Sondaże.pro — Polish Polls

get_polling_averages

Pobiera znormalizowane lub surowe (RAW) średnie sondażowe poparcia partii politycznych w Polsce dla wskazanego okresu (miesiąc, tydzień ISO lub okno kroczące rolling 14/21/30 dni).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "period_type": "<period_type>",
      "period_key": "<period_key>"
    },
    "name": "get_polling_averages"
  }
}

Input Schema

Name	Required	Description
`strategy`	No	Strategia wyliczania średniej (domyślnie weighted_average - ważona wielkością próby z re-normalizacją do 100%)
`survey_id`	No	Opcjonalna lista ID sondaży w formacie JSON string, np. "[101,102]". Jeśli brak, uwzględniane są wszystkie sondaże w okresie.
`period_key`	Yes	Klucz okresu: YYYY-MM dla month, YYYY-Www dla week, last-14d\|last-21d\|last-30d lub YYYY-MM-DD:P{N}D dla rolling
`period_type`	Yes	Typ okresu: month (np. 2025-10), week (np. 2025-W42) lub rolling (np. last-30d, last-14d, 2025-11-10:P21D)
`strategy_version`	No	Wersja strategii (domyślnie 1)

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 18, 2026

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the normalized-vs-raw (RAW) distinction and the rolling-window options, but says nothing about permissions, rate limits, data freshness, or what the response contains beyond the averages.

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 dense sentence with the core operation front-loaded and no filler. It is appropriately sized for the tool, though the parenthetical enumeration of period formats is somewhat list-like rather than structured.

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

Completeness3/5

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

Given five parameters, no annotations, and no output schema, the description is only minimally adequate. It covers the period dimension but leaves the strategy weighting, survey_id filtering, and the shape of returned data entirely to the schema, which the agent must open to call it confidently.

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 100%, so the schema already documents all five parameters including strategy, survey_id, period_key, and strategy_version. The description only reinforces the period-type portion already covered by the schema, adding no syntax or semantics beyond it. Baseline 3 applies.

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?

The description states a specific verb and resource ('Pobiera ... średnie sondażowe poparcia partii politycznych w Polsce'), and its mention of 'znormalizowane lub surowe (RAW)' plus the period vocabulary hints at how it differs from the sibling get_polling_averages_series. It never names that sibling or any other alternative, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives implicit usage context by enumerating supported period types (month, ISO week, rolling 14/21/30 days), which tells an agent what input shapes are valid. However, it offers no explicit when-to-use/when-not-to-use guidance and does not point to get_polling_averages_series for time-series needs.

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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