hk-spatial-mcp

query_hk_data

Retrieve a few individual features from a Hong Kong CSDI spatial dataset to verify a specific value by field match or free text, without opening the full GeoJSON.

Instructions

Read a FEW individual features, so a single value can be verified without opening the GeoJSON.

where is either FIELD=value (case-insensitive match on one field) or bare text searched across all fields. Rows are capped at 20 — this tool exists to check a value, not to dump a dataset; use summarise_hk_data for aggregates and build_map to see the layer.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dataset_id": "<dataset_id>"
    },
    "name": "query_hk_data"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`where`	No
`fields`	No
`dataset_id`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.12.0Oct 23, 2026

TDQS

A4/5.0

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the hard 20-row cap and the matching semantics of `where` (case-insensitive field match vs. free text across all fields), which are real behavioral facts. It is silent on error/empty-result behavior and permissions, but the read-only nature is clear from 'Read'.

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?

Two short paragraphs with the core purpose front-loaded and no filler sentences; every clause either scopes the tool or routes to a sibling. The second paragraph blends query semantics with alternative-tool guidance, a minor organizational quibble.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described. However, with zero annotation coverage and zero schema property descriptions, leaving `fields` undocumented and no note on empty results means the definition is not fully sufficient for a 4-parameter 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 description coverage is 0%, so the description must compensate. It explains `where` thoroughly and implies the row cap that governs `limit`, but `fields` is never explained despite being a non-obvious parameter (field projection). Roughly half the parameters gain meaning from the description.

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 opens with a specific verb and resource ('Read a FEW individual features') and states the scope limit (single value verification, capped at 20 rows). It also explicitly distinguishes itself from `summarise_hk_data` (aggregates) and `build_map` (visualize layer), so an agent can tell what this tool is for without opening the schema.

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?

It gives clear when-to-use ('so a single value can be verified') and when-not-to-use ('this tool exists to check a value, not to dump a dataset'), and names two alternatives with their purposes. It does not address the closest sibling, `search_hk_data`, leaving the query-vs-search distinction to inference.

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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