x-ai-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context about handling encrypted conversations and API selection, but doesn't cover other behavioral aspects such as rate limits, authentication needs, error handling, or pagination. This is a moderate effort but incomplete for a read operation tool.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by implementation details and parameter explanations. Every sentence adds value without redundancy, making it efficient and easy to parse.

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, no annotations, and the presence of an output schema, the description is fairly complete. It covers purpose, behavior, and parameters, but could benefit from more explicit usage guidelines or error handling info. The output schema likely handles return values, so this is adequate.

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 description adds meaningful semantics beyond the input schema: it explains that 'conversation_id' is for a DM conversation and 'count' is the max messages to fetch with a default of 50. Since schema description coverage is 0%, this compensates well, though it could provide more detail on ID formats or count limits.

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: 'Read messages from a DM conversation.' It specifies the resource (DM conversation) and verb (read messages). However, it doesn't explicitly distinguish this tool from sibling tools like 'x_read_dm' or 'x_list_dms', which might have overlapping functionality, so it doesn't reach the highest 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 some implied usage context by mentioning automatic detection of encrypted vs. regular conversations and the APIs used. However, it lacks explicit guidance on when to use this tool versus alternatives like 'x_read_dm' or 'x_list_dms', and doesn't specify prerequisites or exclusions, leaving room for ambiguity.

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