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 mentions 'recent tweets' but doesn't specify what 'recent' means (e.g., time range, pagination), whether it includes retweets or replies, or any rate limits or authentication requirements. This leaves significant gaps in understanding the tool's 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 appropriately sized and front-loaded, with the core purpose stated first followed by parameter details. It avoids unnecessary fluff, but the parameter explanations could be slightly more integrated into the flow rather than listed as 'Args:'.

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 (2 parameters, no annotations, but has an output schema), the description is partially complete. It covers the basic purpose and parameters but lacks behavioral details like response format, error cases, or usage context. The presence of an output schema mitigates some gaps, but more guidance is needed for effective use.

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, which has 0% description coverage. It explains that 'username' is an 'X username (without @) or user ID' and 'count' is the 'Number of tweets (1-100, default 20)', providing crucial context that the schema lacks. However, it doesn't detail error handling or constraints beyond the count range.

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 'Get recent tweets from a specific user', specifying the verb ('Get') and resource ('recent tweets from a specific user'). However, it doesn't explicitly differentiate from siblings like x_home_timeline (general timeline) or x_search_tweets (keyword-based), leaving some ambiguity about its unique scope.

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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention when to choose x_user_tweets over x_home_timeline for user-specific content or x_search_tweets for broader queries, nor does it specify prerequisites like authentication needs or rate limits.

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