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Cbs Nl

by io.github.pipeworx-io
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Search Tables

search_tables
Read-onlyIdempotent

Find CBS StatLine datasets by keyword (matched against title). Returns table id, title, period and language. Table ids ending in "eng"/"ENG" have English labels; others are Dutch.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "keyword": "population"
    },
    "name": "search_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault
topNoMax results (default 25).
keywordYesSearch term matched in the table title, e.g. "population", "energy", "wages".
english_onlyNoIf true, only return English-language tables (id ends in "eng"). Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "keyword": "population"
+  },
+  {
+    "english_only": true,
+    "keyword": "energy",
+    "top": 10
+  }
+]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds valuable behavioral specifics: matching is against title only, and table ids ending in 'eng'/'ENG' indicate English labels. This goes beyond annotations without contradicting them.

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 concise sentences, each with purpose: action+scope, return fields, and language identifier logic. No filler, front-loaded with the primary purpose.

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?

The tool has only 3 parameters, no output schema, and no nested objects. The description explains what it returns (table id, title, period, language) and key behavioral constraints (keyword matched against title, language suffix rule), which is sufficient for agent use.

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 coverage is 100% and each parameter has a description. The description's note about language ids slightly reinforces english_only, but schema already says 'id ends in "eng"'. No new parameter syntax or semantics are added, so baseline 3 applies.

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's action ('Find CBS StatLine datasets by keyword') and specifies the matched field (title). It also lists what is returned (table id, title, period, language), which distinguishes it from sibling tools like get_data or table_info that operate on known datasets.

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?

The description provides clear context: use this tool to search datasets by keyword. It does not explicitly mention alternatives or when-not-to-use, but the purpose is unambiguous enough for an agent to select it appropriately among siblings. No exclusions are noted.

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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