get_carbon_intensity_forecast

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

No annotations are provided, so the description must cover behavioral traits. It only mentions the time horizon and return format, but lacks details on data freshness, update frequency, API limits, or potential rate limiting. This is a gap for a tool with no annotations.

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?

The description is concise and well-structured: a brief one-liner for purpose, followed by parameter details, return format, and a use case. Every sentence provides value 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?

Given the tool has one parameter, no output schema, and multiple siblings, the description covers the main functionality and usage. However, it could be more complete by explicitly distinguishing from get_uk_carbon_intensity and mentioning data source or update frequency.

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?

Schema coverage is 0%, so the description must compensate. It explains hours_ahead with default (24) and max (48), and describes the return value as a list of hourly forecasts. This adds meaning beyond the schema's minimal information.

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?

The description clearly states the tool provides a CO2 intensity forecast for the UK power grid up to 48 hours ahead. The verb 'get' and resource 'carbon intensity forecast' are specific, and it distinguishes from siblings like get_uk_carbon_intensity (likely current) and find_greenest_time_window (different purpose).

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?

The description explains the parameter hours_ahead with default and max, and states the return format is a list of hourly forecasts. It gives a use case: planning energy-intensive tasks. However, it does not explicitly compare to sibling tools or state when not to use it.

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