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Robyn — Gasless Cross-Chain for AI Agents

by io.github.ox31461
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How much of my budget is left?

robyn_mandate_status

Remaining and consumed budget for a signed mandate. Consumption counts ONLY transfers verified on-chain, so the figure cannot be inflated by claiming spends that did not happen.

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": {
      "mandateId": "<mandateId>"
    },
    "name": "robyn_mandate_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
mandateIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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 does reveal a key behavioral trait: consumption counts only verified on-chain transfers, preventing inflation. However, it does not disclose whether the operation is read-only, potential error conditions, auth requirements, or the return format. This is a partial disclosure.

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

Conciseness5/5

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

The description is a single sentence, front-loaded with the core purpose and followed by an important caveat. Every word earns its place; there is no redundancy or fluff. It is efficiently structured and appropriately sized for the tool's complexity.

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

Completeness3/5

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

Given the simple schema (one param, no output schema) and no annotations, the description is fairly complete for a status query. It describes the main function and a crucial behavioral nuance. However, it lacks clarity on the output format (e.g., units, currency) and does not contrast with sibling tools, leaving the agent without enough context to differentiate when this tool is preferred over similar ones.

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

Parameters3/5

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

The schema has one parameter (mandateId) with 0% description coverage, so the description must compensate. It adds context by referring to 'a signed mandate,' indicating the ID refers to a signed mandate. However, it does not explain what a mandate ID looks like, how to obtain it, or any constraints. For a single simple parameter, this is adequate but not comprehensive.

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 identifies the tool's purpose: 'Remaining and consumed budget for a signed mandate.' It uses a specific resource (mandate budget) and distinguishes from siblings like robyn_mandate_check or robyn_spend_statement by focusing on budget status. The caveat about on-chain verification adds precision and clarifies the tool's scope.

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

Usage Guidelines3/5

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

The description implies when to use this tool (when you need accurate, verified budget consumption) via the on-chain verification statement, but it does not explicitly state when not to use it or mention alternative tools. With many siblings, explicit guidance would be beneficial, but the context is enough to infer the primary use case.

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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