Trending topics

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

With no annotations provided, the description adds important context by disclosing that it reads the local Teams cache and not the full server archive. However, it does not mention other behavioral traits like whether results are sorted or if pagination is supported.

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 plus a note, all essential. It is front-loaded with the core purpose and scoping, then adds a critical limitation. No wasted words.

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 no output schema and moderate complexity (7 parameters, none required), the description adequately explains purpose, scoping, and the local cache limitation. It could be improved by mentioning the exemplar message structure but is sufficient for agent selection.

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 description adds limited meaning beyond the schema. It mentions 'window' and 'scope' conceptually but does not elaborate on format or edge cases for the parameters.

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 it returns distinctive/trending topics over a window, with scoping to overall, person, or conversation. It distinguishes from sibling tools like read_messages or search by focusing on trending analysis.

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 implies usage for trending topics and mentions scoping, but lacks explicit guidance on when to use this tool vs alternatives like search or list_conversations. No exclusions or prerequisites are stated.

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