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Open Legal Data (Germany)

by io.openlegaldata
OverviewDiscussionsAdmin

Find decisions citing a decision

get_citing_cases
Read-onlyIdempotent

Get reverse references TO a case (cases that cite this case).

    Find all cases that reference the given case in their text.
    Useful for understanding the impact and precedent value of a
    decision. To narrow the citing set by keyword, court, or date,
    use ``search_cases(query=..., cited_case_id=case_id)`` instead.

    Args:
        case_id: The database ID of the cited case.
        sort: "date" (default, newest first) or "most_cited" (the most
            influential citing cases 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

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "case_id": "<case_id>"
    },
    "name": "get_citing_cases"
  }
}

Input Schema

NameRequiredDescriptionDefault
sortNodate
limitNo
case_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the description's job is to add context. It does so with sort semantics (newest first vs most influential) and the limit clamping behavior including the limit_clamped and requested_limit response fields. It stops short of describing the shape of returned citing cases, which is a minor remaining gap.

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 opening sentence is front-loaded and the alternative-tool routing follows immediately, with parameters documented in a clean Args block. There is slight redundancy between 'Get reverse references TO a case' and 'Find all cases that reference the given case', but every part remains useful.

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?

With no output schema, the description should say enough about returns, and it covers ordering, defaults, caps, and the clamping flags. What it does not describe is the fields of each citing case, though for a simple three-parameter read tool this is a modest gap rather than a blocking one.

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 carry all parameter meaning, and it does: case_id is the database ID of the cited case, sort enumerates 'date' vs 'most_cited' with ordering semantics, and limit documents default 20, max 50, and clamping behavior. This is materially more than the bare schema types provide.

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 states a specific verb and resource: 'Get reverse references TO a case (cases that cite this case)', then reinforces it with 'Find all cases that reference the given case in their text.' This clearly distinguishes the tool from forward-reference siblings like get_case_references and from keyword search.

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?

It gives an explicit use case ('understanding the impact and precedent value of a decision') and names the exact alternative for narrowing results: search_cases(query=..., cited_case_id=case_id). The when-to-use-this vs when-to-use-the-sibling boundary is fully spelled out.

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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