hbr_topic

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

With no annotations, the description carries the behavioral disclosure burden. It does disclose that only public articles are returned, that results are the newest, and that it returns one topic archive page. However, it does not mention pagination behavior, response format, or any rate limits or failure modes, so the behavioral picture is only partially complete.

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 sentences with no filler: the first states the action and result, the second explains the parameter format and points to the authoritative source for valid values. It is front-loaded and every sentence earns its place.

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 tool with no output schema, the description is nearly complete: it tells the agent what the tool returns, the nature of the content, and how to obtain valid parameter values. It could be improved by briefly noting the response structure or pagination, but those are not critical for correct invocation.

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 coverage is 100%, so the schema already documents the single 'topic' parameter. The description adds real value by defining the expected format as '<group>/<slug>' and directing the agent to hbr-categories for the complete value space, which goes beyond the schema's generic 'Harvard Business Review topic slug'.

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 and resource ('Get Harvard Business Review topic archive') and clarifies the exact output: the newest public HBR articles on one topic archive page. It also distinguishes itself from hbr_categories by explicitly referencing it for the valid value space, so an agent can tell this tool apart from related siblings.

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 provides clear context for when to use the tool: when you need articles from a specific HBR topic archive page. It points to hbr-categories for the full known value space, which is an explicit prerequisite, though it does not state when-not-to-use or directly compare with hbr_article or hbr_headlines.

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