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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that input is analyzed in memory and never stored, and details the output (DROP statements with write-amplification cost). No contradictions.

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 covers purpose, output specifics, usage guidance, and safety. It is front-loaded with the key result. Slightly long but each sentence adds value.

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 complexity (three redundancy types), the presence of an output schema, and the annotations, the description fully covers input, output, and safety. No 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 description coverage is 100%, so the schema already documents each parameter. The description adds value by giving concrete examples for ddl (SHOW CREATE TABLE, mysqldump, pg_dump) and explaining how engine and version affect output (DROP syntax, version-dependent verdicts).

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 identifies duplicate and redundant indexes from schema DDL, listing specific categories (exact-duplicate, prefix-redundant, secondary indexes restating PK). The title and description distinguish it from sibling tools like sixta_analyze_query or sixta_analyze_schema_change.

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 explicitly says when to use ('when user pastes CREATE TABLE/schema' or asks about redundant indexes) and that no connection is needed. It does not explicitly state when not to use, but the context is clear.

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