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Opendosm List Datasets

opendosm_list_datasets
Read-onlyIdempotent

List the curated, verified high-value datasets available from data.gov.my / OpenDOSM (Dept of Statistics Malaysia). data.gov.my exposes no machine listing/search endpoint, so this returns a hand-verified set covering inflation, GDP, labour, prices, income, population and demography, with each dataset id, topic, description and its value columns. Optionally filter by topic.

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": {
      "topic": "inflation"
    },
    "name": "opendosm_list_datasets"
  }
}

Input Schema

NameRequiredDescriptionDefault
topicNoOptional topic filter, e.g. "inflation", "labour", "population", "gdp", "prices", "income", "demography", "industry".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "topic": "inflation"
      +  },
      +  {}
      +]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by explaining the data's provenance (hand-verified, covering multiple topics) and the absence of a machine endpoint, which clarifies the tool's behavior beyond the 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 succinct sentences with no wasted words. Front-loaded key info (list curated datasets) followed by context and optional filter. Excellent structure.

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 listing tool with one optional parameter and no output schema, the description covers purpose, data source, and filter capability adequately. It could mention the return format slightly, but completeness is strong given the tool's simplicity.

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% for the single optional parameter. The description adds example topics (inflation, labour, etc.) and indicates the parameter is a filter, enriching the semantic meaning 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 lists curated, verified datasets from data.gov.my / OpenDOSM, with a specific verb (list) and resource (datasets). It distinguishes itself from siblings by focusing on a unique domain (Malaysian statistics) and mentions the hand-verified nature.

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 explains that no machine endpoint exists and the tool returns a hand-verified set, providing context for when to use it. It also mentions optional filtering by topic. However, it does not explicitly exclude when not to use or direct to sibling tools like opendosm_get_dataset for specific datasets.

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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