qgis-dev-probe-mcp

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inspect_layer

Inspect a QGIS layer by id or unique name to retrieve its fields, geometry or raster bands and nodata values, plus sample features for verifying plugin behavior.

Instructions

Details of a layer by id or unique name: fields/geometry (vector) or bands/nodata (raster), sample features.

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": {
      "layer": "<layer>"
    },
    "name": "inspect_layer"
  }
}

Input Schema

Name	Required	Description	Default
`layer`	Yes
`sample`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 25, 2026

TDQS

B3.4/5.0

Behavior3/5

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

No annotations are supplied, so the description carries the full burden; it does disclose the returned content categories (vector fields/geometry, raster bands/nodata, sample features), which is real behavioral value. It omits whether the call has side effects, permission requirements, and how it fails for an unknown layer.

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?

A single dense sentence with the resource and the return categories front-loaded; nothing is wasted. It is perhaps too compressed, but it is structurally sound and easy to scan.

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?

With only two parameters and no output schema, the description should explain what the call returns and any failure behavior. It names the content categories but not the response shape, and says nothing about invalid layer identifiers or the meaning of the sample default.

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 0% and both parameters are bare, so the description must compensate. It usefully clarifies that 'layer' accepts an id or unique name, and hints that 'sample' relates to sampling features, but does not state that sample is a count or how sample=0 behaves.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (inspect/details) and resource (layer), plus the content returned for each layer type (fields/geometry vs bands/nodata). It distinguishes itself from siblings like list_layers by being about a single layer's internals, though it never says so explicitly.

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?

Usage is only implied: an agent can infer this is for examining one known layer, complementing list_layers for discovery. There is no explicit when-to-use, when-not-to-use, or named alternative, and no prerequisite about obtaining a valid layer id/name first.

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