[duvera · risk:low] Look up the current version, summary, license, and homepage of a Python package on PyPI. No account required.
| Name | Required | Description | Default |
|---|---|---|---|
| package | Yes | PyPI package name, e.g. "requests" or "fastapi". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry behavioral disclosure. It declares 'risk:low' and 'No account required', indicating a safe, read-only operation. This is sufficient for a simple lookup tool, though no mention of rate limits or response behavior.
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 a single, well-structured sentence with a risk tag and key details. No unnecessary words, and the most important information comes first.
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 simple lookup with one parameter and no output schema, the description fully explains what data it returns and the lack of authentication. It is complete for the tool's complexity.
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 description coverage is 100%, already describing 'package' as 'PyPI package name'. The description adds concrete examples like 'requests' and 'fastapi', which enhance clarity without being redundant.
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 verb 'Look up' and specifies the resource 'Python package on PyPI'. It lists the exact data returned: version, summary, license, homepage. This distinguishes it from its sibling duvera__dev_npm_package, which covers npm packages.
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 helpful context such as 'risk:low' and 'No account required', but it does not explicitly advise when to use this tool versus alternatives like duvera__dev_npm_package. The agent can infer from sibling names, but explicit guidance is missing.
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.
