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firms_summary

Compute aggregate fire statistics for a geographic area, including total fire count, average brightness, fire radiative power, day vs. night distribution, and confidence level breakdown over 1, 2, or 7 days.

Instructions

Compute aggregate fire statistics for a geographic area over a time period. Returns total fire count, average brightness and fire radiative power (FRP), day vs. night distribution, and confidence level breakdown. Useful for wildfire risk assessment and trend analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoNumber of days to aggregate (1, 2, or 7). Default: 7
eastYesEastern longitude of the bounding box (-180 to 180)
westYesWestern longitude of the bounding box (-180 to 180)
northYesNorthern latitude of the bounding box (-90 to 90)
southYesSouthern latitude of the bounding box (-90 to 90)
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It describes the return values but does not mention any behavioral traits such as whether the tool is read-only, if there are rate limits, maximum bounding box constraints, or how missing data is handled. This leaves significant gaps for an agent to infer safety and limitations.

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: first states the main purpose, second lists the specific outputs, and a third provides a use case. No redundant words; every sentence adds value. The structure is front-loaded with the core action.

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

Completeness4/5

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

Given no output schema, the description adequately enumerates the return values (total fire count, average brightness, FRP, day/night distribution, confidence breakdown). It also provides a use case (wildfire risk assessment). However, it does not mention response format, units, or error behavior, which would enhance completeness for an agent.

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 100% with each parameter described (e.g., lat/lon ranges, days enum). The description adds minimal parameter information beyond the schema, only confirming that 'time period' maps to days and 'geographic area' to bounding box. Baseline 3 is appropriate because schema does the heavy lifting.

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 verb 'Compute aggregate fire statistics' and specifies the resource 'for a geographic area over a time period'. It differentiates from sibling firms tools (e.g., firms_active_point, firms_history) by focusing on aggregated statistics rather than individual fire points or historical records.

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 says 'Useful for wildfire risk assessment and trend analysis', implying appropriate use cases. However, it does not explicitly contrast with alternatives or state when not to use this tool (e.g., for real-time fire tracking use firms_latest). The usage context is implied but not exclusionary.

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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