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explode_layer

Idempotent

Split multi-part geometries into one feature per part while preserving attributes. Output counts are verified so missing parts fail loudly, and inputs without a CRS are rejected.

Instructions

Split multi-part geometries into one feature per part (attributes copied).

The output feature count is verified against the number of parts counted before the engine ran, so a lost part fails loudly instead of shipping. Inputs without a CRS are refused.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_pathYes
output_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the annotations, the description adds meaningful behavioral details: attributes are copied to each output feature, output feature count is verified against the pre-run part count so lost parts fail loudly, and inputs without a CRS are refused. These constraints and failure semantics are not visible in the schema or annotations and materially help an agent anticipate tool behavior.

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?

The description is three sentences with no filler. The main action is front-loaded in the first sentence, and each subsequent sentence adds a distinct piece of information: attribute handling, failure verification, and CRS requirement. Nothing is repetitive or tangential.

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?

Given the presence of an output schema and meaningful annotations, the description covers the core behavior, the output semantics, and key operational constraints. An agent has enough information to select this tool and understand the important failure and requirement conditions without needing to inspect additional resources.

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 for missing parameter documentation. It adds some useful semantics: 'Inputs without a CRS are refused' constrains input_path, and 'attributes copied' hints at output behavior. However, it does not explicitly clarify what input_path and output_path should contain, their supported formats, or the relationship between them, leaving part of the burden on parameter names.

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 uses a specific verb ('Split') and a precise resource ('multi-part geometries into one feature per part'), with a note that attributes are copied. This clearly conveys the operation and distinguishes it from sibling tools like dissolve_layer, merge_layers, or centroid_layer, which perform different geometry transformations.

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?

The description implies when to use the tool: when multi-part geometries need to be exploded into single-part features. However, it does not explicitly state when not to use it, mention prerequisites beyond CRS, or name alternative sibling tools for comparison. The usage guidance is functional but not explicit about exclusions.

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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