get_base_apitools_UserArticlesTweetsGet UserArticlesTweets tweets info 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. It adds only 'Billing per call: 1 Credits' and does not disclose authentication expectations, return behavior, pagination, side effects, or failure semantics.
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 and front-loaded, with no wordy filler. The first sentence repeats most of the tool title, but it is still concise and includes useful billing context.
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 5-parameter tool with no output schema and no annotations, this description is far too sparse. It lacks return behavior, use cases, auth/model expectations, pagination details, and any information that would let an agent safely sense and invoke the tool 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 just 20%; only auth_token has a real description. The tool description neither explains cursor, userId, proxyUrl, resFormat, nor how they relate to getting UserArticlesTweets, so the agent must guess even basic parameter usage.
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 says 'Get UserArticlesTweets tweets info' and 'Group: userTweets', giving a clear verb and resource category. However, it does not explain exactly what UserArticlesTweets returns or how it differs from similar 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?
No 'when to use' guidance is present. The description provides a group label and billing metadata only, which does not help an agent decide between this tool and the many sibling tweet/user-timeline tools.
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.