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joiva_answer_question

DestructiveIdempotent

Answer one open recipe question with the option index the user chose, or ignore=true when the user does not want to answer (the standard then stays, visibly). The answer becomes the user's personal recipe for that dish, the user's entries of the dish are recomputed, and Joiva does not ask about that dish again.

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": {
      "questionId": "<questionId>"
    },
    "name": "joiva_answer_question"
  }
}

Input Schema

NameRequiredDescriptionDefault
ignoreNotrue = keep the standard, do not ask again
optionNoIndex into `optionen`
questionIdYesId of the open question

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / questionId / description
      Previous value: -"`id` from joiva_list_open_questions"New value: +"Id of the open question"
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Beyond the annotations it discloses real consequences: the answer becomes the user's personal recipe, the user's entries for that dish are recomputed, and the question will not be asked again. That is consistent with destructiveHint=true and adds meaningful side-effect context, though reversibility of the recomputation is not addressed.

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?

Two sentences, no filler, with the action and the alternative mode front-loaded. The second sentence is dense with three distinct effects, but each carries information an agent needs.

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?

With no output schema, the description carries the burden of stating outcomes and it does so for the main effects. It is nearly complete for a three-parameter tool; only the source of questionId and any failure behavior are unaddressed.

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 is 3, but the description adds interpretation: 'option' is the index the user chose, and 'ignore' means the standard stays and is 'visibly' retained. The questionId parameter is left entirely to 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 opens with a specific verb and resource ('Answer one open recipe question') and immediately names the two input modes (option index or ignore=true). An agent can tell this apart from the sibling joiva_list_open_questions, which only enumerates questions rather than resolving one.

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

Usage Guidelines4/5

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

It clearly states the two situations that select each mode: supply the chosen option index, or ignore=true when the user declines. What it does not say is where a questionId comes from (presumably joiva_list_open_questions), leaving the prerequisite implicit.

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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