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

The description adds meaningful behavioral context beyond the annotations: it reveals the topic is not persisted to the KG, and that website suggestions produce a visible contribution reward. This complements the readOnlyHint=false and destructiveHint=false annotations without contradiction, though it could go further by mentioning moderation or visibility.

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?

Four short sentences, each earning its place: the action, the intended use cases, the crucial KG non-persistence note, and the reward side effect. The most important information appears first, and there is no redundant text.

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 the rich output schema and complete parameter descriptions, the description covers the key selection and invocation facts: when to use it, what it does, what side effects occur, and what it avoids. It could be more complete by addressing immediate public visibility or approval, but those are not essential for a correct call.

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 description coverage is 100%, so the schema already documents all nine parameters in detail. The description adds only a small bit of nuance about site_suggestion earning a reward, which is also stated in the schema's kind description. No compensation for undocumented parameters is needed.

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 names a specific verb ('Create') and resource ('public discussion topic') and enumerates concrete use cases: substantive question, comparison, missing catalog area, or website suggestion. It also distinguishes the tool from knowledge-graph-related tools by explicitly stating the topic is not written to the KG.

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 clearly states when to use this tool by listing appropriate content types, which sets expectations for calling create_topic. It does not explicitly name alternative tools or give when-not-to-use guidance, but the use-case list is enough to route an agent in most situations.

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