CRM Connector

Propose: Record a payment

propose_record_payment

AI Agents (inside one system): Use when the person asks for this in a system whose AI agent may change records: A payment the customer made elsewhere, such as in cash or by bank transfer, written on an invoice or order; no card is charged. Only the person can approve it, and it is never undone from here. 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_record_payment"
  }
}

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 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

Behavior4/5

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

The description adds significant behavior beyond the annotations: nothing is written yet, the response shows before/after state per record plus a proposal id, only the person can approve, and the change is never undone from this tool. The batch cap of 25 is repeated from the schema, and it doesn't say what happens on partial failure or how long a proposal stays valid, which keeps it short of a 5.

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 purpose and exclusions, then workflow, then anti-patterns, so the ordering is sensible. However, the second sentence is a long colon-chained clause ('Use when the person asks for this in a system whose AI agent may change records: A payment the customer made elsewhere…') that takes work to parse and could be split.

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

Completeness4/5

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

Given an output schema exists and annotations cover the safety profile, the description supplies the missing pieces an agent needs: the human-approval gate, the preview semantics, and the handoff to apply_proposal. It leaves only edge behavior (failure handling, proposal expiry) unstated, which is a minor gap for this complexity.

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 item fields (id, amount, method, paid_at, reference, type vs item_kind) are already documented in the schema. The description only repeats the one-item-per-record and 25-item limit, and adds nothing on the nested id versus top-level system semantics. 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?

States a specific verb and resource ('Propose: Record a payment') and immediately narrows it: 'A payment the customer made elsewhere, such as in cash or by bank transfer, written on an invoice or order; no card is charged.' That definitional detail distinguishes it from sibling propose_* tools and from apply_proposal, which it 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?

Explicit entry condition ('Use when the person asks for this in a system whose AI agent may change records'), explicit exclusion ('Not for reading (use search_records or get_record)'), and an explicit next step ('only then call apply_proposal; when needsApproval is true, share the approve link instead'). Alternatives and conditions are both spelled out.

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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