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Svara på fråga i guiden

answer_prompt

Svarar på en dialog som guiden visar, genom att trycka på samma knapp som användaren skulle.

Använd bara för de frågor som get_state och next_step returnerar i prompts, till exempel förifyllning från förra året, bekräftelse av en liten avvikelse eller en påminnelse. Frågor i själva formuläret besvaras inte här: steg 1 med set_first_annual_report, steg 3 till 6 med update_fields. Förklara alltid frågan för användaren och få ett uttryckligt svar innan du svarar åt hen.

Returnerar clicked (knappens text), och snapshot efter svaret.

Input Schema

NameRequiredDescriptionDefault
inputsNoValfritt: värden för fälten i frågan (snapshot.prompts[].inputs) som fylls i innan knappen trycks, t.ex. {"Insatt aktiekapital (kr)": "25000"}. Fråga användaren om värdet.
optionYesExakt text på svarsalternativet (knappen) från snapshot.prompts[].options, t.ex. 'Nej tack'.
promptNoValfritt: rubriken på frågan (snapshot.prompts[].title) om samma knapptext finns i flera frågor.
draft_idYesUtkastets id (draft_id), t.ex. från list_drafts. Utkastet måste tillhöra det anslutna kontot.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false, idempotentHint=false, openWorldHint=false and destructiveHint=false, so the write/non-idempotent profile is covered structurally. The description adds real value beyond that: it explains the mechanism (simulating a button press), the required user-consent step, and names the return values (clicked and a snapshot) despite there being no output schema.

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?

Four compact sentences, front-loaded with purpose, then boundaries, then the consent rule, then the return. Each sentence carries distinct information; nothing is repeated or filler.

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?

For a mutation tool with no output schema, the description supplies both the return shape (clicked text plus snapshot) and the alternative routing for form questions. It stops short of covering edge cases such as a mismatched option or duplicate button labels beyond the `prompt` hint, so it is strong but not exhaustive.

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?

Schema description coverage is 100%, so every parameter (option, prompt, inputs, draft_id) is already well documented in the schema, including examples. The description adds only indirect context (`förifyllning från förra året` as a typical prompt type), so the baseline 3 applies.

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?

States a specific verb+resource: it answers a dialog shown by the guide by pressing the same button the user would. It further distinguishes itself from siblings by naming what it is NOT for (form questions handled by set_first_annual_report and update_fields). An agent can route correctly without opening any other schema.

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?

Explicit when-to-use (only prompts returned by get_state and next_step, e.g. prefill from last year, small deviation confirmation, reminder), when-not (form questions: step 1 via set_first_annual_report, steps 3-6 via update_fields), and an operational rule to always explain the question and obtain an explicit user answer first.

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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