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gearys_c

Compute the Global Geary's C autocorrelation statistic to measure spatial clustering of geographic data using a shapefile, with configurable dependent variable, CRS, and distance threshold.

Instructions

Compute Global Geary's C Autocorrelation Statistic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
shapefile_pathYes
dependent_varNoLAND_USE
target_crsNoEPSG:4326
distance_thresholdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

Description is minimal, adds no behavioral details beyond the name. Without annotations, the agent is left uninformed about side effects or execution context.

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?

Single sentence is short and to the point, but trades off completeness.

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

Completeness1/5

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

Given the tool's complexity (4 params, multiple siblings), the description fails to convey required inputs, output, or purpose nuances, making it inadequate for correct invocation.

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

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Description does not explain any of the four parameters (shapefile_path, dependent_var, target_crs, distance_threshold), leaving the agent blind despite 0% schema coverage.

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?

Description clearly states the tool computes Global Geary's C Autocorrelation Statistic, distinguishing it from siblings like morans_i and getis_ord_g.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use Geary's C vs alternatives like Moran's I, no context on appropriateness or prerequisites.

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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