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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so no contradiction. The description adds context: returns a 'genuine statewide total', substring matching for county, default behavior for year and quarter. It does not discuss rate limits or auth, but with high annotation coverage, the description adds meaningful nuance.

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 a single paragraph that front-loads the purpose and then adds detail. It is clear and every sentence adds value, though slightly verbose. Could be tightened but still excellent.

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 no output schema, the description fully explains what the output contains (counts per fuel type, share, statewide total) and provides example queries. All 4 parameters are documented, and usage guidance is thorough. The description is self-contained and leaves no obvious 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?

Schema coverage is 100%, and the description adds value beyond schema: explains county uses substring match, quarter defaults to latest filed, year defaults to 2026, and limit max 70 with note that PA has 67 counties. The examples also show typical usage.

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 uses a specific verb ('measure') and resource ('electric-vehicle adoption in Pennsylvania from PennDOT data'). It clearly states what it returns (counts by fuel type per county, share, statewide total) and distinguishes from siblings by explicitly naming pa_dmv_ev_adoption_by_zip and pa_dmv_vehicle_registrations.

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 provides explicit when-to-use guidance (e.g., 'how many EVs are registered in Pennsylvania', 'EV share in Allegheny County') and clearly states when not to use by directing to sibling tools for ZIP-code detail or full fleet data. It also explains quarter-over-quarter growth via year/quarter arguments.

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