Skip to main content
Glama

change_burn

Detect fire scars and classify burn severity by computing the differenced Normalized Burn Ratio (dNBR) from pre-fire and post-fire NIR and SWIR reflectance values.

Instructions

Fire scar / burn severity detection using dNBR (differenced Normalized Burn Ratio). Computes NBR for pre-fire and post-fire dates from NIR and SWIR bands, then classifies burn severity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nir_afterYesNear-infrared reflectance for the post-fire date
nir_beforeYesNear-infrared reflectance for the pre-fire date
swir_afterYesShort-wave infrared reflectance for the post-fire date
swir_beforeYesShort-wave infrared reflectance for the pre-fire date
Behavior3/5

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

No annotations provided. The description explains the algorithm (compute NBR, classify severity) but does not disclose side effects, classification thresholds, or safety implications (e.g., read-only vs destructive). Some behavioral info is present but incomplete.

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?

Two sentences, front-loaded with purpose, no redundancy. Every word adds value.

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?

No output schema, yet description does not explain output format or severity classes. Given 4 parameters and a computational task, more detail on expected results would be helpful.

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 has 100% description coverage for all parameters. The description adds context by explaining that parameters correspond to pre/post NIR and SWIR bands used in dNBR calculation, which is beyond the schema's field descriptions.

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 clearly states the tool detects fire scar/burn severity using dNBR, with specific mention of NIR and SWIR bands and pre/post dates. This distinguishes it from sibling tools like change_detect or spectral_nbr.

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 explicit guidance on when to use this tool versus alternatives. Does not mention prerequisites like satellite imagery or contexts where this tool is appropriate.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/badchars/satellite-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server