DROYD MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context about multi-turn conversations and agent capabilities but lacks details on permissions, rate limits, or response formats. It does not contradict annotations, but for a chat tool with no annotations, more behavioral traits could be described.

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 appropriately sized and front-loaded with the core purpose, followed by structured sections (Agent Types, Multi-turn Conversations, Examples). Most sentences earn their place, though some details (like the 'attached_content' parameter) are not explicitly covered in the description, slightly reducing efficiency.

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?

Given the tool's complexity (multi-turn chat with multiple agent types) and no output schema, the description is moderately complete. It covers usage scenarios and parameters but lacks information on response behavior, error handling, or integration with sibling tools. With no annotations and no output schema, it should do more to be fully comprehensive.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by briefly mentioning parameters in examples (e.g., 'message', 'conversation_uuid', 'agent_type') but does not provide additional syntax or format details. Baseline 3 is appropriate as the schema does the heavy lifting.

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 purpose as 'Chat with a DROYD AI agent' and specifies it 'Supports multi-turn conversations,' which distinguishes it from sibling tools focused on filtering, getting positions, managing trades, or searching. It provides a specific verb ('Chat') and resource ('DROYD AI agent') with explicit scope.

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 offers clear context for when to use this tool by detailing agent types (e.g., 'research' for crypto analysis, 'trading' for signals) and multi-turn conversation handling. However, it does not explicitly state when not to use it or name alternatives among sibling tools, such as when to use droyd_search_content instead for specific queries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.