analyze_query_performance

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

No annotations are provided, so the description carries the full burden. It mentions the method (DMVs) and the purpose, but does not disclose whether the operation is read-only, the required permissions, or any potential performance impact. The verb 'analyze' hints at a read-only operation but this is not explicit.

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, succinct sentence that front-loads the action verb and stays focused on the core purpose. Every word contributes value, with no redundancy or filler.

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 tool with no output schema and no annotations, the description is sparse. It does not explain the structure of the returned data, any required privileges, or limitations. While the purpose is clear, the behavioral context is insufficient for an agent to fully understand the tool's execution and results.

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 covers 100% of parameters (topN and schema) with descriptive text and defaults, so the baseline is 3. The description adds no additional meaning beyond what the schema already provides.

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 verb 'analyze', the resource 'query performance', the method 'using execution statistics DMVs', and the goal 'to find slow queries and bottlenecks'. This distinguishes it from sibling tools like get_table_statistics or suggest_index_optimizations.

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 purpose implies when to use the tool (to find slow queries and bottlenecks), but there is no explicit guidance on when not to use it or which alternatives to choose instead. No exclusions or comparisons are provided.

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