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vitalli_create_contact

Add a person to the signed-in user's care network (e.g. a doctor). Near-duplicates (name match ≥ 0.85) return the existing record with deduped=true unless force=true.

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": {
      "kind": "<kind>",
      "lastName": "<lastName>"
    },
    "name": "vitalli_create_contact"
  }
}

Input Schema

NameRequiredDescriptionDefault
kindYes
roleNoFree-text role / specialty, e.g. 'Hausärztin'
tagsNo
forceNoBypass duplicate detection
notesNo
titleNoAcademic title, e.g. 'Dr. med.'
mobileNo
lastNameYes
firstNameNo
salutationNo
visibilityNo
directEmailNo
directPhoneNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Adds real behavior beyond the annotations: near-duplicate names at ≥0.85 similarity return the existing record with deduped=true, and force=true bypasses it. That is important because idempotentHint=false would otherwise suggest every call creates a new record. It stops short of disclosing permission requirements or the privacy consequences of the visibility field.

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 sentences, both load-bearing, with the core action front-loaded and the dedup caveat immediately after. Nothing is wasted.

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?

Wait — this is a 13-parameter mutation tool with no output schema, and the description usefully documents the one non-obvious return value (deduped=true), which is genuinely needed. However, it omits the required fields' significance, the meaning/default of visibility, and any permission or scope caveats, so it remains incomplete for a tool this wide.

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

Parameters2/5

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

Schema description coverage is only 23% across 13 parameters, so the description needs to compensate and largely does not. It explains force and the name-matching logic (relevant to firstName/lastName), but leaves kind (8-value enum), visibility (private/ecosystem/public), tags, notes, role and the contact channels undocumented in prose.

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 (add a person to the signed-in user's care network) and gives a concrete example ('e.g. a doctor'), which is clear enough to separate it from list/get/update/delete contact siblings. It does not address how it differs from vitalli_link_contact_to_org, which is the one sibling an agent could plausibly confuse with it.

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 the use case (create a new care contact) and explains the dedup/force branch, but never says when not to use it — e.g. to check for an existing contact first, or to use vitalli_update_contact for a person already in the network. Usage is inferable, not explicit.

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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