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Estimate a cost and a time

estimate
Read-only

Preview a prompt's cost and response time before sending, including the model Auto would choose, why it fits, and a cost-effective or quick option at equal quality. No model call is made.

Instructions

Estimate what a prompt would cost and how long it would take before sending it: the model Auto would pick, why, and at the same quality the cheapest and the fastest choice. Nothing is sent to a model.

Input Schema

NameRequiredDescriptionDefault
modelNoauto (the default) or a model id.
speedNoFor auto: "cheapest", "fastest", or a number of seconds to answer within, like "30". Default: the user's choice in Leanfare.
promptYesThe prompt to price.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.15.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description adds genuinely new context by confirming no model call occurs and by naming what the response contains (Auto's pick, the rationale, cheapest and fastest at the same quality). With no output schema, this is the main source of return-value information, though it doesn't describe format or precision of the cost/time figures.

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?

A single front-loaded sentence that opens with the action and closes with the safety guarantee; every clause (cost, time, Auto's pick, why, cheapest, fastest, same quality, no model call) conveys distinct information. No filler or restatement of the title.

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?

For a read-only, three-parameter estimation tool with no output schema, the description covers purpose, the safety profile, and the shape of the result adequately. The remaining gap is quantitative detail (units, precision, whether cost is per-token or total), which matters for an agent interpreting the numbers.

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%, so model, speed, and prompt are already documented in structured form. The description adds framing that helps interpret results ('the model Auto would pick', 'at the same quality'), but it does not explain parameter interactions such as how speed constrains the model choice or what a numeric seconds value does. Baseline 3 applies when the schema carries the parameter burden.

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 ('estimate what a prompt would cost and how long it would take') and enumerates the exact outputs: the model Auto would pick, the reasoning, and the cheapest/fastest choice at equal quality. The closing 'Nothing is sent to a model' separates it from send-side siblings like ask, delegate, and trial without naming them.

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?

'before sending it' gives a clear temporal cue for when to reach for this tool, and 'Nothing is sent to a model' reinforces that it is a pre-flight check rather than an execution path. It stops short of naming a specific alternative (e.g., trial or ask) or stating when not to use it, so the routing is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.