Letter Frequency

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds context about the output format (frequency map, sorted list, most/least common) and parameters that affect behavior (case_sensitive, include_spaces). This goes beyond the annotations' safety profile.

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 Args, Returns, and an Example section. It front-loads the main purpose. While it is slightly long, every sentence earns its place and the structure aids readability.

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?

Despite no output schema, the description fully explains the return values (frequency map, sorted list, most/least common characters) and provides a detailed example. All 5 parameters are explained, and the annotations cover safety and idempotence. The description is complete for this task.

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% with descriptions for all 5 parameters. The description adds value by providing a concrete example ('hello' case) and clarifying the return structure (frequency map, sorted list, most/least common), which helps interpret parameter effects.

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 purpose: 'Get frequency distribution of all characters in text.' It distinguishes itself from siblings like 'count_letter' and 'count_letters' by providing a full distribution rather than a single count, and the example further clarifies the output.

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 provides a clear function but does not explicitly mention when to use this tool versus alternatives like 'count_letter' or 'analyze_sentence'. It implies usage through the detailed description but lacks explicit guidance on exclusions or when not to use.

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