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

With no annotations, the description carries the burden of behavioral disclosure. It does reveal what the tool returns (slugs and summaries) and that it does not return full article content, but it omits other behavioral details such as fuzzy matching behavior, result ordering, pagination, or side-effect guarantees.

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 two tight sentences with no filler. The search scope is front-loaded, and the follow-up tool call is the very next piece of information an agent needs.

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 simple search tool with an output schema and a clearly named sibling (read_topic), the description covers the core workflow and return semantics. The main missing piece is any guidance distinguishing this from discover_topics or clarifying how limit affects the result set.

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%, so the description must compensate. It adds meaning for the query parameter by framing the search as keyword-based over titles and summaries, and the optional limit parameter has an understandable name and default. Still, limit behavior is not explicitly described.

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 states a specific verb ('Keyword search') and a precise resource scope ('Smartipedia article titles and summaries'). It also differentiates from the read_topic sibling by noting that this tool returns only slugs and summaries, not full articles.

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 gives a clear workflow: search for topics, then call read_topic with a slug to get the full article. It does not explicitly contrast this with discover_topics or state when not to use it, so it stops short of full exclusion guidance.

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