Skip to main content
Glama

load_hk_data

Downloads a Hong Kong CSDI dataset as GeoJSON (WGS84) into your workspace, returning a summary instead of raw features. Reuses the local copy on later calls; use refresh to re-download.

Instructions

Download one CSDI dataset as GeoJSON (WGS84) into the workspace. Returns a SUMMARY, not the data itself — never paste the features into the chat, put them on a map with build_map(). The local copy is reused on later calls; pass refresh=True to re-download.

Input Schema

NameRequiredDescriptionDefault
nameNo
refreshNo
dataset_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.12.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that the return value is a summary rather than the data, that local copies are reused on later calls, that refresh=True forces a re-download, and that data is GeoJSON in WGS84. It does not cover failure modes, permissions, or dataset_id validation, so it is strong but not exhaustive.

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 short sentences, front-loaded with the core action and followed by the most important usage warning and caching detail. Every sentence adds practical value with no repetition.

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?

An output schema exists, so the description need not explain the summary structure. For a data-loading tool with no annotations, it sufficiently covers output type, local caching, refresh semantics, and downstream map usage. The main remaining gap is parameter semantics for dataset_id and name.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

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 refresh=True behavior meaningfully, but leaves dataset_id format/valid values and the purpose of the name parameter undocumented. Only one of three parameters receives useful semantic explanation.

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 states a specific verb and resource: 'Download one CSDI dataset as GeoJSON (WGS84) into the workspace.' It also clarifies the scope and points to build_map for visualization rather than pasting features, which helps distinguish it from query/search siblings.

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 usage context: download data locally, then put it on a map with build_map(), and never paste features into chat. It also explains refresh behavior for re-downloading. It does not explicitly say when to use this instead of search_hk_data or query_hk_data, so it falls short of full alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.