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list_courts_in_state

List all courts (Amtsgerichte) in a specific German state with auction counts.

    Args:
        land: State abbreviation (e.g. 'by' for Bayern, 'nw' for Nordrhein-Westfalen,
              'he' for Hessen, 'rp' for Rheinland-Pfalz, 'ni' for Niedersachsen,
              'be' for Berlin, 'br' for Brandenburg, 'sn' for Sachsen,
              'st' for Sachsen-Anhalt, 'th' for Thüringen, 'sh' for Schleswig-Holstein,
              'hh' for Hamburg, 'hb' for Bremen, 'sl' for Saarland, 'mv' for Mecklenburg-Vorpommern)
    

Input Schema

NameRequiredDescriptionDefault
landYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. It does add real value by revealing the return payload includes auction counts, and the 'List' verb signals a read-only operation. It does not state error behavior for an invalid or unknown state abbreviation, nor whether counts are current or cached.

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?

The summary sentence is front-loaded and the Args block follows in the conventional place. The 16-item abbreviation list is long but each entry earns its place given the empty schema; only the parenthetical glosses on the first five states are mild redundancy.

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?

This is a single-parameter read tool with an output schema, so return-value documentation is correctly omitted. The one thing an agent could get wrong — the state identifier format — is fully specified, leaving no material gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate entirely and it does: it enumerates every accepted abbreviation (by, nw, he, rp, ni, be, br, sn, st, th, sh, hh, hb, sl, mv) with a worked example for the first few. An agent can construct a valid call without guessing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource+scope: 'List all courts (Amtsgerichte) in a specific German state with auction counts.' It distinguishes itself from list_federal_states by operating one level deeper (courts within a state), though it does not explicitly name that sibling or the parent-child relationship between the two.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: the agent can infer this is the drill-down after picking a state, but the description never says 'call list_federal_states first to obtain valid abbreviations' nor when to prefer search_auctions instead. With five siblings in the namespace, an explicit routing sentence is missing.

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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