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Glama

Czso Cz

by io.github.pipeworx-io
OverviewAdmin

Data Summary

data_summary
Read-onlyIdempotent

Cheap content summary for a ČSÚ dataset from the data layer: number of data cells (pocetUdaju), covered time range (casovaDimenzeOd/Do), per-dimension value counts, and last-change/publish times. Use this before get_data to gauge size, since full datasets can be large. Version (verze) is auto-resolved from the catalog if omitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kodYesDataset id, e.g. "OBY05B03".
verzeNoDataset version. Optional — defaults to the latest version from the catalog.

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: +[
+  {
+    "kod": "OBY05B03"
+  },
+  {
+    "kod": "OBY05B03",
+    "verze": "1.0"
+  }
+]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already indicate readOnly, openWorld, idempotent, non-destructive. Description adds context by calling it 'cheap' and explaining what it returns, which helps the agent understand its lightweight nature.

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?

Three sentences, no wasted words. First sentence lists outputs, second gives usage context, third adds parameter detail. Front-loaded with purpose.

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?

For a simple read-only tool with two parameters, the description adequately covers what it does, when to use it, and parameter behavior. No output schema needed; description explains return fields.

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 covers both parameters with descriptions (100% coverage). Description adds that version (verze) auto-resolves from catalog if omitted, providing extra semantics beyond the 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?

The description clearly states the tool returns a cheap content summary for a ČSÚ dataset, listing specific fields (number of data cells, time range, per-dimension counts, timestamps). It distinguishes from sibling tools by explicitly recommending use before get_data to gauge size.

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

Usage Guidelines5/5

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

Explicitly says 'Use this before get_data to gauge size, since full datasets can be large.' Also explains that version is auto-resolved if omitted, providing clear when-to-use and behavioral guidance.

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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