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 with full message history' and includes a 'WARNING: Uses unofficial API,' which adds some context about reliability or potential risks. However, it doesn't cover other important behavioral aspects such as rate limits, authentication requirements, error handling, or whether the operation is read-only or has side effects, leaving significant gaps.

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 well-structured and front-loaded, with the core purpose stated first, followed by parameter details and a warning. Each sentence adds value: the first defines the tool, the second explains the parameter, the third clarifies the return, and the fourth provides a critical warning. There's no unnecessary fluff, making it efficient, though it could be slightly more concise by integrating the return statement into the first sentence.

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 tool's moderate complexity (a read operation with one parameter) and the presence of an output schema (which handles return value documentation), the description is reasonably complete. It covers the purpose, parameter source, and a key warning. However, without annotations and with sibling tools like 'get_conversation_details', it lacks guidance on tool selection and deeper behavioral context, making it adequate but not fully comprehensive.

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 input schema has 0% description coverage, but the description compensates by explaining that 'conversation_id' is a 'Conversation ID (from get_conversations results).' This adds meaningful context beyond the schema's type definition. However, with only one parameter, the baseline is high, and the description doesn't provide additional details like format examples or constraints, so it meets but doesn't exceed expectations.

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: 'Get full message history for a specific conversation.' It uses a specific verb ('Get') and resource ('full message history for a specific conversation'), making the function unambiguous. However, it doesn't explicitly differentiate from its sibling 'get_conversation_details', which appears to serve a similar purpose, preventing a perfect score.

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 minimal guidance: it mentions that 'conversation_id' should come 'from get_conversations results', which is a useful prerequisite. However, it lacks explicit instructions on when to use this tool versus alternatives (e.g., 'get_conversation_details' or other conversation-related tools), and it doesn't specify any exclusions or conditions for use beyond the warning about the unofficial API.

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