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ris-austria-mcp-server

by io.github.cyanheads

RIS Reference Lists

ris_list_reference
Read-onlyIdempotent

Ground the opaque German codes across the RIS surface — static and offline, no upstream call. Topics: applications (all 39, with coverage windows, binding status, and content formats), courts (17 codes with Geschäftszahl examples and successor mapping), states (the three Bundesland request spellings), decision_types, decision_kinds (per-court Entscheidungsart values), issuing_bodies (dsk/dok/pvak/verg bodies and social-insurance issuers), ministries (abbreviations and full designations, historical included), collections (the 7 announcement collections and their parameter matrix), stages (lawmaking pipeline), changed_since_intervals, section_types, gazette_parts (BGBl parts and era tiers), law_types, district_authorities (all Bezirksverwaltungsbehörden), justiz_subject_areas (Fachgebiet taxonomy), search_syntax (operators and wildcard rules), and citation_formats (the shapes ris_lookup_citation parses). Recovery hints from the other ris_* tools route here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesWhich reference table to return. Pick the topic named in the error recovery hint or zero-hit notice that sent you here.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
notesNoTopic-level caveats and usage guidance. Empty when none apply.
topicNoThe requested topic, echoed back.
entriesNoReference entries for the topic.
summaryNoWhat this topic covers and which tool parameters consume its values.

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint=false, idempotentHint. The description adds that the tool is 'static and offline, no upstream call', which is consistent with read-only and adds context about no network dependency. It does not contradict annotations. It also states the coverage of topics, which is useful for understanding scope.

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 description is long but well-structured: it opens with the core purpose, then lists topics with concise parenthetical details, and ends with the routing hint. Each sentence contributes either to scope or usage, so despite length, it is efficient and front-loaded.

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?

Given the tool has a single parameter with an exhaustive enum, and the output schema exists (not shown but present), the description is complete. It explains what the tool returns, how to choose the topic, why one might land here, and the operational behavior. Nothing critical is missing.

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?

The schema provides an enum of 17 topics with a brief usage instruction. The description significantly adds meaning by detailing what each topic contains (e.g., 'applications (all 39, with coverage windows, binding status, and content formats)'), enabling the agent to select the correct topic. This goes beyond the enum names.

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 purpose: to ground opaque German codes across the RIS surface by returning static reference tables. It enumerates 17 topics, distinguishing itself from sibling search tools. The phrase 'static and offline, no upstream call' clarifies it is a lookup, not a live query.

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?

The description explicitly instructs that recovery hints from other ris_* tools route here, and the parameter schema description repeats this guidance ('Pick the topic named in the error recovery hint or zero-hit notice'). This gives clear when-to-use direction and implicitly distinguishes it from the search tools that generate those hints.

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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TDQS

A4.8/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: fetching documents, resolving citations, searching different content domains (legislation, case law, gazette, drafts, announcements), listing reference data, and tracking changes. No two tools overlap in function or could be confused for the same task.

Naming Consistency5/5

All tools follow a uniform ris_[verb]_[noun] snake_case pattern, using verbs like get, list, lookup, search, and track. The naming convention is entirely predictable and consistent across the server.

Tool Count5/5

With 9 tools, the server is well-scoped for its purpose of Austrian legal information retrieval. Each tool serves a distinct and necessary function, with no redundancy or unnecessary bloat.

Completeness5/5

The tool set covers the full lifecycle of legal research: reference lookup, citation resolution, five content-type searches, document retrieval with format control, and delta tracking for mirrors. There are no obvious gaps—every action an agent might need is available.

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