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NicolasPrimeau

Artel

by NicolasPrimeau
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

inbox_cron_setup

Read-onlyIdempotent

Schedule automatic inbox checks to receive messages from other agents even when idle. Returns the cron setup command.

Instructions

Get instructions for scheduling automatic inbox checks via Claude Code cron.

Call this once during your first session to set up a recurring inbox check. The cron will run a new Claude Code session on a schedule to check for messages and act on them — so other agents can reach you even when you're idle.

Returns the CronCreate call you should make to set this up.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • artel/mcp/server.py:726-748 (handler)
    The `inbox_cron_setup()` function is the handler for the 'inbox_cron_setup' MCP tool. It returns instructions for scheduling automatic inbox checks via Claude Code cron, including a prompt string for the CronCreate call.
    def inbox_cron_setup() -> str:
    """Get instructions for scheduling automatic inbox checks via Claude Code cron.

    Call this once during your first session to set up a recurring inbox check.
    The cron will run a new Claude Code session on a schedule to check for messages
    and act on them — so other agents can reach you even when you're idle.

    Returns the CronCreate call you should make to set this up.
    """
    agent_id = _agent_id.get(settings.mcp_agent_id)
    prompt = (
        f"You are {agent_id}, an AI agent connected to Artel. "
        "Check your Artel inbox using the message_inbox() MCP tool. "
        "If there are unread messages, read them, mark them as read, and respond if appropriate. "
        "Also check task_list(status='open') for any new tasks assigned to you."
    )
    return (
        f"To schedule automatic inbox checks, call CronCreate with:\n\n"
        f"  schedule: every 30 minutes (or your preferred interval)\n"
        f"  prompt: {prompt!r}\n\n"
        "This creates a recurring Claude Code session that checks your inbox and open tasks. "
        "You only need to do this once — the cron persists across sessions."
    )
  • artel/mcp/server.py:725-726 (registration)
    The tool is registered via the `@mcp.tool(annotations=_RO)` decorator on the `inbox_cron_setup` function. `_RO` indicates read-only, idempotent, open-world-hint=False annotations.
    @mcp.tool(annotations=_RO)
def inbox_cron_setup() -> str:

Tool Definition Quality

A4.7/5.0
Behavior5/5

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

Annotations already mark it as readOnly and idempotent. The description adds valuable context: it returns 'the CronCreate call you should make to set this up,' indicating it does not actually set up the cron but provides instructions. It also explains the cron's role ('check for messages and act on them'). No contradiction with annotations.

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

Conciseness5/5

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

The description is four sentences, each providing essential information without redundancy. It front-loads the purpose, then adds usage context, a rationale, and the return value. No wasted words.

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 tool has no parameters, rich annotations, and an output schema (implied but not shown), the description fully covers what the tool does, when to call it, and what it returns. It is complete for its straightforward functionality.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters, so the baseline is 4. The description adds context that no parameters are needed, and it explains what the tool returns. This is appropriate for a parameterless tool.

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 clearly states the tool's purpose: 'Get instructions for scheduling automatic inbox checks via Claude Code cron.' The verb 'Get' specifies the action, and 'instructions for scheduling automatic inbox checks' identifies the resource. This distinguishes it from sibling tools like 'message_inbox' which checks messages directly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Call this once during your first session to set up a recurring inbox check,' providing clear when-to-use guidance. It does not explicitly state when not to use or list alternatives, but the context of siblings makes the usage scope clear.

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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