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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds meaningful context: returns partial summaries and advises directing users to the URL for full details, which is critical for proper agent guidance.

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 sentences covering purpose, output, parameter usage, and an important behavioral note (partial summaries). It is front-loaded with the key verb and resource, with no extraneous information.

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 tool has three optional parameters, no output schema, and comprehensive annotations, the description covers all aspects: what it returns, how to use parameters, and the nature of the output (partial summaries). It also suggests a follow-up action (send user to URL), ensuring completeness for agent decision-making.

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?

With 100% schema coverage, parameters are well-documented in the schema. The description adds value by explaining usage patterns (omit query to browse, topic biases results) that go beyond purely technical definitions.

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 the tool finds articles answering a 'why is my' question and specifies it returns titles, summaries, and URLs. It distinctly distinguishes itself from siblings (get_article for full content, list_topics for topic slugs) by focusing on search and browse functionality.

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 explains both optional arguments, including the ability to omit query to browse and pass topic to bias results. It implies not to use for retrieving full article content, suggesting the user visit the URL or use get_article instead, though explicit sibling comparisons are not stated.

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