get_topic_distribution

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

With no annotations provided, the description carries the full burden but only offers a one-line summary. It does not disclose whether the operation is read-only, the data sources, aggregation details, or performance implications.

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 sentence, which is concise but at the expense of necessary detail. It front-loads the purpose but leaves critical information missing, making it under-specified for reliable use.

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 no output schema, 0% param coverage, and no annotations, the description is severely incomplete. It fails to explain the output format (counts, percentages), the definition of topics, or any constraints, making it nearly impossible 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?

Parameter coverage is 0% in the schema, and the description adds no meaning to 'days' or 'limit'. It does not specify units, allowed values, or how these parameters affect the distribution (e.g., time range, result count).

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 retrieves the distribution of messages across topics, using a specific verb and resource. However, it does not differentiate from similar sibling tools like 'get_language_distribution', leaving ambiguity about what constitutes a 'topic'.

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?

There is no guidance on when to use this tool versus alternatives, prerequisites, or scope. The description lacks any contextual cues about typical use cases or when it is inappropriate.

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