Robyn — Gasless Cross-Chain for AI Agents

Why this route won — and what it beat

robyn_why_this_route

Returns the full routing decision: every rail that quoted, what each would deliver, the margin the winner won by, and which rails stayed SILENT and why. Signed, so you can archive the rationale. CHECK wasCompetitive BEFORE TELLING A USER THE PRICE IS GOOD. If it is false, exactly one rail answered and "best" means "only" — it did not beat anything. Rails in silentRails did NOT lose; they failed to answer (down, rate-limited, missing credentials). Never describe them as more expensive.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "fromChain": "<fromChain>",
      "toChain": "<toChain>",
      "amount": "<amount>"
    },
    "name": "robyn_why_this_route"
  }
}

Input Schema

Name	Required	Description	Default
`amount`	Yes
`toChain`	Yes
`toToken`	No
`fromChain`	Yes
`fromToken`	No
`toAddress`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedAug 2, 2026

TDQS

A4.1/5.0

Behavior5/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains key nuances: the meaning of wasCompetitive, that silent rails failed to answer rather than being more expensive, and that the output is signed for archival. This goes well beyond a typical description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is composed of four sentences, with each sentence adding critical information: the output contents, the signed nature, the wasCompetitive warning, and the silentRails misrepresentation risk. It is a bit dense but not overly long.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description covers the essential output components and interpretation caveats, which is helpful. However, it omits any explanation of the required parameters and does not mention potential error conditions or edge cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, and the description does not explain any parameters such as fromChain, toChain, amount, or toAddress. Users are left to infer parameter meaning from the tool's name and routing context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns the full routing decision, including every rail that quoted, what they would deliver, and the winning margin. This specific verb+resource clearly distinguishes it from sibling tools like robyn_quote or robyn_route_status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit usage guidance, such as checking wasCompetitive before telling a user the price is good and warning that silentRails did not lose but failed to respond. However, it does not explicitly compare against sibling tools or state when to use this tool versus alternatives.

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

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