local_authority

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

Annotations already establish readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so safety is covered; the description adds genuinely new context by disclosing the 10-credit cost and the shape of the result (sub-scores with score/max/detail plus percentile). It does not mention permission or quota nuances beyond the flat credit price, keeping it short of a 5.

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?

Four short sentences, front-loaded with the trigger condition and immediately followed by return shape, then a tracking hint and cost. No filler, though the 'Good single metric to track over time' line is the softest and could be folded into the usage sentence.

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?

With an output schema present, the description needn't explain return values, yet it summarizes them usefully; combined with annotations covering safety and the disclosed credit cost, an agent has enough to decide and call correctly. The only gap is no guidance on when a more granular audit sibling is preferable.

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 business_name, location, and keyword are already documented at the field level. The description adds nothing about parameter behavior (e.g., how keyword alters the score versus defaulting to the business name), which is the baseline-3 case where the schema carries the load.

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 states a specific verb+resource ('calculating a composite 0-100 local authority score') and enumerates the output components (ranking, reviews, profile, citations, percentile), so an agent knows exactly what this produces. It does not explicitly name a sibling it is not (e.g., local_audit or reputation_audit), so differentiation from the many audit tools is only inferable.

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?

'Use when calculating a composite 0-100 local authority score' and 'Good single metric to track over time' imply the usage context (a rollup/tracking metric versus detailed point-in-time audits), but there is no explicit when-not condition or named alternative to select instead.

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