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iniyusril

Dataverse Support MCP

by iniyusril

find_contact

Locate Dataverse contact records by email address to identify email senders and support customer replies.

Instructions

Find contact records by email address (emailaddress1 or emailaddress2).

Input Schema

NameRequiredDescriptionDefault
email_addressYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, yet it never says whether this is a read-only lookup, whether it returns zero, one, or many records, or what happens when no contact matches. The one piece of real behavioral context is the dual-field matching rule, which is genuinely useful but not enough on its own.

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?

A single sentence with no filler, and the dual-field matching detail is placed inline where it is immediately useful rather than buried after boilerplate.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and the single-parameter surface is simple. However, for a lookup tool the missing pieces — match strictness and no-result behavior — are the ones an agent most needs before invoking it.

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 0% — the parameter is documented only as "Email Address" — so the description must compensate, and it partially does by revealing that the value is matched against either email field. It still omits match semantics: exact vs partial, case sensitivity, and whether a non-matching value is an error or an empty result.

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 ("Find contact records") and adds the lookup key semantics — matching against emailaddress1 or emailaddress2 — which is more precise than the name alone. It does not explicitly differentiate itself from siblings like create_contact or get_email, but the find-vs-create distinction is unambiguous.

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

Usage Guidelines2/5

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

There is no statement of when to use this instead of create_contact or get_email, and no prerequisites or exclusions. The agent must infer the use case entirely from the verb.

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