x-mcp

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 fetching 'recent mentions' but doesn't specify time ranges, sorting order, or what constitutes a 'mention' (e.g., replies, tags). It also omits details on rate limits, error handling, or response format, leaving significant gaps for a tool with potential complexity.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the return values look like (e.g., list structure, fields included) or address behavioral aspects like pagination beyond the 'next_token' parameter hint. For a tool fetching social media data, more context on output and constraints is needed.

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 100% description coverage, clearly documenting both parameters ('max_results' and 'next_token') with their types and constraints. The description adds no additional parameter semantics beyond what the schema provides, which is acceptable given the high schema coverage, resulting in a baseline score.

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 action ('Fetch') and target resource ('recent mentions of the authenticated user'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_tweets' or 'get_timeline' that might also retrieve mentions in different contexts, 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 no guidance on when to use this tool versus alternatives like 'search_tweets' or 'get_timeline', nor does it mention prerequisites such as authentication requirements. It simply states what it does without contextual usage instructions.

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