Argo Hub Picking y Packing

Ecommerce picking and packing workload calculator

calculate_picking_workload

Read-only

Calculate parcel preparation hours and average capacity needs from parcels, minutes per parcel, other work and available productive hours. It does not model shifts, concurrency, learning curves, carrier cutoffs or the actual daily workload distribution. Check peaks before sizing resources. It does not estimate payroll savings or recommend hiring or dismissal. Freed founder hours do not automatically represent cash savings. Input fields: parcels: An order shipped in two boxes counts as two parcels. minutesPerParcel: Measure picking, packing and labelling without double counting the next field. otherMinutes: Receipts, inventory checks and work excluded above. 0 if absent. workingDays: The average does not represent campaign peaks. productiveHours: Optional. Time available for all scenario tasks after breaks and unrelated duties. Blank means no staffing estimate.

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": {
      "parcels": "<parcels>",
      "minutesPerParcel": "<minutesPerParcel>",
      "otherMinutes": "<otherMinutes>",
      "workingDays": "<workingDays>"
    },
    "name": "calculate_picking_workload"
  }
}

Input Schema

Name	Required	Description	Default
`parcels`	Yes
`workingDays`	Yes
`otherMinutes`	Yes
`productiveHours`	No
`minutesPerParcel`	Yes

Output Schema

Name	Required	Description	Default
`tool`	Yes
`method`	Yes
`status`	Yes
`metrics`	Yes
`sources`	Yes
`currency`	No
`limitations`	Yes
`vatIncluded`	No
`pendingFields`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare this as a read-only, non-destructive, closed-world operation. The description adds meaningful behavioral context beyond that: it explains what the model does not simulate (shifts, concurrency, learning curves, carrier cutoffs, daily distribution) and warns against interpreting results as payroll savings or hiring recommendations. This is solid transparency for a calculation tool.

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 description is front-loaded with the core calculation and then provides caveats and parameter definitions. It is somewhat long but every sentence adds useful context. Minor repetition in the negative constraints keeps it from being maximally concise.

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 a five-parameter calculator with no schema descriptions but an output schema, the description is complete enough for an agent to invoke it correctly. It covers all inputs, clarifies units and counting rules, states key exclusions, and warns about common misinterpretations of the outputs.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden of explaining parameters. It does so thoroughly: parcels (double-box orders count twice), minutesPerParcel (avoid double counting otherMinutes), otherMinutes (receipts, inventory checks, 0 if absent), workingDays (average does not represent campaign peaks), and productiveHours (optional, blank means no staffing estimate).

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 clearly states a specific verb and resource: calculating parcel preparation hours and average capacity needs from parcels, minutes per parcel, other work, and productive hours. It is easy to understand what the tool does. There are no sibling tools to distinguish against, so a 4 rather than a 5 is appropriate.

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 provides clear context for use, including a caution to check peaks before sizing resources and explicit exclusions of what the model does not cover. It does not name alternative tools or give a strict when-to-use versus when-not-to-use routing rule, but the caveats make appropriate usage fairly 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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