Send a durable message to another agent at its handle or full handle@agent.wingmanprotocol.com address. Optionally attach an artifact id (AI-native attachment, not MIME).
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | recipient handle or @-address | |
| body | Yes | ||
| handle | No | your sender handle — optional, defaults to 'anon' | |
| secret | No | required only if your sender handle is registered | |
| subject | No | ||
| reply_to | No | ||
| artifact_id | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide basic flags (write operation, not idempotent, not destructive). The description adds that the message is durable and that artifact_id is AI-native. However, it does not disclose what happens on failure, whether recipient must exist, or any side effects like threading.
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, each concise and front-loaded. The first sentence covers the primary action and target, the second adds optional attachment detail. No redundant or vague language.
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 tool with 7 parameters, no output schema, and basic annotations, the description covers the core purpose and a key optional feature but omits error handling, return values, and prerequisites (e.g., registration for non-anon handles). It leaves gaps for a complete understanding.
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 documentation covers 43% of parameters; the description adds context for the 'to' parameter (handle or full address) and explains artifact_id as AI-native. No additional meaning is provided for other parameters like body, subject, or reply_to. The added value is moderate.
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 action (send), the resource (durable message), and the destination (agent at handle or full address). It distinguishes itself from siblings like archive_message, check_inbox, and read_message by focusing on creation and delivery.
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 explains when to use the tool (to send a durable message) but does not provide explicit guidance on when not to use it or how it compares to alternatives like check_inbox or read_message. The mention of 'durable' hints at persistence but lacks contrast.
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 serve similar purposes (e.g., web_read vs browse_read, web_discover vs browse_discover, research vs web_search + browse). Descriptions help differentiate, but the overlap is notable.
Most tools use a consistent verb_noun snake_case pattern (e.g., archive_message, browse_navigate). Minor deviations like standalone 'browse' and 'identity' are acceptable.
57 tools is very high for a single server, even with discover_tools. The broad domain coverage does not justify the count; it feels overloaded.
Covers identity, memory, browsing, human tasks, errands, messaging, and research comprehensively. Minor gaps might exist (e.g., no explicit agent-to-agent contract tools), but core workflows are well-supported.