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Model Ruler — AI Cost Calculators

Workflow Automation Platform Cost Calculator

automation-cost-calculator
Read-onlyIdempotent

Use for generic or non-agent recurring workflow platform billing across Zapier task billing, Make credit billing, and n8n execution billing. Use agent-workflow-cost-calculator instead when the workflow is explicitly an AI agent with app actions or MCP tool calls. Use agent-loop-cost-calculator instead when the question is about LLM inference/reasoning cost per successful agent task.

Input Schema

NameRequiredDescriptionDefault
make_modules_per_runNoMake module actions per scenario run; defaults to billable_steps_per_run
billable_steps_per_runNoBillable actions/modules per run (default 5)
workflow_runs_per_monthYesWorkflow/scenario runs per month

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety and determinism profile is fully covered by structured data. The description adds scoping context (which billing models are in scope) but says nothing about the returned output, assumptions, or platform-specific billing edge cases. With annotations carrying the behavioral burden, this is adequate but not additive.

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?

Three sentences, all routing-oriented, with zero filler. The scope statement comes first, followed by the two exclusion/alternative conditions in a consistent 'Use X instead when Y' pattern that is easy to scan.

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?

There is no output schema, so the description is the only place return values could be described, and it omits what the calculator actually returns (presumably per-platform cost breakdowns given the multi-platform scope). Routing is otherwise complete for a read-only deterministic calculator, so the gap is minor but real.

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 all three parameters (workflow_runs_per_month, billable_steps_per_run, make_modules_per_run) are already documented in the schema, including defaults and the Make fallback to billable_steps_per_run. The description adds domain framing around billing models but no parameter-level meaning beyond what the schema provides, so the baseline of 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 states a specific function (recurring workflow platform billing cost calculation) and enumerates the exact billing models covered: Zapier task billing, Make credit billing, and n8n execution billing. It explicitly differentiates itself from two named siblings, so an agent can identify it without opening any 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 when-to-use condition ('generic or non-agent recurring workflow platform billing'), then names agent-workflow-cost-calculator for AI-agent workflows with app actions/MCP calls and agent-loop-cost-calculator for LLM inference/reasoning cost per successful task. Both alternative routes and their selecting conditions are stated.

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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