get_base_apitools_highlightsV2Highlights Tweets by V2 Group: Tweets. 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, and the description does not disclose any behavioral aspects such as side effects, required authentication (beyond the auth_token parameter), rate limits, or whether it mutates data. The only hint is the billing note, which is not behavioral.
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 very short and avoids verbosity, which is positive. However, it is so minimal that it sacrifices essential information, making it less useful. The inclusion of 'Billing per call' is extraneous to the tool's function.
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 lack of annotations, sparse schema descriptions, and minimal description, the tool is far from complete. The description provides almost no context about input requirements, output format, or expected behavior, making it inadequate for an agent to use confidently.
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?
Of the five parameters (cursor, userId, proxyUrl, resFormat, auth_token), only auth_token has a description in the schema. The others are completely undocumented, and the description does not explain their purpose or format. This fails to provide meaningful semantics for most parameters.
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 'Highlights Tweets by V2' is vague and lacks a clear verb (e.g., 'get', 'fetch'). It does not specify what operation is performed or what 'Highlights' means in this context. The title adds little clarity. It does not distinguish from numerous sibling tools that also handle tweets.
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. Given the large list of sibling tools (e.g., tweetTimeline, userTweetsV2), the description provides no criteria for selection or context of use.
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.