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malkreide

lobbywatch-mcp

by malkreide

lobbywatch_get_parlamentarier

Read-onlyIdempotent

Retrieve a Swiss federal parliamentarian's full profile and declared interests. Use a name or ID for fuzzy matching; near-miss candidates are suggested when no exact match is found.

Instructions

Look up a Swiss federal parliamentarian and return their full profile, including all declared/researched interessenbindungen.

On a fuzzy miss, the response surfaces near-miss candidates so the LLM can prompt the user with "did you mean…?" suggestions instead of treating the empty result as authoritative (audit ARCH-003).

Args: name_or_id: Either the numeric Lobbywatch ID (as string) or a name. Name matching is fuzzy — partial last names work.

Use cases: - "Show me Anna Mustermann's full lobbying profile" - "What conflicts of interest does parliamentarian #42 declare?" - "Look up Wehrli — give me everything you have"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
name_or_idYes

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
parlamentarierNo
suggestionsNoNear-miss fuzzy candidates when the lookup failed (ARCH-003)
Behavior4/5

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

Adds value beyond annotations by describing fuzzy miss handling and that the profile includes interessenbindungen. 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?

Well-structured with summary, args, use cases, and note. Every sentence adds value; no fluff.

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?

For a simple tool with one parameter, the description covers all relevant aspects: behavior on hit/miss, parameter explanation, and use cases. Output schema exists but is not needed in description.

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?

Explains that name_or_id can be a numeric ID or fuzzy name, and that partial last names work. Schema coverage is 0%, so the description fully compensates.

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 it 'Look up a Swiss federal parliamentarian and return their full profile', clearly identifying the resource and action. It also distinguishes from sibling tools like lobbywatch_search_parlamentarier_nach_branche.

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 explicit use cases ('Show me Anna Mustermann's full lobbying profile') and explains fuzzy miss behavior. Does not explicitly contrast with siblings but offers sufficient 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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