CRM Connector

Propose: Assign to a user

propose_assign_owner

AI Agents (inside one system): Use when the person asks for this in a system whose AI agent may change records: A contact, deal or ticket given to another user of the person's system as its owner or assignee, the person responsible for it. Give one item per record, at most 25. Nothing is written yet: the answer shows, per record, what it holds now and would hold after, plus a proposal id. Show it to the person, say so first when something would be sent to the people in their system, ask whether to go ahead, and only then call apply_proposal; when needsApproval is true, share the approve link instead. Not for reading (use search_records or get_record).

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": {
      "system": "<system>",
      "items": "<items>"
    },
    "name": "propose_assign_owner"
  }
}

Input Schema

Name	Required	Description	Default
`items`	Yes	One object per record, at most 25.
`system`	Yes	Which AI agent: the system's id from get_ai_agent_options, or the name of the system or its connection. Ask the person which AI agent they mean unless they named it in this conversation; never pick one yourself.

Output Schema

Name	Required	Description	Default
`notice`	No
`changes`	Yes
`systemId`	Yes
`warnings`	Yes
`expiresAt`	Yes
`approveUrl`	Yes
`proposalId`	Yes
`systemName`	Yes
`needsApproval`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 10, 2026

changedInput schema / properties / items / items / properties / type / description

Previous value: -"The type of the record: a contact or a deal."New value: +"The type of the record: a contact, a deal or a ticket."

changedInput schema / properties / items / items / properties / type / enum

Previous value: -[
-  "contact",
-  "opportunity"
-]New value: +[
+  "contact",
+  "opportunity",
+  "ticket"
+]

Changed1 schema field changedNov 5, 2026

changedInput schema / properties / system / description

Previous value: -"Which AI agent: the system's id from get_ai_agents_info, or the name of the system or its connection. Ask the person which AI agent they mean unless they named it in this conversation; never pick one yourself."New value: +"Which AI agent: the system's id from get_ai_agent_options, or the name of the system or its connection. Ask the person which AI agent they mean unless they named it in this conversation; never pick one yourself."

AddedNov 5, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations declare a non-read-only, open-world, non-idempotent mutation, and the description goes well beyond them: nothing is written, the answer returns a current-vs-proposed per-record preview plus a proposal id, an approval-link flow exists, and changes may notify people in the system. The only gap is that it doesn't say what happens to items that fail validation in the batch; 'Nothing is written yet' is a rollout statement, not a contradiction of readOnlyHint=false.

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

Conciseness4/5

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

Front-loaded with the usage condition and zero filler sentences, but several clauses are crammed into single long sentences (the owner definition and the approval instructions), making it denser than needed. Every piece still earns its place.

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

Completeness5/5

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

For a batch mutation tool with an output schema, the description covers purpose, the batch limit, the dry-run result shape, and the approval gate, which is everything an agent needs before invoking it. Return-value details are correctly left to the output schema.

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 description coverage is 100% and the schema already documents system, items, id, type and user, including the enum and maxItems 25. The description's 'Give one item per record, at most 25' merely restates the schema, so baseline 3 applies with no added syntax or format meaning.

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?

States a specific verb+resource: proposing that a contact, deal or ticket be assigned to another user as owner/assignee. It explicitly defines what counts (the person responsible for the record) and names the item types, so an agent can distinguish it from propose_update_fields or propose_add_follower.

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?

Gives explicit when-to-use ('Use when the person asks for this in a system whose AI agent may change records'), an explicit when-not ('Not for reading (use search_records or get_record)'), and the follow-up path (only call apply_proposal after confirming, or share the approve link when needsApproval is true).

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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