CRM Connector

Propose: Add a line item

propose_add_line_item

AI Agents (inside one system): Use when the person asks for this in a system whose AI agent may change records: A product or service line added to a record, such as a deal, with its name, quantity and price. 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_add_line_item"
  }
}

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

A4.6/5.0

Behavior5/5

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

Beyond the annotations, the description explains that nothing is written yet, that the response is a preview showing current and proposed state plus a proposal id, and that the person must be shown the proposal and asked before apply_proposal. It also discloses the important open-world side effect of sending something to people in their system and what to do when needsApproval is true.

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?

The description is front-loaded with the usage condition and then moves through the proposal workflow in a logical order. It is somewhat dense and awkwardly prefixed with 'AI Agents (inside one system):', but nearly every sentence carries necessary safety or procedural 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?

Given the approval-based workflow, open-world side effects, and sibling tools, the description covers the essential context: what is proposed, what is returned conceptually, what the agent must show the user, and when to call apply_proposal. An output schema exists, so it does not need to explain the return shape further.

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%, so the parameters are already well documented. The description repeats the key constraints, such as one item per record and at most 25, but does not add meaning beyond what the schema already provides.

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?

The description names a specific resource and action: proposing a product or service line item on a record such as a deal, including name, quantity, and price. It also explicitly distinguishes itself from reading tools and from the final apply_proposal step, so an agent can identify its role without inspecting the schema.

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?

It gives clear when-to-use guidance: when the person asks for this in an AI-agent-managed system that may change records. It also gives explicit alternatives for reading (search_records or get_record) and states the required approval workflow before calling apply_proposal.

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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