performance_analyze_database_index_usage

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

Annotations are absent, so the description carries full burden. It discloses that the tool examines statistics, identifies missing indexes, and analyzes patterns, but does not clarify if it is read-only or if any modifications occur. The description is adequate but not explicit about side effects.

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 four sentences and includes a 'Returns:' line that may be redundant given the output schema. It could be more concise by removing the returns description.

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 the tool's simplicity (no parameters, output schema exists), the description covers what the tool does and its purpose. It lacks details on error handling or prerequisites, but overall it is sufficiently complete for an analysis tool.

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?

The input schema has no parameters, so schema coverage is 100%. The description does not need to explain parameters. Baseline for zero parameters is 4, which is appropriate.

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 verb ('analyze'), resource ('database index usage'), and outcome ('optimization recommendations'). It distinguishes itself from sibling tools like performance_get_database_performance_status by focusing specifically on index usage.

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 gives a clear use case ('Use this for database tuning') but does not specify when not to use it or mention alternative tools. It lacks explicit guidance on exclusion scenarios.

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