Twitter MCP Server

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 the tool retrieves events with a limit (default 20, max 100), which adds some context, but lacks critical details like rate limits, authentication requirements, data freshness, or error handling. For a tool accessing external API data with no annotations, this is a significant gap.

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 purpose clearly, followed by a structured 'Args:' section. There's no wasted text, and each sentence earns its place by explaining parameters. Minor improvement could be made by integrating parameter details more seamlessly, but it's efficient.

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 3 parameters with 0% schema coverage and no output schema or annotations, the description is moderately complete. It covers parameter meanings well but lacks behavioral context (e.g., API constraints, error responses) and output details. For a tool that fetches event data from Twitter/X, more information on data format or limitations would enhance completeness.

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 successfully explains all three parameters: 'username' (Twitter username without @), 'is_follow' (True for followers, False for unfollowers), and 'limit' (default and max values). This adds meaningful semantics beyond the bare schema, though it doesn't cover edge cases like invalid usernames.

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: 'Get follower/unfollower events for a Twitter/X user.' It specifies the verb ('Get') and resource ('follower/unfollower events'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'get_twitter_kol_followers' or 'get_twitter_user', which might also retrieve follower-related data.

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. It doesn't mention sibling tools or contexts where other tools might be more appropriate, such as using 'get_twitter_user' for general user info or 'get_twitter_kol_followers' for specific follower types. Usage is implied through parameter descriptions but not explicitly stated.

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