CRM Connector

Propose: Add a task

propose_add_task

AI Agents (inside one system): Use when the person asks for this in a system whose AI agent may change records: A task or follow up on a record in the person's system, such as a call next week; the system may notify the user it is assigned to. 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_task"
  }
}

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?

Annotations declare readOnlyHint=false, destructiveHint=false, openWorldHint=true, and idempotentHint=false, but the description adds materially more: nothing is persisted yet, the response contains a per-record before/after state plus a proposal id, and the system may notify the assigned user. The side effect of notification on other people is exactly the kind of behavioral context 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.

Conciseness4/5

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

The conditional trigger and the primary constraint are front-loaded, and the workflow steps are ordered as the agent should execute them. Some sentences are run-on and pack several clauses together (the opening sentence mixes the trigger, the resource, and an example), costing a little readability.

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 summarizes what the answer contains (current vs. proposed state, proposal id), which is the right level of detail for a propose/confirm workflow. Combined with the system-selection rule, batch limits, and the hand-off to apply_proposal, an agent has everything needed to call and follow through correctly.

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 both top-level parameters and every nested item field are already documented in the schema. The description restates the batching rule ("one item per record, at most 25") and the system-selection guidance that the schema already carries, adding little new meaning; baseline 3 applies.

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 the specific action and resource (add a task/follow-up on a record) and frames it as a non-committal proposal rather than a write. It explicitly distinguishes itself from reading siblings ("Not for reading (use search_records or get_record)") and from the committing sibling (apply_proposal), so an agent can route correctly without opening 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 an explicit precondition ("Use when the person asks for this in a system whose AI agent may change records"), a full call sequence (show the diff, disclose outbound notifications, ask permission, then call apply_proposal), and a branch for needsApproval=true pointing to the approve link. It also states a negative case for reads, leaving little to infer.

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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