Bella

Customer Profile

customer_profile

Read-onlyIdempotent

Retrieve one customer's 360° profile by ID, full or partial name, or email, including lifetime revenue, orders, favorite category, and last five orders; ambiguous names return candidates.

Instructions

A 360° view of one customer: profile, lifetime revenue, orders, favourite category and last 5 orders.

If several customers match a partial name, returns the candidates so you can ask which one.

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": {
      "customer": "<customer>"
    },
    "name": "customer_profile"
  }
}

Input Schema

Name	Required	Description	Default
`customer`	Yes	Customer id (e.g. '42'), full or partial name, or email.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Nov 3, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavior — fuzzy matching by partial name yields a candidate list instead of failing — which an agent must know to avoid misreading a multi-match response as a single customer.

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?

Two short sentences, front-loaded with what the tool returns, followed by the one caveat that changes caller behavior. No filler or restatement of the title.

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?

With an output schema present and annotations covering safety, the description needs only to frame scope and edge behavior, which it does for the multi-match case. It does not say what happens when nothing matches (empty result vs error), a small remaining gap for a lookup tool.

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 the single parameter already documents accepted forms (id, full or partial name, email), so the schema carries the syntax burden. The description only adds the multi-match consequence, not additional format detail; baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific resource and scope ('one customer') and enumerates exactly what is returned: profile, lifetime revenue, orders, favourite category, last 5 orders. The singular per-customer focus implicitly but clearly separates it from list-shaped siblings like top_customers and sales_summary.

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?

Gives a concrete usage rule for the ambiguous case: partial-name matches return candidates so the agent can ask which one, which tells the caller how to proceed rather than guessing. It stops short of explicit when-not or routing guidance against siblings (e.g. sales_summary for aggregates), so it is clear context without exclusions.

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

Deploy Server