[venmo · risk:low] Request a payment from a contact via Venmo (no money leaves your account)
| Name | Required | Description | Default |
|---|---|---|---|
| note | No | Optional note explaining the request | |
| recipient | Yes | The Venmo handle, phone, or contact to request from | |
| amount_cents | Yes | Amount being requested, in cents |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility. It discloses that the tool is low-risk and that it does not move money, which is the key behavioral trait. However, it does not cover other potential behaviors like reversibility, limits, or authentication needs, leaving some gaps.
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. Every word earns its place; no redundancy or unnecessary detail.
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 tool with 3 parameters, no output schema, and no nested objects, the description provides sufficient context. The only minor gap is lack of behavior around success/results, but this is not required given the low 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?
Schema coverage is 100% and parameter descriptions are already clear. The description adds no additional meaning beyond what the schema provides, so baseline score of 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 it requests a payment from a Venmo contact, and explicitly notes that no money leaves the account, distinguishing it from sending payments. It uses specific verb+resource and 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?
No explicit guidance on when to use or not use this tool, and no alternatives are mentioned. However, the parenthetical hint about no money leaving the account provides implicit context. For a tool with no sibling Venmo tools, the guidance is adequate but not proactive.
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.
