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upgrade_plan

Generate a checkout link to UPGRADE the merchant's GriffNode plan (higher limits + features). Before calling, CONFIRM WITH THE USER which plan tier and billing cycle they want — call list_plans to show the options — and which coin to pay with. Do NOT guess these. Returns a payable checkout (deposit address, amount, pay link); nothing is charged until they pay it.

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": {
      "plan_id": "<plan_id>",
      "coin": "<coin>"
    },
    "name": "upgrade_plan"
  }
}

Input Schema

NameRequiredDescriptionDefault
coinYesCoin the user will pay with, e.g. BTC, LTC, ETH, USDT. Ask the user.
plan_idYesPlan tier to upgrade to: 'business' or 'professional'. Confirm with the user (use list_plans).
billing_cycleNoBilling cycle: monthly, quarterly, biannual, yearly, or biennial. Defaults to monthly — confirm with the user.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations cover the safety profile (non-readonly, non-destructive). The description adds real context absent from annotations: it returns a payable checkout (deposit address, amount, pay link) and nothing is charged until paid. It does not mention that repeated calls may create duplicate checkout links despite idempotentHint=false.

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?

Three dense sentences, front-loaded with the action, then constraints, then return/charge semantics. No filler; each clause carries new information.

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

Completeness5/5

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

No output schema exists, but the description summarizes the return (deposit address, amount, pay link) and the deferred-charge behavior. Combined with the fully documented params and annotations, an agent has everything needed to call this correctly.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds the behavioral constraint that plan_id and coin must be confirmed with the user rather than guessed, and notes billing_cycle defaults to monthly — value beyond the field-level descriptions.

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

Purpose4/5

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

States a specific verb and resource — generate a checkout link to upgrade the merchant's plan — and clarifies the scope (higher limits + features). It does not explicitly contrast itself with the sibling create_payment, so the boundary between paying for a plan versus a generic payment is left implicit.

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

Usage Guidelines5/5

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

Explicitly instructs to confirm plan tier and billing cycle with the user, names the alternative (list_plans) to show the options, requires the coin to be chosen, and warns not to guess. Clear when-to-use and prerequisites with no inference needed.

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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