get_renewable_summary

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

No annotations present, so the description must cover behavioral traits. It explains the aggregation and return format but lacks details on error scenarios, data availability, or any side effects. The tool is likely read-only, but this is not explicitly confirmed.

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 structured with clear sections (Args, Returns, Examples) and front-loads the core purpose. It is slightly verbose due to the examples, but each section adds value. One or two sentences could be trimmed, but overall efficient.

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 only 2 parameters and an output schema (though not provided in input), the description explains the return as a JSON string with breakdown and percentages. It covers the essential information for using the tool, though it omits potential errors or data gaps.

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?

Input schema has 0% description coverage, so the description compensates well by specifying date format (YYYY-MM-DD), hour format (HH, 00-23), and default hour (12). This adds meaningful semantic information beyond the raw schema types.

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's purpose: 'Get renewable energy generation summary at a specific time.' It lists the specific renewable sources (wind, solar PV, solar thermal, hydro) and includes renewable percentage calculations, making it distinct from siblings like 'get_generation_mix' which likely covers total generation.

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 implies usage for obtaining renewable summary at a precise time, with examples showing how to call it at different hours. It does not explicitly compare to siblings or state when not to use, but the context of renewable-specific aggregation provides clear situational guidance.

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