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malkreide

lobbywatch-mcp

by malkreide

lobbywatch_list_interessenbindungen

Read-onlyIdempotent

Retrieve conflicts of interest (Interessenbindungen) for a Swiss parliamentarian by name or ID, with optional filters for full-time or currently active mandates.

Instructions

Return the list of interessenbindungen (conflicts of interest) for one parliamentarian, optionally restricted to full-time or currently-active mandates.

On a fuzzy miss, near-miss candidates are returned in suggestions (audit ARCH-003).

Args: name_or_id: ID or name (fuzzy). nur_hauptberuflich: If True, only main-occupation mandates. nur_aktiv: If True, drop mandates with an end date (bis) set.

Use cases: - "Which active mandates does Jositsch hold today?" - "List Anna Mustermann's full-time mandates only" - "Give me every IB ever declared by parliamentarian #1"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
name_or_idYes
nur_hauptberuflichNo
nur_aktivNo

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
parlamentarier_idYes
countYes
interessenbindungenNo
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?

Beyond annotations (readOnlyHint, idempotentHint), the description adds key behaviors: fuzzy matching with suggestions on near-miss, and optional restrictions (nur_hauptberuflich, nur_aktiv). It does not contradict annotations.

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 well-structured with sections for purpose, behavior, Args, and use cases. It is slightly verbose but each sentence adds value, and it is front-loaded with the main purpose.

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 that an output schema exists and the parameters are simple, the description covers all necessary aspects: input parameters, fuzzy matching, optional filters, and common use cases. It does not require further elaboration.

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 description explains each parameter clearly in the Args section (e.g., 'nur_hauptberuflich: If True, only main-occupation mandates'), compensating for the 0% schema description coverage. Use cases further illustrate parameter usage.

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 'Return the list of interessenbindungen (conflicts of interest) for one parliamentarian', using a specific verb and resource. It distinguishes from sibling tools like 'lobbywatch_get_parlamentarier' by focusing on conflicts of interest.

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?

The description provides three concrete use cases (e.g., 'Which active mandates does Jositsch hold today?') that illustrate when to use the tool. However, it does not explicitly mention when not to use it or name alternatives, though the sibling tools cover different purposes.

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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