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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the agent knows this is a safe, repeatable lookup against a fixed dataset. The description adds scope detail by naming which programs are returned, but says nothing about data currency (rebate amounts change), regional eligibility limits, or return format. Useful context, but not rich beyond what annotations provide.

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?

Two sentences, zero filler, and front-loaded: the what comes before the when. Every clause earns its place, and naming the two specific programs adds real value rather than padding.

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?

For a single-parameter, read-only, no-output-schema lookup, the description is nearly sufficient: it tells the agent what data comes back at a program level, which compensates for the absent output schema. Minor gap is that it does not indicate the lookup is limited to residential/Georgia Power territory or how current the rebate figures are.

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% and the single charger_type enum is fully documented in the schema, including the level2 default. The description mentions EV chargers generally but adds no syntax or behavioral detail about how charger_type changes results, so the schema does the heavy lifting and baseline 3 applies.

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?

States a specific verb (look up) and resource (Georgia EV charger rebates/incentives) and even enumerates the two programs covered, the Georgia Power EV rebate and the state tax credit. The sibling tools are electrical calculations (panel capacity, voltage drop, charger setup recommendation), so this data-lookup tool is unambiguously distinct from them.

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 gives the triggering condition: use when a user asks about EV charger rebates, incentives, or tax credits in Georgia. That is a clear when-to-use statement. It stops short of naming exclusions (e.g., rebates outside Georgia, commercial programs) or alternative tools, which it could have done given the sibling set.

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