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soulnai

nl-opendata-mcp

by soulnai

cbs_query_dataset

Read-onlyIdempotent

Query CBS datasets using OData filters and column selection. Returns CSV data with translated dimension values.

Instructions

Queries data from a dataset with optional filtering and column selection.

Args: params: QueryDatasetInput containing: - dataset_id (str): Dataset ID (e.g., '85313NED') - top (int): Number of records (default: 10) - skip (int): Records to skip (default: 0) - filter (str, optional): OData filter (e.g., "Perioden eq '2023JJ00'") - select (List[str], optional): Column names to return - compact (bool): Return summary for large results (default: True) - translate (bool): Translate coded dimension values to text (default: True)

Returns: str: CSV data with human-readable dimension values

Note: Use cbs_get_metadata with metadata_type="dimensions" to find filter codes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYesInput model for querying datasets.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Adds behavioral context beyond annotations: returns CSV, uses OData filter syntax, and translates dimension values. Annotations already provide safety profile.

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?

Well-structured with Args and Returns sections, but slightly verbose. Could be more concise while retaining clarity.

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?

Covers all parameters, explains return format (CSV), includes annotations, and references sibling for metadata. Sufficient for a query tool.

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%, so baseline 3. Description repeats parameter info but adds example filter and translate explanation, adding marginal value.

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?

Clear verb 'Queries' and resource 'data from a dataset', with optional filtering and column selection. Distinguishes from siblings by referencing cbs_get_metadata for filter codes.

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?

Implies usage for querying data and hints at using cbs_get_metadata for filter codes, but lacks explicit guidance on when to use this tool versus alternatives or when not to use it.

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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