[twitter · risk:low] Search for recent tweets matching a keyword, hashtag, or phrase using the Twitter v2 API. Pass your Twitter Bearer Token via X-Duvera-Service-Token header — Duvera never stores it. Get a free Bearer Token at developer.twitter.com.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Twitter search query. Supports operators like "from:user", "#hashtag", "-word". | |
| max_results | No | Number of tweets to return (10-100, default 10). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full transparency burden. It discloses the API version, token handling (not stored), and risk level, but omits behavioral details like rate limits, error handling, result format, or what happens on invalid credentials.
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?
Two sentences plus a concise risk tag. No superfluous words. The purpose is front-loaded and efficient. Meets conciseness ideal.
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 two-param tool with no output schema or annotations, the description covers basic purpose and auth but lacks details on result format and error behavior. Adequate but not fully complete.
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 coverage is 100%, with both parameters described in the schema. The tool description adds marginal value by mentioning 'keyword, hashtag, or phrase' for query but does not elaborate on max_results beyond default/range. Baseline 3 is appropriate.
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 searches for recent tweets by keyword, hashtag, or phrase using Twitter v2 API. This is specific and distinct from sibling tools, which are for other services (e.g., wiki, news).
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 authentication setup instructions (Bearer Token header) but lacks guidance on when to use this tool versus alternatives (e.g., other search tools) or when not to use it. Usage context is implied but not explicit.
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.
Each tool is prefixed with its service name, and within each service, tools have distinct actions (e.g., mail_read vs. availability_find). The duvera tools cover different subdomains like dev, finance, and food with no overlap, making selection unambiguous.
All tools follow the pattern service__action_object or service__category_action, using lowercase with underscores. The order of verb and noun varies slightly (e.g., package_track vs. boardingpass_show), but the naming is highly predictable and readable.
With 52 tools, the server is large but justified as a gateway aggregating many external services. Each tool corresponds to a common task for its service, so no tool feels extraneous, though the total number is high.
The tool surface covers a wide array of services but only provides one or two basic operations per service (mostly read-only). While this suits a quick-lookup gateway, deeper workflows (e.g., creating or updating resources) are missing, leaving gaps for many use cases.
