get TweetTimeline Detail
get_base_apitools_tweetTimelineget tweetDetail and reply Group: Tweets. Billing per call: 1 Credits.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| cursor | No | ||
| proxyUrl | No | ||
| resFormat | No |
get_base_apitools_tweetTimelineget tweetDetail and reply Group: Tweets. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| cursor | No | ||
| proxyUrl | No | ||
| resFormat | No |
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 full behavioral burden, but it only says 'get tweetDetail and reply Group: Tweets', which implies a GET-like read but reveals nothing about response format, error conditions, rate limits, pagination, cursor behavior, or whether auth is needed. The only behavioral tidbit is billing cost. This is thin for a complex Twitter scraping API tool.
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 at 10 words, which is concise, but it's under-specified rather than efficiently complete. The billing sentence is the only additional context. It doesn't waste words but doesn't include enough substance.
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 tool with 4 undocumented params, no output schema, no annotations, and no param descriptions, the tool description needs to compensate heavily. It doesn't. The presence of siblings like get_base_apitools_tweetReply and get_base_apitools_userTweetReply makes the missing differentiation more costly. Not complete enough for an AI agent to use reliably without hallucinating.
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 0%, so the description bears the burden of explaining parameters, but it doesn't mention any of them. The schema has four parameters (id, cursor, proxyUrl, resFormat) with no descriptions in the schema itself. An agent would have to infer that 'id' is the tweet ID and 'cursor' handles pagination, but there's zero support from the description.
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 states 'get tweetDetail and reply Group: Tweets', which identifies the tool as fetching tweet detail and replies. However, it's terse and doesn't clearly explain what 'Group: Tweets' means. It doesn't mention the likely sibling tool 'get_base_apitools_tweetReply' or differentiate from other timeline tools. The name 'get TweetTimeline Detail' plus 'tweetDetail' indicates a read operation, but purpose is only vaguely conveyed. This is minimally viable but not clear to an agent deciding between a dozen similar tools.
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 sibling tools like userTimeline, homeTimeline, shareTweetReplies, or tweetReply. The description does not specify use cases, required auth, or prerequisites. The billing note 'Billing per call: 1 Credits' is context but not usage guidance. No exclusions or alternatives are mentioned.
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.