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Open Legal Data (Germany)

Find decisions citing a law

get_cases_for_law
Read-onlyIdempotent

Find all cases that cite a specific law section.

    Returns cases that reference the given statute section in their
    text. Useful for understanding how courts interpret a specific
    provision. To narrow the citing set by keyword, court, or date,
    use ``search_cases(query=..., cited_law_book=..., cited_law_section=...)``
    instead.

    Args:
        book_code: Law book code (e.g. "BGB", "StGB").
        section: Section identifier (e.g. "823").
        law_id: Direct law database ID (alternative to book_code+section).
        sort: "date" (default, newest first) or "most_cited" — the
            latter surfaces the landmark decisions interpreting this
            provision (most-cited first).
        limit: Maximum results (default 20, max 50). Values above 50 are
            clamped; the response then includes ``limit_clamped: true``
            and the original ``requested_limit``.
    

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_cases_for_law"
  }
}

Input Schema

NameRequiredDescriptionDefault
sortNodate
limitNo
law_idNo
sectionNo
book_codeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive behavior, so the description focuses on what those don't cover: sort ordering semantics ('newest first' vs 'most_cited'), clamping above 50, and the `limit_clamped`/`requested_limit` response fields. It stops short of describing the overall result shape or total-result behavior, but adds real value beyond the annotations.

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?

Front-loaded with purpose, then the alternative routing, then structured Args. The one soft sentence ('Useful for understanding how courts interpret...') is arguably filler, and the Args block mirrors schema field names, but overall there is little waste.

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?

With no output schema and zero schema coverage, the description supplies the parameter definitions, the fallback routing to a sibling, and the clamp/response-field behavior an agent needs to interpret results. Remaining gaps (case object fields, precedence between law_id and book_code+section) are minor for a single-purpose lookup.

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 carries the full burden and does so: it defines book_code, section, law_id (as an alternative to book_code+section), sort with its two modes and defaults, and limit with default, max, and clamp behavior.

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 and resource ('Find all cases that cite a specific law section') and clarifies scope as citations appearing in case text. This distinguishes it from 'get_citing_cases' and 'search_cases' without needing to open either 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?

Explicitly names the alternative ('search_cases') and the exact condition that selects it (narrowing by keyword, court, or date), even showing the relevant argument names. Nothing is left to inference about when to prefer the other tool.

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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