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 value by specifying the authentication requirement (OAuth token with tweet.write scope) and the character limit (max 280 characters), which aren't in the schema. However, it doesn't cover other important behaviors like rate limits, error conditions, or what happens on success (e.g., returns tweet ID), leaving gaps in transparency.

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 authentication requirements, then parameter details in a clear bullet-like format. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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 write operation with 2 parameters), no annotations, and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the main action, authentication, and parameter semantics. However, it could be more complete by mentioning potential side effects (e.g., tweet visibility) or linking to sibling tools for context, keeping it from a perfect score.

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?

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics beyond the schema by explaining that 'text' is tweet text with a max of 280 characters and 'reply_to' is an optional tweet ID to reply to. This clarifies the purpose and constraints of both parameters effectively, though it doesn't cover all possible edge cases (e.g., format of tweet ID).

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 verb ('Post') and resource ('a new tweet'), making the purpose immediately understandable. It distinguishes from siblings like x_delete_tweet or x_get_tweet by specifying creation rather than deletion or retrieval. However, it doesn't explicitly differentiate from similar tools like x_send_dm (which also posts content), so it's not a perfect 5.

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 usage context by mentioning the required OAuth token and scope, which implies when authentication is needed. However, it lacks explicit guidance on when to use this tool versus alternatives like x_send_dm for direct messages or x_reply_to_tweet (if it existed), and doesn't specify prerequisites beyond authentication. This leaves room for ambiguity in tool selection.

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