Open Legal Data (Germany)

Send feedback to OLDP

submit_feedback

Send feedback about OLDP or this MCP server to the OLDP team.

    Use this to report bugs (wrong results, errors, broken tools),
    problems with the legal data (missing or wrong decisions, laws or
    references), or to request features. Only submit feedback the user
    wants to send or has agreed to; do not include personal data or
    confidential case details. Requires a signed-in connection (OAuth or
    API token); anonymous calls return an error with a sign-up link.

    Args:
        category: One of ``feature_request``, ``bug_report``,
            ``data_issue`` or ``other``.
        message: The feedback itself, in English or German
            (20-5000 characters). For bugs, describe what you did, what
            you expected and what happened instead.
        subject: Optional one-line summary (max 200 characters).
        context: Optional technical context (max 2000 characters), e.g.
            the tool name and arguments involved, case IDs, ECLI or law
            references.

    Returns:
        ``{"submitted": true, ...}`` on success, otherwise ``{"error": ...}``.

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": {
      "category": "<category>",
      "message": "<message>"
    },
    "name": "submit_feedback"
  }
}

Input Schema

Name	Required	Description	Default
`context`	No
`message`	Yes
`subject`	No
`category`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=false), the description discloses the auth requirement — 'Requires a signed-in connection (OAuth or API token); anonymous calls return an error with a sign-up link' — which is exactly the kind of failure mode an agent needs before invoking. It also reveals the response envelope ({"submitted": true, ...} on success, {"error": ...} otherwise), a detail not covered by annotations since no output schema exists.

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?

It is front-loaded with the purpose and consent guardrail before the Args block, and every section has a clear role. It is somewhat long, with the Args/Returns scaffolding adding bulk that could be tightened, but no sentence is genuinely wasted — the Returns paragraph is the only substitute for the missing output schema.

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?

For a four-parameter write tool with no output schema and no annotation-level detail, the definition covers everything an agent needs: purpose, invocation triggers, consent and privacy constraints, authentication prerequisites with the anonymous-call failure mode, per-parameter formats and limits, and the shape of the success/error response.

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: it supplies the allowed category values (feature_request, bug_report, data_issue, other) that the schema leaves as an unconstrained string, plus length bounds and formats for message (20-5000 chars, English or German), subject (max 200), and context (max 2000, with examples like tool name, arguments, case IDs, ECLI). This is substantive meaning the schema alone does not convey.

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 opens with a specific verb and resource: 'Send feedback about OLDP or this MCP server to the OLDP team.' It then enumerates the exact feedback classes (bugs, wrong legal data, feature requests), which cleanly separates it from the sibling read-only legal research tools such as search_cases or get_case.

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 states concrete triggers ('report bugs (wrong results, errors, broken tools)', 'problems with the legal data', 'request features') and an explicit gate: 'Only submit feedback the user wants to send or has agreed to.' It also carries a negative constraint (no personal data or confidential case details), so the agent knows both when to call and when not to.

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

All Open Legal Data (Germany) tools Inspect

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