list_conversations

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains the result ordering, the exact fields returned, and the limitation that it only provides previews, not the full messages. This is substantial, though it does not explicitly state that the operation is side-effect-free, but the read-only nature is strongly implied.

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 three short sentences: the first states the primary purpose and ordering, the second lists return fields, and the third points to the sibling for more detail. Every sentence earns its place, and the most critical information is front-loaded. Zero waste.

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 tool is simple (3 optional params, no nested objects) and an output schema exists, so the description need not detail return structure. It covers the essential behavioral context: what is returned, order, and the boundary with get_conversation. Missing mention of search_conversations is a minor gap, but the description is otherwise complete for an agent to invoke this correctly.

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?

All three parameters (tag, limit, offset) are fully described in the input schema, so the description adds no additional parameter semantics. Per the rubric, when schema coverage is high, a baseline score of 3 is appropriate; the description does not detract but also does not enrich.

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 opens with a clear verb-resource pair ('List saved conversations') and a key behavior ('newest first'). It explicitly distinguishes itself from the sibling get_conversation by stating it returns a list with previews rather than full messages, making it easy for an agent to choose between them.

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?

It clearly directs the agent to use get_conversation when full messages are needed, providing a concrete alternative and when-not-to-use guidance. However, it does not mention the close sibling search_conversations, which could be relevant for filtering or query-based retrieval, so coverage of alternatives is incomplete.

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