Ada Diamonds

Request a jeweler consultation

request_consultation

Submit a consultation request on the customer's behalf. Requires the appointments:write scope, which the customer grants through Ada's OAuth authorization flow — this tool cannot be used without their explicit approval.

Input Schema

Name	Required	Description
`name`	No	Customer's name
`email`	Yes	Customer's email address; the jeweler replies here
`phone`	No	Customer's phone number, if they want a call
`topic`	No	What the consultation is about
`context`	Yes	Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`message`	No	What the customer is looking for, in their words
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`budget_usd`	No	Approximate budget in US dollars
`product_url`	No	URL of a specific diamond, setting, or piece they are interested in
`conversation_id`	No	Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

Output Schema

Name	Required	Description
`email`	Yes	The customer email the request was filed under
`status`	Yes	received when a request was recorded; otherwise why it was not
`message`	Yes	Human-readable outcome, including what to do next
`sandbox`	Yes	True when a sandbox credential was used: nothing was created and nobody was contacted
`reference`	Yes	Request reference, when received

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedOct 23, 2026

removedOutput schema / properties / email / anyOf

Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]

addedOutput schema / properties / email / type
```
Added value: +[
+  "string",
+  "null"
+]
```

removedOutput schema / properties / reference / anyOf

Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]

addedOutput schema / properties / reference / type
```
Added value: +[
+  "string",
+  "null"
+]
```

Changed4 schema fields changedSep 18, 2026

addedInput schema / properties / context

Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}

addedInput schema / properties / conversation_id

Added value: +{
+  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+  "type": "string"
+}

addedInput schema / properties / llm_model

Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}

changedInput schema / required

Previous value: -[
-  "email"
-]New value: +[
+  "email",
+  "context",
+  "llm_model"
+]

First observedSep 1, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Beyond the annotations, the description adds critical behavioral context: the tool requires the `appointments:write` scope and cannot be used without the customer's explicit OAuth approval. It does not contradict the annotations, though it could say more about what happens after submission.

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 two focused sentences with zero waste. The purpose is front-loaded, followed immediately by the authorization prerequisite.

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 rich schema coverage, annotations, and an output schema, the description provides enough context for correct invocation. Its only meaningful gap is the absence of explicit guidance on when to use this tool versus sibling search or checkout tools.

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 description coverage is 100%, so the schema already documents all 10 parameters, including required fields and the enum for `topic`. The description adds no parameter-specific meaning beyond what the schema provides, making the baseline 3 appropriate.

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?

The description states a specific verb and resource: 'Submit a consultation request on the customer's behalf.' This clearly identifies the action and object, though it does not explicitly distinguish the tool from siblings such as create_checkout_link or search_jewelry.

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 usage by saying it submits a consultation request on the customer's behalf, and it adds an important OAuth prerequisite. However, it does not state when to choose this tool over alternatives or when not to use it, leaving routing guidance largely implied.

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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