get_conversation

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool returns conversation details and a full transcript, which is helpful, but it doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication requirements, or error conditions. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 and well-structured, with two clear sentences: one stating the purpose and return values, and another providing usage guidelines. Every word earns its place, and there is no unnecessary information or redundancy.

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 of a tool that retrieves conversation data with three parameters, no annotations, and no output schema, the description is incomplete. It lacks details on parameter meanings, behavioral traits (e.g., read-only status, error handling), and output structure, making it inadequate for the agent to fully understand and use the tool 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?

The schema description coverage is 0%, meaning none of the three parameters (conversation_id, wait_for_completion, include_analysis) are documented in the schema. The description adds no information about these parameters, failing to compensate for the lack of schema documentation. This leaves the agent with no guidance on what these parameters mean or how to use them effectively.

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's purpose with a specific verb ('Gets') and resource ('conversation with transcript'), and distinguishes it from the sibling tool 'get_conversation_transcript' by mentioning it returns both conversation details and full transcript. However, it doesn't explicitly differentiate from other conversation-related tools like 'list_conversations'.

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 provides explicit usage guidance with 'Use when: analyzing completed agent conversations,' which clearly indicates the intended context. It doesn't specify when not to use it or name alternatives, but the context is sufficiently clear for effective tool selection.

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