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

Annotations already declare readOnlyHint=true, and the description adds valuable behavioral context: 'refreshed hourly,' '48-hour Open-Meteo forecast,' and 'forward-looking, not lagged capacity factors.' Listing the return fields further increases transparency beyond the annotation.

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 compact, with the main purpose and output fields front-loaded, followed by usage guidance and an update frequency note. Every sentence earns its place; no fluff or redundant details.

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?

Despite having no output schema, the description compensates by naming the output fields and explaining the score's meaning and data source. The optional 'days' parameter is fully documented in the schema, so the description is complete for an agent to select and invoke the tool correctly.

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?

The schema description covers 100% of the single 'days' parameter, including its purpose, range, and Gold tier requirement, so the tool description correctly leaves parameter details to the schema. Baseline 3 applies because the schema does the heavy lifting.

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 it 'Returns a 0-100 renewable resource availability score for the ERCOT/Texas grid' with specific output fields (availability_score, avg_wind, avg_radiation), and distinguishes itself by clarifying 'forward-looking, not lagged capacity factors.' The verb+resource+scope is specific and unambiguous, even among many sibling tools.

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?

Explicit when-to-use guidance is provided: 'Call when the user asks about wind/solar conditions, renewable generation, ERCOT supply, or grid weather, or when timing electricity-price forecasts, day-ahead virtual offers, or LMP spike-risk windows.' It lacks explicit when-not-to-use or named alternatives, but the contexts are clear and actionable.

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