Analyze Sentence

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

The description specifies that the tool returns per-word breakdowns with counts and positions, and explains the case_sensitive parameter. This adds context beyond the annotations (readOnlyHint, idempotentHint), which already indicate safety. The description is consistent and informative.

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 efficiently structured with a concise summary followed by a clear Args section and an example. Every sentence is purposeful, and the most critical information is front-loaded.

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 simple tool with three parameters, no output schema, and no nested objects, the description fully covers the tool's purpose, parameters, and expected output. It is complete and adequate for correct invocation.

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%, so the baseline is 3. The description reiterates parameters and provides an illustrative example, which adds some value beyond the schema descriptions but does not significantly enhance parameter meaning.

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: analyzing a sentence word-by-word for a specific letter, showing per-word counts. The example reinforces the purpose and distinguishes it from sibling tools like count_letter which likely provides a total count.

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?

No explicit guidance on when to use this tool vs. alternatives such as count_letter, letter_frequency, or count_substring. The example implicitly suggests usage but fails to provide context for selection among siblings.

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