CRM Connector

Propose: Set the system's own fields

propose_update_fields

AI Agents (inside one system): Use when the person asks for this in a system whose AI agent may change records: New values for fields of a record that exist in the person's own system, such as a lead status or a custom field, by their own names. 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_update_fields"
  }
}

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.

Changed1 schema field changedNov 10, 2026

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

Previous value: -[
-  "contact",
-  "opportunity",
-  "invoice",
-  "estimate",
-  "job",
-  "appointment"
-]New value: +[
+  "contact",
+  "opportunity",
+  "invoice",
+  "estimate",
+  "job",
+  "appointment",
+  "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

Behavior5/5

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

Goes well beyond annotations by disclosing that nothing is written yet, that the response shows per-record before/after state plus a proposal id, and that a downstream side effect can send messages to people in the customer's system. The needsApproval branching is exactly the kind of behavior an agent cannot infer from readOnlyHint/destructiveHint alone.

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 audience and trigger, then the payload rule, then the safety workflow, with no filler. The opening 'AI Agents (inside one system):' is awkward and a few clauses run long, but every sentence carries operational information.

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 non-idempotent, open-world proposal tool with an output schema, the description still supplies the essentials: what is returned, that no write occurs, and the required approval handoff. Nothing needed to invoke or follow up on it is missing.

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 100%, so the schema already documents items, type, id, fields, and system selection. The description only reiterates 'one item per record, at most 25' and that fields are given 'by their own names', adding minimal meaning beyond the structured data.

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: producing proposed new values for fields of existing records in the person's own system, addressed by the field's own name. It also names what it is not ('Not for reading (use search_records or get_record)'), which separates it from neighboring read tools, though the distinction from propose_update_item/propose_update_task is only implied by 'fields... by their own names'.

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 preconditions (a system with an AI agent that may change records), a concrete post-call workflow (show current vs proposed values, disclose outbound sends to people in the system, ask permission, then call apply_proposal), and a branch for needsApproval via an approve link. It also excludes read use cases and points to alternatives.

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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