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malkreide

lobbywatch-mcp

by malkreide

lobbywatch_get_ranking

Read-onlyIdempotent

Rank Swiss parliamentarians by number of interest connections or full-time mandates. Filter by party or commission to see top involvement.

Instructions

Rank parliamentarians by a criterion.

Args: kriterium: One of "anzahl_interessenbindungen", "anzahl_hauptberuflich". kommission: Optional commission abbreviation filter (e.g. "WBK-N"). partei: Optional party filter (e.g. "SP", "SVP", "Mitte"). limit: Top-N to return (1–100).

Use cases: - "Top 10 SP MPs by total mandate count" - "Which Mitte-Fraktion members have the most full-time mandates?" - "Rank WBK-N by IB count — who's most involved?"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kriteriumNoanzahl_interessenbindungen
kommissionNo
parteiNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoData: Lobbywatch.ch — CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). Not an official register; community-researched records.
provenanceYesWhich endpoint / dump the payload came from
kriteriumYes
eintraegeNo
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true; description aligns by describing a read-only ranking. No additional behavioral traits (e.g., rate limits, data freshness) are disclosed beyond what annotations provide, but no contradictions.

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?

Extremely concise: single sentence intro, clear Args section, and two-line Use cases. Every sentence adds value; no filler or redundancy.

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 presence of an output schema, no need to describe return values. All parameters are covered, use cases illustrate typical applications, and the tool's purpose is fully contextualized for an AI agent.

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 description coverage is 0%, so description compensates by explaining each parameter: enum values for kriterium (with examples), optional filters for kommission and partei (with sample values), and range for limit. Provides meaning beyond raw schema.

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 clearly states 'Rank parliamentarians by a criterion', specifying the verb and resource. It distinguishes from sibling tools like lobbywatch_get_parlamentarier or lobbywatch_list_interessenbindungen which do not perform ranking.

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?

Provides concrete use cases (e.g., 'Top 10 SP MPs by total mandate count') and explains parameters like kriterium, kommission, partei, limit. Lacks explicit when-not-to-use or alternatives, but examples strongly imply appropriate contexts.

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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