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nu:legal Deutsches Recht

by eu.nulegal
OverviewDiscussionsAdmin

Corpus coverage

getCoverage
Read-onlyIdempotent

What the corpus holds and what it does not: laws, decisions, courts, the version archive and the Länder covered. Call it before you report that something does not exist. The answer's coverage block is /v1/coverage: statutes per Land (statutes: full_text, partial or none), decisions per court level, the citation graph and what every version date is, all from one daily table. Example: {}

Input Schema

NameRequiredDescriptionDefault
courtNoAdds `courts` with only the courts whose name, slug or ECLI code contains this ('köln', 'BVerwG').
includeNo`["courts"]` adds `courts`: the court registry (slug, names, branch, level, Land, ECLI court code, decision count), at most 25 rows, busiest first.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / court
      Added value: +{
+  "description": "Adds `courts` with only the courts whose name, slug or ECLI code contains this ('köln', 'BVerwG').",
+  "type": "string"
+}
    • addedInput schema / properties / include
      Added value: +{
+  "description": "`[\"courts\"]` adds `courts`: the court registry (slug, names, branch, level, Land, ECLI court code, decision count), at most 25 rows, busiest first.",
+  "items": {
+    "enum": [
+      "courts"
+    ],
+    "type": "string"
+  },
+  "type": "array"
+}
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and non-destructive, so the description is not carrying the safety burden. It adds genuine behavioral context beyond that: the payload is the /v1/coverage block, statutes carry full_text/partial/none status, versions are date-keyed, and everything comes from one daily-refreshed table (a freshness signal not encoded anywhere else).

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?

Three sentences plus a call example, front-loaded with the purpose and then the usage rule. Slightly dense in the third sentence ("all from one daily table" is compressed), but no filler or restatement of the name/title.

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?

There is no output schema, so the description must convey the return shape — it does, naming the `coverage` block and its sub-sections (statutes per Land with status, decisions per court level, citation graph, version dates). Remaining gaps are minor: response size and whether output is paginated or aggregated are unstated.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3; the schema already explains `court` matching and what `include: ["courts"]` adds (max 25 rows, busiest first). The description earns a point above baseline by supplying "Example: {}", which signals that the zero-argument call is valid and is the default way to get the full coverage picture.

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 precisely what the tool reports: which laws, decisions, courts, version archive and Länder the corpus holds, and explicitly what it does not hold. That negative-space framing distinguishes it cleanly from search (which returns hits) and getNorm/getChanges (which return documents).

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

Usage Guidelines4/5

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

Gives a concrete prescriptive trigger: "Call it before you report that something does not exist." That is a clear when-to-use rule tied to a specific agent failure mode. No explicit when-not condition or named sibling alternative, so it stops short of the top score.

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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