get_random_by_topic

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It states only that the result is random and topic-filtered, but does not explain how topics map to content, what happens on invalid or unknown topics, whether results are reproducible, or what the response structure looks like.

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, well-formed sentence with no filler. It front-loads the core action and the key qualifier, making it immediately parseable by an agent.

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 single-parameter read-like tool, the description captures the essential purpose, but it omits practical context such as how topic slugs are obtained or validated and what a 'text segment' looks like. With no output schema and no annotations, a bit more context would improve completeness, yet the tool is simple enough that the current description is minimally viable.

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 already provides 100% coverage for the single parameter, describing 'topic' as 'The topic slug.' The description adds little beyond restating that the result relates to a topic, so the baseline of 3 applies because the schema handles parameter documentation adequately.

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 identifies the verb ('Get'), the resource ('a random text segment'), and the scoping criterion ('related to a specific topic'). It is specific enough to distinguish this from a general random-text tool, though it does not explicitly name the sibling alternatives.

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 implies when to use the tool—when a topic-related random segment is needed—but gives no explicit guidance on when to prefer it over get_random_text or other siblings. There are no exclusions, prerequisites, or alternative-selection cues beyond the topic qualifier.

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