Open Legal Data (Germany)

Find similar court decisions

get_similar_cases

Read-onlyIdempotent

Find court cases textually similar to a given case.

    Seeds an Elasticsearch "more like this" query with the full text of
    the given case and returns the most similar OTHER cases, ranked by
    similarity. Useful for comparative research: once you have one
    on-point decision, surface neighbouring case law without crafting a
    keyword query. For keyword- or citation-scoped neighbours instead,
    use search_cases.

    Args:
        case_id: The database ID of the seed case.
        limit: Maximum results (default 10, 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_similar_cases"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`case_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), yet the description still adds real value: the MLT retrieval mechanism, similarity ranking, exclusion of the seed case itself, and the limit-clamping behavior with the returned 'limit_clamped' and 'requested_limit' flags. It does not describe the shape of an individual result, which keeps it short of a 5.

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 the purpose, then usage routing, then parameters — a sensible order with no filler sentences. The docstring-style 'Args:' block is slightly more verbose in presentation than a compact prose sentence would be, but every line still carries information.

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 tool with no output schema, the definition covers purpose, routing, the retrieval mechanism, and the clamping edge case including the response flags that surface it. The only gap is that it never sketches what a returned case record contains, which matters somewhat given no output schema exists.

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: case_id is identified as the database ID of the seed case, and limit gets a default (10), a hard maximum (50), and the clamping semantics plus the response fields that signal clamping. That is meaning well beyond the bare 'integer / Limit / default 10' in the schema.

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 court cases textually similar to a given case') and immediately clarifies the mechanism: it seeds an Elasticsearch 'more like this' query with the seed case's full text and returns similar OTHER cases. The word 'OTHER' plus the explicit contrast with search_cases makes it distinguishable from every sibling without opening a 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?

Gives a concrete when-to-use scenario ('once you have one on-point decision, surface neighbouring case law without crafting a keyword query') and an explicit alternative with its selecting condition ('For keyword- or citation-scoped neighbours instead, use search_cases'). Nothing about routing is left to inference.

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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