get_base_apitools_userTweetsV2Get UserTweets by V2 Group: userTweets. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| cursor | No | ||
| userId | No | ||
| proxyUrl | No | ||
| resFormat | No | ||
| auth_token | No | web twitter login cookie info 'auth_token' |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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 discloses no behavioral details such as authentication requirements (auth_token), pagination via cursor, or expected return format, leaving the agent completely in the dark beyond the tool's name.
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 short, but its only substantive sentence is a tautology and the billing note is marginal. This is under-specification rather than effective conciseness; the sentences do not earn their place by adding useful content.
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?
With five parameters, no required fields, and no output schema, a usable description must cover parameter semantics, expected behavior, and use context. This description provides none of that, making it nearly impossible for an agent to invoke the tool correctly or understand its results.
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 only 20% (only auth_token has a description), so the description must compensate by explaining the parameters. It provides no information about cursor, userId, proxyUrl, resFormat, or auth_token, failing to add any meaning beyond the schema's minimal hints.
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 repeats the tool name/title ('Get UserTweets by V2') and adds only a grouping label and a billing note. It does not describe the operation's scope or distinguish it from timeline siblings like userTimeline or tweetsTimelineV2, making it essentially a tautology.
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?
There is no guidance on when to use this tool versus the many similar Twitter timeline tools, nor any exclusions, prerequisites, or alternative tool references. The description only mentions a billing credit, which does not help with tool selection.
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.
The set is full of confusing variants such as get_/post_ prefixed duplicates of the same endpoints, competing V1/V2 versions of the same action (e.g., followersList vs. followersListV2), and poorly described tools like CommunitiesSearchV2 and getCt0 that give no clear unique purpose. Agents would frequently need to guess between similar tools for a single task.
Naming is chaotic, mixing camelCase (getDMS, likeV2), PascalCase (CreateNoteTweet, CommunitiesMemberV2), and inconsistent prefixes (gettools_*, get_*, post_*) with duplicated operations. The 'get_/post_' prefixes appear to indicate API method rather than action, but they are applied inconsistently, with some tools appearing under both and others only once. There is no predictable verb_noun pattern throughout.
With 107 tools, the server is extremely large, far exceeding the 50+ threshold for extreme mismatch, and this count is inflated by duplicates (many get_/post_ twins) and overlapping V1/V2 variants. Even the unique tool set is likely around 60-70, which is still an unwieldy surface for an agent to negotiate. This severely disrupts coherence.
The tool set covers most core Twitter/X domains: tweets, likes, retweets, follows, DMs, search, communities, lists, and profile management. However, it is cluttered with duplicates and lacks some obvious pieces like mute/unmute operations or a direct 'update tweet' action, and several tools appear to be thin wrapper variations of the same endpoint. Coverage is broad but not cleanly organized.