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Glama

elster_edaten_fetch

Retrieves the pre-filled ELSTER tax data (eDaten) for a given tax year by walking the ESt form to the import step and reading values back without saving or transmitting anything.

Instructions

Retrieves the pre-filled tax data ("vorausgefüllte Steuererklärung" / eDaten) the tax authority already holds for a year: Lohnsteuerbescheinigung, Vorsorgeaufwendungen, Lohnersatzleistungen, Riester/Rürup. ELSTER only exposes these from inside the ESt form, so this walks the form up to the import step and reads the values back. The form is left without saving, so no draft is kept (ELSTER may offer it for recovery at the next login). Nothing is ever transmitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesTax year to retrieve.
anlagenNoCheckbox ids on the Anlagenauswahl page. Defaults to Hauptvordruck + Anlage N + Anlage Vorsorgeaufwand, which is what eDaten fills. Exact ids, e.g. "VAnlageN", "VAnlageG", "VAnlageKAP".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it discloses that the form is left unsaved, no draft is kept, ELSTER may offer it for recovery at next login, and nothing is ever transmitted. It still doesn't state session/login prerequisites or expected runtime, so it is not fully complete.

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?

Front-loaded with the resource and its German name, then the mechanism, then the side-effect caveats. Every sentence earns its place and nothing is redundant.

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 two-parameter read operation with no output schema and no annotations, the description covers purpose, mechanism, side effects, and the categories of data returned. It does not sketch the exact return shape or error conditions, but it is close to complete.

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 both parameters (year, anlagen) are already documented in the schema, including the default anlagen set and id examples. The description adds no parameter-level meaning beyond that, 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?

The description gives a specific verb (retrieves), a precisely named resource (pre-filled tax data / vorausgefüllte Steuererklärung / eDaten), and enumerates the exact data categories returned (Lohnsteuerbescheinigung, Vorsorgeaufwendungen, Lohnersatzleistungen, Riester/Rürup). It is clearly distinguishable from siblings like elster_drafts_list or elster_datenuebernahme_list.

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 explains when this tool is needed by describing the constraint that forces it: ELSTER only exposes eDaten from inside the ESt form, so the tool walks the form to the import step. It gives clear context but never explicitly names an alternative tool or a when-not-to-use condition, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.