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mcp-lovdata

mcp-lovdata

by synjan
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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Hent en stortingssak med dokumenttekst

preparatory_get

Get details of a legislative preparatory case: topics, committee, proceedings, decisions, and document links. Optionally fetch the full text, truncated to a character limit.

Instructions

Detaljer om én sak: emner, komité, saksgang, vedtak og lenker til dokumentene. Sett includeText for å hente selve teksten i innstillingen eller proposisjonen — den er ofte lang, så den avkortes.

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": {
      "caseId": "<caseId>"
    },
    "name": "preparatory_get"
  }
}

Input Schema

NameRequiredDescriptionDefault
caseIdYessakId fra et søketreff.
maxCharsNo
includeTextNoHent dokumentteksten, ikke bare metadataene.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations provided, the description carries the behavioral burden. It usefully warns that document text is often long and is truncated ('den er ofte lang, så den avkortes'), but it does not describe return structure, permissions, or other behavioral constraints.

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 compact and front-loaded: the first sentence states the core purpose, and the second explains the optional text behavior and its important truncation caveat. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description names the main returned content and the optional text behavior, which is adequate for a basic call. However, with no output schema and several sibling getters, the lack of tool-selection guidance and undocumented maxChars behavior leave some gaps for an agent.

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

Parameters3/5

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

Schema description coverage is 67%, and the description adds meaningful context for includeText by explaining that it retrieves the actual innstilling/proposisjon text. However, maxChars is not explained in the description, and caseId is only minimally connected to a search result.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool returns details about a single parliamentary case: subjects, committee, case process, decisions, and links to documents. The singular focus ('én sak') helps distinguish it from search tools, though it does not explicitly contrast it with sibling getters like get_document.

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

Usage Guidelines2/5

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

There is no explicit guidance about when to use this tool instead of preparatory_search, get_document, or get_article. The only conditional instruction concerns setting includeText, which is a parameter choice rather than tool-selection guidance.

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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