47 tag (e.g. 'en', 'en-US', 'pt-BR', 'es'). Replies and prices follow it.
user_confirmedNoOnly without a confirmation prompt: true only after the user explicitly said yes.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already establish a non-read-only, non-destructive, closed-world mutation. The description adds important behavior beyond annotations: approval requires explicit user confirmation and the tool can return a question instead of performing the action. It still does not describe the full effect of approval or the success response, so 4 rather than 5.

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?

Front-loaded and compact, with no filler sentences. The middle sentence is slightly dense with punctuation but remains readable and every clause carries useful instruction.

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?

Covers purpose, confirmation workflow, and retry condition for a four-parameter mutation. With no output schema, it mentions that the tool may return the question but does not outline the success response or effects of approval, which is a minor gap.

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?

Schema coverage is 100%, so the baseline would be 3. The description adds meaning for user_confirmed beyond the schema: it must be true only after an explicit yes, and the confirmation loop explains why. The other parameters remain adequately covered by 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?

Names a specific verb and resource ('Approves one movement preview') and adds scope ('e.g. waving') that distinguishes it from image approval and other sibling actions. It is more than a restatement of the title.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states the precondition (the user saw and liked the preview), the fallback when no confirmation form exists (return the question, ask it, retry with user_confirmed true only after an explicit yes), and the prohibition (never decide for the user). This is clear when-to-use and when-not guidance.

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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