verify_index

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It explicitly states that the clone is destroyed afterwards always, the operation takes tens of seconds to minutes, and it fails loudly when measurement is impossible. This is substantial, honest transparency beyond basic mutation/read hints.

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 front-loaded with the core purpose and verdict, then follows with evidence details and operational requirements. Every sentence delivers relevant information—purpose, evidence types, prerequisites, execution time, and failure behavior—with no wasteful 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 complex tool with no annotations, the description covers prerequisites, execution time, side effects (clone destruction), failure modes, and verdict logic. An output schema exists, so return values need not be described. However, the optional parameters sqls, queryids, and regression_top_n are not explained in relation to the tool's logic, leaving some invocation ambiguity.

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 0%, so the description must compensate, but it does not clearly explain parameter meanings. Terms like 'candidate index' and 'top production queries' only loosely map to index_def and queryids/sqls; regression_top_n and profile are not explicitly tied to their parameters. The schema names provide some clues, but the description adds little direct parameter guidance.

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 opens with 'MEASURE a candidate index on a disposable data-bearing clone and return a verdict,' which identifies a specific action, resource, and outcome. It distinguishes itself from siblings by stating 'This is the only tool that produces evidence' and enumerating the exact evidence produced.

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 clearly states when this tool should be used (when evidence is needed) and calls out prerequisites (clone_provider='docker', Docker running). It implicitly differentiates from sibling tools by claiming exclusivity for evidence production, though it does not explicitly cite alternative tools or when-not-to-use conditions.

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