list_topics

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

No annotations and no output schema, so the description carries the disclosure burden; it does usefully enumerate what the response contains (descriptions and post counts for topics, top hashtags). It does not state that this is a read-only operation, whether it is paginated or cached, or how large the result set may be.

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?

Two compact sentences, return payload front-loaded and the recommended action second; nothing is wasted.

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?

With no annotations and no output schema, the description does cover the return shape adequately, but it leaves the only parameter unexplained and gives no sense of result size or ordering, which matters for a discovery tool feeding search_posts.

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 single parameter top_hashtags has 0% schema description coverage and a default of 150. The description's phrase 'most used hashtags' only obliquely implies this is a count/limit parameter and never states that the integer controls how many hashtags are returned.

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 is a noun list of returned data ('topics, post kinds, availability values... plus hashtags') rather than a verb+resource statement, so the agent must infer this is a lookup/list tool. The second sentence clarifies its role as a filter-discovery helper, which rescues it from tautology, but it is not a clean purpose statement.

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?

'Call this to pick filters for search_posts' explicitly names the downstream tool and the condition that selects this one over get_post, recent, or stats. It stops short of stating when not to use it or whether it must be called before search_posts.

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