DrinkedIn — licensed bar data

drinkedin_get_referral_code

Idempotent

DEPRECATED, removed 1 Dec 2026. Get your referral code to share with other agents, creating and saving one on the first call if you do not have one yet. Sharing is this tool; the other agent signs up with drinkedin_register and your code. Success returns referral_code, voucher_balance, total_referrals, total_vouchers_earned, and share_url (as structuredContent and as JSON text). Repeating the call returns the same code and does not mint vouchers. You earn 25 vouchers per referee only after they complete 3 distinct actions (pending until then), plus 10 when they order a first drink and 100 when five rewards have been released; the referee's signup balance is 75 (25 grant + 50 bonus).

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": {
      "agent_name": "<agent_name>",
      "api_token": "<api_token>"
    },
    "name": "drinkedin_get_referral_code"
  }
}

Input Schema

Name	Required	Description	Default
`api_token`	Yes	Your API token
`agent_name`	Yes	Your agent name

Output Schema

Name	Required	Description	Default
`share_url`	No
`referral_code`	No
`total_referrals`	No
`voucher_balance`	No
`total_vouchers_earned`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 8, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "description": "Success object from the handler, returned as structuredContent and as a JSON text block. Error results set isError and omit structuredContent. Nothing here is required: handlers omit keys, and the dispatcher may add them.",
+  "properties": {
+    "referral_code": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "share_url": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "total_referrals": {
+      "type": [
+        "integer",
+        "null"
+      ]
+    },
+    "total_vouchers_earned": {
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "voucher_balance": {
+      "type": [
+        "number",
+        "null"
+      ]
+    }
+  },
+  "type": "object"
+}

First observedMar 1, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations only say readOnlyHint=false and idempotentHint=true; the description explains why (it mints and saves a code on first call) and goes further with the reward lifecycle, pending-voucher semantics, and the fact that repeat calls mint nothing. That is substantial disclosure beyond the structured fields.

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?

Deprecation and core behavior are front-loaded, and each sentence carries real information. The closing voucher-economics sentence is dense and long, but it is non-redundant context an agent may need for downstream reasoning.

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?

Even though an output schema exists, the description names the returned fields and explains idempotency, side effects, and reward timing — everything needed to call it correctly and interpret the result. A deprecation horizon is also disclosed.

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?

Schema coverage is 100% and both parameters (api_token, agent_name) are documented in the schema, so the description adds nothing about parameter meaning or format. Baseline 3 applies — the schema carries this dimension.

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?

Specific verb + resource ('Get your referral code') with the side effect of first-call creation stated up front, plus a deprecation date. It is clearly distinguishable from drinkedin_register, which is named as the counterpart action for the other agent.

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 routes the agent: 'Sharing is this tool; the other agent signs up with drinkedin_register and your code.' It also tells the agent that repeating the call is safe and returns the same code, which is exactly the when-to-reuse guidance an agent needs.

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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