list_conversations

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

No annotations are provided, so the description carries the full burden. It states it 'Returns: conversation list with metadata', which gives basic output information, but lacks critical behavioral details: it doesn't mention pagination behavior (implied by limit/offset parameters but not explained), authentication requirements, rate limits, error conditions, or whether it's read-only (though 'Lists' implies it). For a tool with 4 parameters and no annotation coverage, this is insufficient.

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 extremely concise (two brief sentences) and front-loaded with the core purpose. Every word earns its place: the first sentence states what it does and returns, the second provides usage guidance. There's no redundancy or unnecessary elaboration.

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 complexity (4 parameters, no annotations, no output schema), the description is incomplete. It covers the basic purpose and usage context but misses parameter explanations, detailed behavioral transparency (like pagination or auth), and output specifics beyond 'conversation list with metadata'. For a listing tool with filtering parameters, this leaves significant gaps for an AI agent to use it 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?

Schema description coverage is 0%, so the schema provides only parameter names and types without descriptions. The description adds no parameter semantics whatsoever—it doesn't explain what 'agent_id', 'status', 'limit', or 'offset' mean, their expected formats, or how they affect the listing. With 4 undocumented parameters, the description fails to compensate for the schema gap.

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 verb ('Lists') and resource ('agent conversations'), making the purpose immediately understandable. It distinguishes from sibling tools like 'get_conversation' (which retrieves a specific conversation) by indicating it returns a list. However, it doesn't explicitly differentiate from other list tools like 'list_agents' or 'list_phone_numbers' beyond the resource type.

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 includes a 'Use when:' clause ('browsing conversation history'), which provides clear context for when to invoke this tool. This helps distinguish it from 'get_conversation' (for detailed view of a single conversation). However, it doesn't specify when NOT to use it or mention alternatives like filtering conversations by other criteria not covered by the parameters.

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