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

Annotations already cover the read-only and idempotent safety profile. The description adds behavioral nuance beyond annotations by warning that avg_time_to_power_months and avg_queue_wait_months are DIFFERENT measurements and that avg_queue_wait_months is a proxy from live queue depth. This prevents the agent from quoting the wrong metric. It also documents the return shape, though an output schema appears to 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?

Dense but efficiently structured: trigger condition, example, parameter constraints, return shape, critical measurement caveat, and exclusions each earn their place. The most important information (when to use and what it compares) is front-loaded, and the caveats are clearly highlighted.

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?

Covers every context an agent needs for correct invocation: the use case, the alternative tools for adjacent scenarios, the exact valid input domain, the return structure, and the subtle measurement distinction. With one required parameter and a highly specified description, nothing essential is missing.

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 description coverage is 100%, so the parameter is already documented as a comma-separated list with valid values. The description adds value by repeating the 2-4 max constraint, spelling out the 7 valid ISOs, and giving a concrete example call (compare_isos isos='PJM,ERCOT,CAISO').

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 opens with a specific trigger ('Use when a user wants a side-by-side of 2-4 ISO grids') and enumerates exactly what is compared: fuel mix, demand, renewable/gas share, interconnection-queue depth, time-to-power. It also distinguishes itself from get_grid_scoreboard and get_grid_intelligence, making its scope unambiguous.

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?

Explicitly states when to use it ('instead of N sequential get_grid_intelligence calls') and when not to use it ('Do NOT use to rank ALL grids globally (use get_grid_scoreboard) or for the single-ISO deep brief (use get_grid_intelligence)'). The example with PJM, ERCOT, CAISO further ground the intended use case.

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