tweetapi_user_by_idRequires a TweetAPI API key and consumes normal TweetAPI quota. Read-only; one upstream request per call. The model must request pagination cursors explicitly. Fetch one public user profile by user ID.
| Name | Required | Description | Default |
|---|---|---|---|
| userId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond the annotations: it notes the requirement of an API key and quota consumption, specifies 'one upstream request per call,' and instructs that pagination cursors must be requested explicitly. This is exactly the kind of rate-limit and pagination detail that benefits the agent, and it aligns with the readOnlyHint annotation.
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 concise, with each sentence contributing key information (auth, quota, read-only, pagination, purpose). It is slightly packed but not excessive, earning a high score.
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 single-parameter read-only tool, the description covers the essential aspects: purpose, authentication, quota, pagination behavior, and read-only nature. It does not detail the response structure, but 'public user profile' implies the return, and the absence of an output schema makes this acceptable.
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?
With schema description coverage at 0%, the description compensates by clarifying that the tool fetches a profile 'by user ID.' While it doesn't describe the format (the schema pattern ^\d+$ does that), the purpose sentence directly ties the parameter to its usage, making it meaningful.
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 'Fetch one public user profile by user ID,' using a specific verb and resource. This distinguishes it from sibling tools like user_by_username and user_by_ids, which handle different lookup methods or multiple IDs.
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 implies usage when a user ID is available (by saying 'by user ID') but does not explicitly contrast with alternatives like user_by_username or provide when-not-to-use guidance. It does mention the necessity of an API key and quota consumption, which is contextual but not alternative-based.
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.