get_user_aboutFetch the extended 'about' / profile page data for a Twitter/X user by screen name. Returns extra profile metadata beyond what get_user_info gives (when available). Use get_user_info first; only call this if you need additional about-page fields.
| Name | Required | Description | Default |
|---|---|---|---|
| userName | Yes | Twitter/X screen name without @ — fetches the user's profile 'about' / bio page. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral nuance: the extra metadata is only available 'when available,' and the tool returns data beyond what get_user_info provides. It doesn't detail rate limits or failure modes, but the read-only annotations lower that burden.
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?
Three tight sentences: verb and resource, value relative to get_user_info with an availability caveat, and explicit usage order. There is no filler and the core scope is front-loaded.
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?
For a one-parameter, read-only tool, the description sufficiently covers what it does, when to use it, and how it relates to get_user_info. No output schema exists, so return specifics are only described vaguely as 'extra profile metadata,' but that is adequate for selection and invocation.
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 100%: the userName parameter is already described as a Twitter/X screen name without @ that fetches the profile about/bio page. The description only restates 'by screen name' and adds no additional parameter-level meaning, so the baseline 3 applies.
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?
States a specific verb and resource: 'Fetch the extended about/profile page data for a Twitter/X user by screen name.' It explicitly differentiates from get_user_info by saying it returns 'extra profile metadata beyond what get_user_info gives,' so the agent can distinguish the closest sibling.
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?
Gives explicit routing guidance: 'Use get_user_info first; only call this if you need additional about-page fields.' It names the alternative tool and the exact condition for choosing this one.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools cleanly target distinct resources: trends, replies, quotes, retweeters, followers, followings, mentions, and search. However, get_user_info and get_user_about overlap significantly, and get_user_last_tweets vs search_tweets have overlapping capabilities that are only separated by usage warnings.
All tools use a consistent snake_case convention with get_ as the dominant verb, followed by a clear noun target: get_trends, get_tweet_replies, get_user_followers, get_tweets_by_ids. search_tweets is the single intentional exception but follows the same predictable pattern.
12 tools is well-scoped for a read-only Twitter/X data-access server. Each tool covers a distinct major data surface—trends, individual tweet interactions, user profiles, relationships, mentions, and search—without unnecessary bloat.
The set covers the most common Twitter read workflows: user lookup, timelines, search with date ranges, followers/followings, mentions, and engagement metrics like replies, quotes, and retweeters. Obvious gaps like liking users or list-based lookups are missing, but they are not critical to the server's apparent core purpose.