Relay Protocol 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 effectively describes the tool's behavior by specifying what it returns ('status, transaction hash, and other execution details'), listing possible status values, and explaining the request ID format. However, it lacks details on error handling, rate limits, or authentication needs, which are minor gaps for a read-only status check tool.

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 well-structured and front-loaded with the core purpose, followed by usage guidelines, parameter details, and an example workflow. Every sentence adds value without redundancy, making it efficient and easy for an AI agent to parse quickly.

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 low complexity (1 parameter, no output schema, no annotations), the description is largely complete. It covers purpose, usage, parameters, and workflow. However, the absence of an output schema means the description doesn't detail the structure of returned data (e.g., fields in 'execution details'), which is a minor gap for full contextual 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?

The input schema has 100% description coverage, so the baseline is 3. The description adds value by clarifying the parameter semantics: it explains the requestId format ('Hex string starting with "0x"') and provides an example, which goes beyond the schema's generic description. This enhances understanding but doesn't fully compensate for potential complexities like length constraints.

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 specific action ('Get the current execution status') and resource ('of a cross-chain request'), distinguishing it from sibling tools like relay_get_quote (for quotes) or relay_get_requests (likely for listing requests). It precisely identifies what the tool does without being vague or tautological.

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 explicitly states when to use this tool ('After executing a quote/swap, use the requestId from the response to monitor progress') and provides an example workflow linking it to relay_get_quote. This gives clear context and distinguishes it from alternatives like relay_get_requests, making it highly actionable for an AI agent.

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