CRM Connector

Propose: Add to a workflow

propose_add_to_workflow

AI Agents (inside one system): Use when the person asks for this in a system whose AI agent may change records: A record put into one of the person's own workflows or campaigns, which then runs its steps, and may send messages. Only the person can approve 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_add_to_workflow"
  }
}

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.

Changed3 schema fields changedNov 10, 2026

changedInput schema / properties / items / items / properties / automation_kind / description

Previous value: -"A workflow, a campaign or a sales sequence; workflow when left out."New value: +"A workflow, a campaign, a sales sequence or a help desk macro; workflow when left out."

changedInput schema / properties / items / items / properties / automation_kind / enum

Previous value: -[
-  "workflow",
-  "campaign",
-  "sequence"
-]New value: +[
+  "workflow",
+  "campaign",
+  "sequence",
+  "macro"
+]

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

A4.3/5.0

Behavior5/5

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

Annotations only say readOnly=false, destructive=false, openWorld=true, idempotent=false. The description adds far more: no state change occurs yet, the response contains per-record before/after state plus a proposal id, workflow steps may send messages to people in the system, only the person can approve, and there is a needsApproval branch requiring an approve link. This is exactly the behavioral context the annotations cannot convey.

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

Conciseness3/5

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

Nearly every sentence carries substantive information, but it is delivered as a single dense paragraph mixing trigger conditions, side effects, and the approval protocol, which makes it hard to scan. The opening qualifier 'AI Agents (inside one system)' is awkward and adds little. Restructuring into short ordered steps would improve it without losing content.

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?

An output schema exists, yet the description still characterizes the return shape (per-record current vs. prospective state plus a proposal id) and the needsApproval branch, so an agent knows what to do with the response. For a two-parameter, side-effect-bearing proposal tool, nothing material about invoking it correctly 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 description coverage is 100%, so the schema already documents both parameters in detail (including the item fields, the 25-item cap, and the instruction to ask which AI agent). The description restates the one-item-per-record and max-25 rule, which duplicates the schema, and adds only modest framing about the workflow belonging to the person. Baseline 3 is appropriate.

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?

The description states a specific action and resource: putting a record into one of the person's workflows or campaigns, and clarifies it is a proposal rather than a write ('Nothing is written yet ... plus a proposal id'). It also rules out a reading use case ('Not for reading (use search_records or get_record)'), which separates it from siblings. It loses a point because the core purpose is phrased passively and buried behind a meta prefix ('AI Agents (inside one system): Use when ...') rather than a direct verb.

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 an explicit trigger condition ('Use when the person asks for this in a system whose AI agent may change records'), an explicit exclusion with named alternatives (search_records, get_record), and an explicit next step: show results, ask, then call apply_proposal, or share the approve link when needsApproval is true. The whole propose-then-apply chain is spelled out with no inference required.

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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