get_base_apitools_userTimelineGet UserTimeline tweets info (same by userTweetsV2) 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?
With no annotations provided, the description carries the full burden of behavioral disclosure, but it only mentions billing and grouping. It does not state that this is a read operation, that auth_token is required, or any potential side effects, rate limits, or error behavior. The description is almost silent on how the tool behaves beyond the basic action.
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 extremely brief, but brevity is not the same as conciseness. The phrase 'same by userTweetsV2' is ambiguous and potentially redundant, and the billing/group info is not the most important context. It lacks a logical structure that front-loads the critical purpose and usage details.
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 has 5 parameters, no output schema, and no annotations, the description is grossly inadequate. It does not explain what the tool returns, how to handle parameters, or any preconditions. The description barely states the function and offers no context to guide an AI agent in invoking it correctly.
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). The tool description adds no parameter semantics at all; it does not explain the roles of cursor, userId, proxyUrl, or resFormat. The description completely fails to compensate for the low schema coverage, leaving parameters ambiguous.
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 retrieves a user's timeline tweets, using the verb 'Get' and resource 'UserTimeline tweets info'. However, it references another tool ('same by userTweetsV2') without clarifying distinctions, and the purpose is not fully differentiated from siblings like userTweetsV2 or tweetTimeline.
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 alternatives. The note 'same by userTweetsV2' implies equivalence but gives no context about prerequisites, exclusions, or when one should be preferred over the other. The description provides no actionable usage direction.
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.