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spectral_ndwi

Calculate Normalized Difference Water Index (NDWI) to detect water bodies, assess flood extent, and monitor drought conditions using green and NIR band reflectance.

Instructions

Calculate Normalized Difference Water Index (NDWI) from Green and NIR band reflectance values. NDWI = (Green - NIR) / (Green + NIR). Values range from -1 to 1. Used for detecting water bodies, assessing flood extent, and monitoring drought conditions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nirYesNIR band reflectance value (0–1). Near-Infrared band, typically Sentinel-2 Band 8 or Landsat Band 5.
greenYesGreen band reflectance value (0–1). Green visible band, typically Sentinel-2 Band 3 or Landsat Band 3.
Behavior3/5

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

No annotations are provided, so the description must cover behavior. It includes the formula and value range, but does not mention potential division-by-zero issues, required input preprocessing, or the output format beyond range. This is adequate but not thorough.

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 concise sentences, front-loaded with the formula and key information. No unnecessary words, and the structure is logical.

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?

The description states the output range but does not specify the exact return type (e.g., a single number) or behavior for edge cases (e.g., division by zero). Given no output schema, more detail would be beneficial for a complete understanding.

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% with good parameter descriptions. The tool description adds value by providing typical band assignments (e.g., Sentinel-2 Band 3, Landsat Band 3) and the formula, which helps understand parameter meaning beyond the schema.

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?

The description clearly states the tool calculates NDWI from Green and NIR bands, provides the formula, and lists applications. It is specific but does not explicitly differentiate from sibling spectral indices like NDVI or NBR.

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?

The description provides clear usage context by listing applications (water detection, flood extent, drought monitoring). However, it lacks explicit when-not-to-use or comparisons to alternatives.

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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