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 the OAuth requirement, which is useful, but fails to describe other critical traits such as whether the action is reversible, rate limits, error conditions, or the response format (though an output schema exists). 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 highly concise and well-structured: the first sentence states the purpose, the second provides a prerequisite, and the third documents the parameter. Every sentence adds value without redundancy, making it easy to scan and understand 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 tool's moderate complexity (a mutation action with authentication needs), no annotations, and an existing output schema, the description is partially complete. It covers the purpose and parameter but lacks details on behavioral aspects like side effects or error handling. The output schema mitigates some gaps, but overall completeness is only 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 explicitly documents the single parameter ('tweet_id: ID of the tweet to like'), adding meaning beyond the input schema, which has 0% description coverage. However, it does not provide additional context such as format examples or constraints, so it only partially compensates for the schema's lack of detail.

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 ('Like a tweet') and the resource ('a tweet'), making the purpose immediately understandable. However, it does not explicitly differentiate this tool from sibling tools like 'x_liked_tweets' (which likely lists liked tweets) or 'x_get_tweet' (which retrieves tweet details), missing an opportunity for full sibling distinction.

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 includes a prerequisite ('Requires OAuth token'), which provides some context for when authentication is needed. However, it offers no guidance on when to use this tool versus alternatives (e.g., when to like vs. bookmark or delete a tweet) or any exclusions, leaving usage decisions ambiguous.

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