get_trending_topics

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the two extraction modes, references the config/frequency_words.txt source, and states that the return is a JSON frequency list. It does not discuss side effects, but for a getter-style statistics tool the disclosed behavior is sufficient.

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 Examples sections. Every sentence adds value, the main purpose is front-loaded, and the examples are concise illustrations rather than repetition.

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 tool with three optional parameters and no annotations, the description is complete: it defines all parameters, their defaults, mode semantics, extraction sources, return format, and usage examples. Nothing an agent needs to call the tool correctly is missing.

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?

The schema provides no descriptions at all, yet the description documents every parameter: top_n with its default, mode with both allowed values and their meanings, and extract_mode with both options plus the config file dependency. Examples reinforce the parameter combinations, fully compensating for the 0% schema coverage.

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 function: retrieving hot-topic frequency statistics, and the examples make the purpose concrete. It does not explicitly distinguish itself from siblings such as analyze_topic_trend, so it misses the top score, but the verb+resource combination is specific.

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 by explaining the mode options and showing concrete examples for preset keywords and auto extraction. It does not explicitly state when not to use this tool or name alternatives, so the guidance is strong but not fully exclusionary.

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