Twitter MCP Server

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 states the tool retrieves profile information but does not specify whether this is a read-only operation, if it requires authentication, rate limits, error handling, or what the output format looks like (e.g., JSON structure). This leaves significant gaps for an AI agent to understand 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 front-loaded with the core purpose in the first sentence, followed by a concise 'Args' section that efficiently explains the parameter. Every sentence earns its place without redundancy, 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 tool's low complexity (1 parameter, no nested objects) but lack of annotations and output schema, the description is partially complete. It covers the purpose and parameter well, but fails to address behavioral aspects like output format, error cases, or authentication needs, which are important for a tool interacting with an external API like Twitter/X.

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 schema description coverage is 0%, so the description must compensate. It provides clear semantics for the single parameter 'username,' explaining it is a Twitter username without the @ symbol and giving an example ('elonmusk'). This adds essential meaning beyond the basic schema, fully documenting the parameter.

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 a specific verb ('Get') and resource ('Twitter/X user profile information'), and distinguishes it from siblings like get_twitter_user_by_id (which uses ID instead of username) and get_twitter_user_tweets (which retrieves tweets rather than profile info).

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 implies usage context by specifying 'by username,' which helps differentiate it from get_twitter_user_by_id. However, it lacks explicit guidance on when to use this tool versus alternatives like get_twitter_user_by_id or search_twitter, and does not mention any prerequisites or exclusions.

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