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Glama

Jak głosował poseł danego dnia

glosy_posla_w_dniu
Read-onlyIdempotent

Retrieve all votes cast by a Polish Sejm deputy on a single sitting day, including agenda item and Senate amendment or veto outcomes, in one call instead of querying each vote.

Instructions

Wszystkie głosy jednego posła w jednym dniu posiedzenia, z tematem, punktem porządku obrad i rozstrzygnięciem przy poprawkach Senatu i wecie. Jak poseł głosował w serii głosowań jednego dnia (np. nad wszystkimi poprawkami Senatu): to narzędzie, jedno wywołanie, a nie glosowanie po kolei. Dni posiedzeń daje lista_posiedzen albo profil_posla z dni=true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesNumer posła
dataYesDzień posiedzenia (RRRR-MM-DD)
kadencjaNoNumer kadencji Sejmu; domyślnie 10 (bieżąca, od 13 listopada 2023)
posiedzenieYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
uwagiNo
zrodlaYes
kalendarzNo
wynikCzesciowyNoTylko przy wyniku NIEPEŁNYM: powiedz to użytkownikowi na początku

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), lowering the bar. The description usefully adds the aggregation behavior ('jedno wywołanie, a nie glosowanie po kolei'), but the rest of its content (topic, agenda item, Senate amendment/veto outcome) is return-content detail that the output schema already provides.

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?

Two compact sentences lead with the core purpose and then the routing/alternative information; nothing is wasted and the most important claim is front-loaded.

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

Completeness4/5

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

With a rich output schema and full annotations, the description only needs to frame purpose and routing, which it does. The only gap is the undocumented 'posiedzenie' parameter, which is minor given the schema and the defaulted 'kadencja'.

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 high (75%), so the schema carries most parameter meaning; the description adds no parameter-level detail (formats, ranges, or what 'posiedzenie' means, which is the one undocumented field). Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a precise verb+resource+scope: 'Wszystkie głosy jednego posła w jednym dniu posiedzenia'. It also distinguishes itself from the per-vote alternative ('to narzędzie, jedno wywołanie, a nie glosowanie po kolei'), so an agent can separate it from glosowanie/glosowania_posiedzenia without opening schemas.

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?

Gives clear usage context ('Jak poseł głosował w serii głosowań jednego dnia, np. nad wszystkimi poprawkami Senatu') and names the alternative sources for the required date (lista_posiedzen, profil_posla z dni=true). It stops short of stating when NOT to use it (e.g. multi-day or multi-MP queries), so it is strong but not exhaustive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.