NIFC Wildfire Data

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

Mentions data update frequency ('frequently during fire season') but lacks other behavioral details like rate limits, caching behavior, or data latency since no annotations exist.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with purpose first, followed by return value description and Args section; no redundant text though the docstring-style Args formatting could be more integrated.

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

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

Adequately complete given the simple schema and existence of output schema; mentions key return fields (name, location, size, containment) without over-explaining what the structured output schema already covers.

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

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

Excellent compensation for 0% schema description coverage by documenting all three parameters with clear semantics, expected formats, and concrete examples (e.g., 'CA', 'OR', 100).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it retrieves active wildfire incidents from NIFC with specific return fields, though it doesn't explicitly differentiate from sibling tools get_fire_perimeters and get_fire_stats.

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

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

Provides no guidance on when to use this tool versus alternatives or when filtering parameters are appropriate.

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

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

Discloses data scope ('active or recent') and matching behavior ('case-insensitive partial match') but omits auth requirements, rate limits, or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Appropriately brief and front-loaded; the Args section is slightly informal but efficiently conveys necessary parameter semantics without redundancy.

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

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

Adequate for the low complexity (2 optional params); briefly acknowledges return values despite presence of output schema.

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

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

Effectively compensates for 0% schema description coverage by documenting both parameters, including critical behavioral detail about partial matching for fire_name.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it retrieves fire perimeter boundaries for active/recent wildfires, distinguishing it from sibling tools via the specific resource type (perimeters vs active fires/stats).

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

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

Provides implied usage context ('Useful for understanding geographic extent') but lacks explicit guidance on when to choose this over get_active_fires or get_fire_stats.

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

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

Adds data provenance context ('from active incident data') and default year behavior, but lacks other behavioral traits like rate limits or cache details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, appropriately brief; Args section is necessary given schema lacks descriptions.

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

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

Sufficient for low complexity (1 optional param); presence of output schema excuses lack of return value documentation.

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

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

Effectively compensates for 0% schema description coverage by documenting the year parameter's purpose, type hint (e.g. 2025), and default behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clear specific action (get wildfire statistics) and resource (total fires/acres), implicitly distinct from siblings (aggregate stats vs active fires/perimeters).

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

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

No guidance on when to choose this over get_active_fires or get_fire_perimeters; only parameter-level guidance provided.

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