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create_contact

Create a contact after explicit confirmation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
emailNo
notesNo
phoneYesPhone number in E.164 format
titleYes
optOutNoDo-not-call. Set optedOut true when the contact has asked not to be called again; no outbound call to that number will be dispatched for this organization. Set false to clear it. The date is recorded server-side.
groupIdsNo
confirmedYesMust be true only after the user explicitly confirms this exact operation
customFieldsNo
idempotencyKeyYesA unique identifier generated once for this intended write. Reuse exactly when retrying.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
successNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.4/5.0
Behavior2/5

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

Annotations already indicate readOnlyHint=false, so the mutation is known. The description adds the confirmation requirement, which is a behavioral constraint not in the annotations. However, it omits details like idempotency semantics (covered by schema) and any side effects beyond creation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence, front-loaded with the action. It is not verbose, but it is so brief that it offers no structural breakdown or detail. While conciseness is a virtue, this borders on under-specification rather than efficient communication.

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

Completeness1/5

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

With 10 parameters, nested objects, an output schema, and a confirmation flow, this description is grossly insufficient. It does not explain the confirmation requirement's mechanics, the idempotency key's role, or any preconditions. An agent would have to rely entirely on the schema, which is incomplete. The description fails to provide the context needed for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 40%, and the tool description provides zero parameter explanations. It does not compensate for the low coverage; the schema's own descriptions (e.g., for phone, confirmed, idempotencyKey) carry the load, but many parameters like tags, groupIds, customFields remain unexplained. The description adds no semantic value for any parameter.

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 clearly states the action 'Create a contact' with a specific resource. It adds a meaningful qualifier ('after explicit confirmation') that conveys a prerequisite. However, it does not differentiate this from sibling create tools like create_call or create_case, which also create entities.

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?

The description mentions the requirement of explicit confirmation, implying it should be used only after user consent. But it gives no guidance on when to use this tool versus alternatives (e.g., update_contact for edits, delete_contact for removal) and no context on typical use cases.

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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