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polls.karbach.digital

search_lobby_register

Search the German Bundestag lobby register (organisations): name, field of interest, type, minimum lobbying spend.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldNo
limitNo
queryNo
min_eurNo
org_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. 'Search' implies a read, but nothing is said about pagination behavior despite the limit parameter, result caps, return shape, or auth needs. For a 5-parameter tool with zero annotation coverage this is a notable gap.

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?

A single front-loaded sentence with no waste; the resource and its searchable dimensions are stated immediately. It is appropriately sized, if a touch under-elaborated.

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

Completeness2/5

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

With no annotations, no output schema, and five undocumented optional parameters, the description should say more about what a search returns, currency/sorting of results, and default behavior of limit. It names filter facets but leaves the call-and-response picture incomplete.

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 0%, so the description must compensate, and it partially does by naming the searchable facets: name (query), field of interest (field), type (org_type), and minimum lobbying spend (min_eur). It adds real meaning over bare schema titles, but the limit parameter is never explained and the facet-to-parameter mapping is left implicit.

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?

States a specific verb (Search) and resource (German Bundestag lobby register) and scopes it to 'organisations', which distinguishes it from entry-level lookups. It does not explicitly call out its sibling get_lobby_register_entry, but the search-vs-fetch distinction is inferable from the verb.

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?

No when-to-use guidance, no exclusions, and no named alternatives. The listed facets imply you filter by them, but an agent gets no steer on when this beats get_lobby_register_entry or lobbying_ranking.

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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