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Propose: Log a call or meeting

propose_log_activity

AI Agents (inside one system): Use when the person asks for this in a system whose AI agent may change records: A call or meeting that took place, written on a record's timeline in the person's system; nothing is dialled and no invitation is sent. 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_log_activity"
  }
}

Input Schema

NameRequiredDescriptionDefault
itemsYesOne object per record, at most 25.
systemYesWhich 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

NameRequiredDescriptionDefault
noticeNo
changesYes
systemIdYes
warningsYes
expiresAtYes
approveUrlYes
proposalIdYes
systemNameYes
needsApprovalYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • 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"
      +]
  2. Changed1 schema field changed
    • 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."
  3. Added

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 discloses that nothing is written immediately, that the response is a preview with current and proposed values plus a proposal id, and that a person must approve before apply_proposal is called. It also warns when something would be sent to people in their system and explains the needsApproval link path, which is exactly the workflow context an agent needs.

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 content is relevant and mostly front-loaded, with purpose, exclusions, constraints, and approval workflow in a compact block. The opening sentence is syntactically dense and repeats the item limit already enforced by the schema, so it is slightly less crisp than it could be.

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 two-step proposal tool with human approval, open-world effects, and an output schema, the description covers the trigger, the non-write preview behavior, the approval handoff, the reading alternative, and the batch limit. Nothing essential for correct invocation 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%, and every parameter including nested item fields has its own description, so the schema already carries parameter semantics. The description only restates the item constraint ('one item per record, at most 25') and does not add format or selection meaning beyond the schema.

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 states a specific action and resource: logging a call or meeting on a record's timeline, while explicitly saying nothing is dialled and no invitation is sent. It also distinguishes this from reading tools by naming search_records and get_record, so an agent can tell it apart from adjacent propose and read operations.

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 (the person asks for this in a system whose AI agent may change records) and an explicit exclusion (not for reading; use search_records or get_record). It further routes the next step to apply_proposal and explains the needsApproval alternative, leaving little to inference.

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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