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Malaysia Land Lots & Local Plan Zoning

by io.github.BumiAtlas
OverviewDiscussionsAdmin

Map image of a Malaysian lot and its neighbours

MY_lot_image
Read-onlyIdempotent

A map image centred on a Malaysian lot (id, the UPI from MY_lot_search) or a point (query), with every lot in view outlined and labelled with its lot number, so you can see which lot is where. The lot passed as id is drawn in red with a larger label; a query point is a red dot. Returns the lots in view as JSON (label: the lot number, with /2 on a number repeated from another mukim or section; id (UPI), lot, keluasan in m²; labelled: false where its label didn't fit), then one JPEG per basemap. Basemaps: satellite (Esri World Imagery, often a few years old), hybrid (the same imagery with road and place names), streets and topo (Esri's street and topographic maps). Pass several to compare, e.g. ['satellite', 'streets'] to match buildings with street names. Lot outlines are yellow on imagery and magenta on maps. Lots are only loaded for some states, so elsewhere the image has none. Imagery is not always aligned with the cadastre: offsets of a few metres are possible. A scale bar is at bottom left. Labels are left off where they'd overlap; call again with a smaller radius to read them. Each image costs about as much context as 1,000 words, so ask for what you need.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

NameRequiredDescriptionDefault
idNoUPI from MY_lot_search, drawn in red
sizeNoImage width and height in pixels
queryNo'latitude, longitude' to centre on instead of a parcel
radiusNoMetres from the centre to the image edge. Default: fits the parcel with a margin, or 80 m around a point
basemapsNoOne image per basemap

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive behaviour, and the description adds substantial context: return composition as JSON plus JPEGs, basemap provenance and staleness, state-dependent lot coverage, possible imagery/cadastre offsets, scale bar placement, label suppression, and context cost. This is exactly the kind of behavioural detail an agent needs 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?

Despite being dense, the paragraph is front-loaded with the core purpose and return shape, then layers useful caveats. Every sentence appears to earn its place: basemap choices, colour conventions, coverage limits, alignment caveats, label overlap, and context cost.

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?

For a complex image-producing tool with no output schema, five parameters, and only safety annotations, the description covers return format, image semantics, limitations, and practical usage well enough for an agent to call it correctly. No major missing context is apparent.

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%, so the baseline is 3, but the description adds real meaning for `id` (drawn in red with larger label), `query` (red dot), `basemaps` (satellite/hybrid/streets/topo meanings and comparison example), and `radius` (smaller radius to read labels). It does not add anything for `size`, keeping it from a 5.

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 concrete output: a map image centred on a Malaysian lot or point, with every lot in view outlined and labelled. It distinguishes the `id` input as coming from MY_lot_search versus a `query` point, making the tool clearly identifiable as the visual map-image sibling.

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 contexts: seeing which lot is where, comparing basemaps such as satellite versus streets to match buildings with street names, and calling again with a smaller radius when labels overlap. It does not explicitly state when not to use it or name MY_lot_get/MY_zoning_get as alternatives, so it falls short of full when/when-not guidance.

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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