tweetapi_tweet_translateRequires a TweetAPI API key and consumes normal TweetAPI quota. Read-only; one upstream request per call. The model must request pagination cursors explicitly. Translate public tweet text without changing the tweet.
| Name | Required | Description | Default |
|---|---|---|---|
| dstLang | Yes | ||
| tweetId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds several behavioral details beyond the annotations: it requires an API key, consumes normal quota, performs one upstream request per call, and notes that pagination cursors must be explicitly requested. These add context about operational behavior that the annotations (readOnlyHint, idempotentHint, destructiveHint) do not convey. The mention of pagination cursors is somewhat ambiguous but still counts as additional disclosure. No contradiction with annotations.
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 relatively short but not tightly focused. The first sentence mixes API key requirements, quota consumption, read-only status, and an oddly placed instruction about pagination cursors; the second sentence is the actual purpose. It could be restructured to be more direct, but it is not overly verbose.
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 no output schema, the description should clarify what the tool returns (e.g., translated text), but it does not. The pagination cursor instruction is unexplained and creates confusion about whether the output is paginated. The description also does not mention language code format or error conditions. Given the tool's simplicity, the omissions leave important gaps.
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?
The schema has 0% description coverage, so the description must compensate for explaining the parameters. It does not: it never mentions 'tweetId' or 'dstLang' directly, nor does it explain what values are appropriate (e.g., language codes). The only inferable meaning comes from the tool title and schema patterns. This is a significant gap.
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's action: 'Translate public tweet text without changing the tweet.' This is a specific verb+resource, and it is distinct from all sibling tools, none of which perform translation. Even though the description includes extra operational details, the core purpose is unambiguous.
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?
The description provides clear context: it requires a TweetAPI API key, is read-only, and makes one upstream request per call. It implicitly indicates when to use this tool (when translation of a public tweet is needed) and there are no alternative translation tools among siblings. However, it does not explicitly state 'use when...' or mention any exclusions.
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.
Several tools have overlapping or unclear boundaries: tweetapi_user_followers_v2 and tweetapi_user_followers_list both fetch followers with nearly identical descriptions, and tweetapi_docs_search overlaps with tweetapi_endpoint_lookup. Additionally, tweetapi_user_about_account and tweetapi_user_by_username both retrieve user info by username, creating confusion.
All tools share the 'tweetapi_' prefix and follow a consistent resource_specific pattern (e.g., tweetapi_tweet_details, tweetapi_user_followers_ids). The use of lowercase with underscores is uniform, and there is no mixing of camelCase or inconsistent verb styles.
With 38 tools, the server is overstuffed. Many tools are redundant (e.g., three follower variants, three documentation-related tools), which inflates the count beyond what is needed for a read-only Twitter API wrapper. A leaner set of 15-20 tools would be more appropriate.
The read-only API surface is well covered: tweets (details, metrics, quotes, retweets, translate, search), users (profiles, followers, following, subscriptions, verified followers), lists, communities, and spaces. Minor gaps exist (e.g., no direct 'get user mentions' or list lookup by slug), but core workflows are fully supported.