show_dataset_topic

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

With no annotations, the description carries the full burden of behavioral disclosure. 'Show' implies a read-only operation, which is useful, but the description does not reveal any behavioral traits beyond that: no mention of return format, pagination, whether it includes replies, authentication needs, or error behavior. A single verb is thin transparency for an unannotated tool.

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, front-loaded sentence with no filler words. It efficiently communicates the primary action and resource. However, the conciseness borders on under-specification, sacrificing enough detail that it only partially serves the agent. Still, as a structural matter, it is compact and well-ordered.

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 and no output schema, the description should at least explain what topic_ref is and how it relates to a dataset topic. It does neither. The description is insufficient for an agent to confidently construct a valid call, especially given the existence of similar topic tools for other resource types. More context is needed about the expected value of topic_ref and what 'thread' includes.

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 input schema has 0% description coverage, and the tool description does not mention topic_ref at all. The parameter name 'topic_ref' hints that it is a reference to a topic, but no format, source, or usage guidance is provided. With zero coverage in both schema and description, the agent has no semantic grounding for the sole required parameter.

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 states a specific verb and resource: 'Show' a 'dataset topic thread'. The dataset qualifier distinguishes it from sibling tools like show_kernel_topic, show_competition_topic, and show_forum_topic. However, it does not clarify what 'topic thread' entails (e.g., replies, metadata), leaving mild ambiguity about the exact scope.

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 provided on when to use this tool versus alternatives. For instance, there is no mention of how it differs from list_dataset_topics, show_kernel_topic, or show_forum_topic, nor when one should be preferred. The agent must infer usage entirely from the tool name and one-line description.

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