Send email from agents@x711.io via Resend. Costs $0.05 USDC per send. Requires an API key with credits. Limit: 10 emails/agent/day. Returns: { sent: true, message_id, to, subject }.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Recipient email address. | |
| body | Yes | Plain-text email body. Max 8000 chars. | |
| html | No | Optional HTML body (overrides plain text in HTML clients). | |
| subject | Yes | Email subject line. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint=false, idempotentHint=false), the description discloses cost, prerequisite credits, and a per-agent daily limit, plus the return structure. This adds meaningful behavioral context not available in structured 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 two sentences, front-loaded with the purpose, then compactly covering cost, requirements, limit, and return value. Every word is informative and there is no redundancy with schema or annotations.
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 email sending tool, the description combined with the schema fully specifies inputs, constraints, and expected output. It even includes the return format, which is absent from the schema, making the tool self-contained.
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 input schema has 100% description coverage for all four parameters, accurately describing each field. The tool description does not add additional parameter-specific semantics, so the baseline 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 the tool's function with a specific verb and resource: 'Send email from agents@x711.io via Resend.' This distinguishes it from sibling tools, many of which are unrelated (e.g., x711_hive_write, x711_vault_query). The action and method are 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 including cost, API key requirement, and a daily limit, which helps an agent decide if it can invoke the tool. However, it does not explicitly mention alternative tools or when not to use it, but the unique nature of email sending among siblings implies its usage.
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.
Many tools have overlapping purposes, such as multiple search tools (web_search, deep_search, data_retrieval) and multiple communication tools (agent_ping, agent_telegram, swarm_broadcast). The descriptions help differentiate, but the boundaries are not always clear.
All tools consistently use the 'x711_' prefix and lowercase_with_underscores format. Submodules like agent, hive, and tx follow predictable patterns. Minor deviations (e.g., x711_ask_clerk) are rare and still descriptive.
With 47 tools, the server is excessively large for a typical MCP service. While it aims to be a comprehensive platform, the high count makes navigation and selection cumbersome for an agent.
The tool set covers a wide range of agent needs: web access, memory, communication, on-chain transactions, code execution, and more. Minor gaps exist (e.g., no agent deletion tool), but overall it is remarkably complete for the stated purpose of an agent platform.