List conversations

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

The description warns that it reads the local Teams cache, not the full server archive, which is a critical behavioral trait. With no annotations provided, this disclosure adds value. It does not mention any destructive actions, which is consistent with a read operation.

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 cover purpose, filters, and a critical caveat. Every sentence is meaningful and efficient, front-loading the main function.

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?

The description lacks details about the return format or fields, which would help with no output schema. The caveat adds context, but overall completeness is moderate for a tool with 6 parameters.

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 83%, so baseline is 3. The description lists filter options but does not add significant detail beyond the schema. It groups parameters but does not clarify formats or defaults beyond what the schema provides.

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 lists conversations with default newest N and filtering by kind/participant/title/time. The verb 'list' and resource 'conversations' are specific, and the tool is distinct from siblings like search or read_messages.

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 browsing conversations with default and filter options. However, it does not explicitly state when not to use it or compare to alternatives, though sibling tools suggest different purposes.

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