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Skriv i formulärfält

fill_input
Idempotent

Skriver i ett formulärfält i steg 1, som när användaren skriver.

Använd i steg 1 när bolaget fylls i utan SIE-fil (manuell inmatning): sök bolag på namn eller organisationsnummer, och ange räkenskapsårets datum. Vilka fält som finns står i snapshot.inputs (get_state). För steg 2 till 6, använd update_fields. Tryck sedan på de knappar som behövs (t.ex. hämta företagsuppgifter) med press_button.

Returnerar filled, value och snapshot efteråt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelYesFältets etikett exakt som i snapshot.inputs[].label (steg 1), t.ex. 'Räkenskapsår från'.
valueYesVärdet som skrivs i fältet, som användaren skulle skriva det. Organisationsnummer som NNNNNN-NNNN (t.ex. 559515-1589), datum som ÅÅÅÅ-MM-DD.
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 already declare readOnlyHint=false, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds value by describing the interaction model ('as when the user writes'), the discovery prerequisite via get_state, and the post-call action. It falls short of a 5 only because it doesn't state failure modes or permission requirements.

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?

Purpose is front-loaded in one line, followed by a compact workflow paragraph and a one-line return statement. Every sentence carries routing or prerequisite information; only the trailing return sentence is somewhat redundant given it could be inferred.

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

Completeness5/5

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

There is no output schema, yet the description names the return payload (filled, value, snapshot), so an agent knows what comes back. Combined with the prerequisite pointer to get_state and the follow-up press_button step, nothing needed to call this correctly is missing.

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 the schema already explains label, value and draft_id in detail, including format examples (NNNNNN-NNNN, ÅÅÅÅ-MM-DD). The description reinforces the field-discovery path but adds no syntax or constraint beyond the schema, 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 (skriver) and resource (formulärfält) scoped to step 1, and explicitly separates itself from update_fields which handles steps 2-6. An agent can distinguish this from every sibling without opening the 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?

Names the exact condition for use (step 1, manual company entry without a SIE file), tells the agent where to find valid fields (snapshot.inputs via get_state), routes steps 2-6 to update_fields, and names the follow-up tool (press_button). When-to-use, alternatives, and sequencing are all explicit.

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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