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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description does not need to add much. It mentions the return fields (common characters, unique, etc.), which adds some context beyond annotations, but not significantly.

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 well-structured with brief intro, Args list, Returns, and an example. It is concise and front-loaded, though slightly verbose with the 'Useful for...' line. Overall efficient.

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 3 parameters, 100% schema coverage, good annotations, and no output schema, the description covers all necessary context: what the tool does, parameters, return values, and an example. It is complete for an agent to use correctly.

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 coverage is 100%, and the description restates parameter names and types. It adds the default value for case_sensitive, which is already in the schema. No additional meaning beyond what the schema 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 it compares letter frequencies between two texts, with a specific verb-resource combination. It distinguishes from siblings like count_letter and letter_frequency by emphasizing comparison of two texts.

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 mentions it is useful for analyzing similarity or differences, implying when to use. It does not explicitly state when not to use or list alternatives, but the example and context provide adequate guidance.

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