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Ansvar-Systems

Finnish Law MCP Server

validate_citation

Verify Finnish legal citations against an authoritative database and receive warnings for repealed or amended provisions.

Instructions

Validate a Finnish legal citation against the database.

Parses the citation, checks that the document and provision exist, and returns warnings about status (repealed, amended). This is the zero-hallucination enforcer.

Supported formats:

  • "Laki 1050/2018 1 luku 1 §"

  • "1050/2018 1:1"

  • "SFS 2018:218 1 kap. 1 §" (legacy compatibility)

  • "Prop. 2017/18:105"

  • "SOU 2017:39"

  • "NJA 2020 s. 45"

When NOT to use: If you want to format a citation string, use format_citation. This tool checks existence in the database.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
citationYesCitation string to validate

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.3

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it delivers meaningful behavioral detail: it parses, checks document/provision existence, returns status warnings, and supports legacy formats. It does not specify exact return shape or invalid-input handling, but for a read-oriented validator the core behavior is clearly disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and efficient: a one-sentence purpose, a clear behavior summary, a compact list of supported formats, and an explicit when-not-to-use section. Every part earns its place, and the key purpose is front-loaded.

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?

The description covers the tool's purpose, behavior, supported formats, and sibling differentiation. Since there is no output schema, the main missing piece is a precise return contract or error behavior for invalid citations, but for a single-parameter validator this is a relatively minor gap.

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 only says 'Citation string to validate,' but the description adds concrete supported formats such as 'Laki 1050/2018 1 luku 1 §', '1050/2018 1:1', and 'NJA 2020 s. 45.' This goes well beyond the schema and is essential for correct invocation.

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: 'Validate a Finnish legal citation against the database.' It clearly explains what validation entails—parsing, checking existence of document and provision, and returning warnings—and distinguishes itself from the sibling format_citation. An agent can immediately tell this tool's job from its siblings.

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 says when not to use the tool and names the alternative: 'If you want to format a citation string, use format_citation.' It also clarifies that this tool checks existence in the database. This gives an agent actionable routing guidance rather than leaving usage to inference.

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