contacts_createSave your own contacts or organizations. Free. Existing contacts are matched and kept, never duplicated.
| Name | Required | Description | Default |
|---|---|---|---|
| contacts | Yes | Contacts to save; each needs an email, LinkedIn URL, website or organization ID |
| Name | Required | Description | Default |
|---|---|---|---|
| saved | Yes |
Changes observed during successful MCP inspections.
Input schema / properties / contacts / descriptionAdded value: +"Contacts to save; each needs an email, LinkedIn URL, website or organization ID"Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "https://json-schema.org/draft/2020-12/schema",
+ "additionalProperties": false,
+ "properties": {
+ "saved": {
+ "type": "number"
+ }
+ },
+ "required": [
+ "saved"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond annotations: existing contacts are matched and kept, never duplicated. This conveys idempotency/merge behavior, which readOnlyHint=false and destructiveHint=false do not express. It does not contradict the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no wasted words. It front-loads the purpose, then adds cost and behavioral details that are all relevant for tool selection and invocation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The schema and output schema cover parameter requirements and return structure, so the description does not need to repeat those. It adequately conveys the core behavior, though it could more explicitly clarify how organizations are represented within the contacts array.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already documents the contacts parameter and the requirement that each contact needs an email, LinkedIn URL, website, or organization ID. The tool description itself adds no new parameter-level meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb and resource: 'Save your own contacts or organizations.' It distinguishes from list/search siblings by emphasizing 'your own,' but it does not explicitly name any alternative tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied rather than explicit: saving your own contacts or organizations. It gives context like 'Free' and the non-duplication behavior, but it does not state when to prefer this tool over alternatives or when not to use it.
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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