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Czso Cz

by io.github.pipeworx-io
OverviewAdmin

List Datasets

list_datasets
Read-onlyIdempotent

Browse the Czech Statistical Office (ČSÚ) open-data catalog of datasets ('datové sady'). Returns id (kod), version (verze), Czech title (nazev), status, and available time/territory levels. The full catalog is ~781 datasets; filter by a case-insensitive substring of the Czech title (the API has no server-side search) and page with limit/offset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows to return (default 25, max 200).
queryNoCase-insensitive substring matched against the Czech title (nazev), e.g. "rozvody", "inflace", "mzdy".
offsetNoRows to skip for paging (default 0).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "inflace"
+  },
+  {
+    "limit": 50,
+    "offset": 0,
+    "query": "mzdy"
+  }
+]
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Discloses that API has no server-side search, which is critical behavioral info beyond annotations. Adds specific return fields. No contradictions with annotations.

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 efficient sentences, front-loaded with purpose and key details, no wasted words.

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 list tool with rich annotations, it covers purpose, parameters, return fields, and API limitations. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, description adds case-insensitive substring matching detail and paging context, going beyond schema.

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?

Uses specific verb 'browse' and resource 'catalog of datasets', clearly lists return fields, and distinguishes from siblings like 'dataset_detail' via scope.

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?

Explains filtering and paging behavior, mentions lack of server-side search, and provides context for when to use. Does not explicitly name alternative tools but context is clear.

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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