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

Annotations declare readOnlyHint and idempotentHint, and the description adds behavioral details: it returns total word count, unique words, top 20 with counts and percentages, and sorting order. This goes beyond the annotations and gives a clear picture of what the tool outputs.

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 three sentences, front-loads the purpose, and provides specific return details. It includes a source link which is not clutter. Every sentence contributes useful information without redundancy.

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 read-only tool with a clear return contract and an output schema present, the description is complete. It covers what the tool does, what it returns, and the optional stop-word behavior. Nothing essential is missing for an agent to use it 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%, so both parameters are documented. The description's mention of stop words largely repeats the schema's description. It adds minimal extra meaning, so the baseline of 3 is appropriate.

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 counts word frequency in a block of text, sorted by frequency, and returns specific metrics. It uses a specific verb 'Count' and resource 'word frequency', and distinguishes itself from sibling tools like hopi_word_counter by emphasizing the frequency distribution and top-20 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 gives clear context: it's for analyzing word frequencies. It does not explicitly mention alternatives or when not to use it, but it provides enough context for an agent to understand its purpose. The optional stop-word filtering is mentioned, but no explicit routing to siblings is provided.

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