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Haseeb-Ahmed-AI

customer-data-mcp

search_customers

Find customers by partial name, email, or company. Returns matching profiles with basic info—ideal when you have a name or email instead of a customer ID.

Instructions

Search for customers by name, email, or company name. Performs a case-insensitive partial match, so 'smith' will match 'John Smith' and 'jane.smith@...'. Returns a list of matching customers with their basic profile info (does not include full order history — use get_customer_details or get_customer_orders for that). Use this when the user gives a name, email, or company rather than an exact customer ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch text to match against customer name, email, or company (partial match, case-insensitive). Example: 'smith', 'acme', 'john@example.com'.
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses case-insensitive partial matching, indicates the return content ('basic profile info'), and explicitly excludes full order history, directing to other tools. It does not mention pagination or error behavior, but for a read-only search these are minor gaps.

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 sentences, front-loaded with the core purpose, each earning its place. No redundancy, and the secondary alternatives are mentioned succinctly without digressing.

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?

For a simple one-parameter search tool, it covers the essential context: what it matches, what it returns (basic profile), what it excludes (order history), and when to use it. It could elaborate on what 'basic profile info' includes, but given the single parameter and no output schema, this is adequate.

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 already fully documents the query parameter with description and example, covering the matching behavior (partial, case-insensitive). The tool description restates the same info but adds no new semantic detail beyond the schema, so baseline 3 is appropriate.

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?

Description states a specific verb ('Search for customers'), identifies the resource ('customers'), and enumerates searchable fields (name, email, company). It also distinguishes from siblings by noting it's for partial text matches rather than exact IDs and mentions get_customer_details/get_customer_orders for order history, making it clear what this tool is for.

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 states when to use: 'Use this when the user gives a name, email, or company rather than an exact customer ID.' It also guides toward alternatives for order history, providing clear when-to-use and when-not-to-use guidance.

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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