show_kernel_topic

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

With no annotations provided, the description carries the full disclosure burden, but it only implies a read operation through the word 'show'. It discloses nothing about the response format, error behavior for invalid topic_ref values, whether the full discussion is returned, or any prerequisites. It does not contradict any annotations, but it adds almost no behavioral context.

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?

At five words, the description is maximally concise and front-loaded with no filler. However, the brevity comes at the cost of substantive content that other dimensions penalize, so it is efficient in structure but under-informative in practice.

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 one required parameter, no output schema, and no annotations, the description is insufficiently complete. An agent knows only that it should 'show a kernel discussion topic' but has no idea what the response will contain, what topic_ref should look like, or how this fits into the flow of kernel discussion workflows.

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 0% — the topic_ref property's description is an empty string. The tool description does not compensate in any way: it never mentions topic_ref, its format (ID, slug, URL, or numeric), or how an agent can obtain a valid value. The agent must guess the parameter's semantics entirely from its name.

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 uses a specific verb ('show') and resource ('kernel discussion topic'), clearly identifying this as single-topic retrieval rather than a list operation. The 'kernel' qualifier implicitly separates it from show_dataset_topic, show_competition_topic, and show_forum_topic, but differentiation is implicit via naming, not explicit, and it is ambiguous whether 'show' returns the topic metadata, the full thread, or comments.

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?

No guidance is given on when to use this tool versus alternatives. There is no mention of list_kernel_topics as the way to obtain a topic_ref, no exclusion of the other show_*_topic siblings, and no context about which resource type this applies to beyond the name itself.

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