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barevalue_estimate

Calculate AI podcast editing costs before ordering. Get a breakdown of AI bonus minutes, subscription minutes, credits, and payment required based on audio duration.

Instructions

Calculate the cost of an AI podcast editing order before submission. Returns breakdown of AI bonus minutes, subscription minutes, credits, and payment required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
duration_minutesYesAudio duration in minutes (1-300)
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool returns a cost breakdown, which is useful, but does not cover other behavioral aspects like error handling, rate limits, authentication requirements, or whether it performs any side effects (e.g., creating a draft order). This leaves gaps in transparency for a tool that likely interacts with order data.

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 front-loaded and highly concise, consisting of two sentences that efficiently convey the tool's purpose and output. Every sentence earns its place by providing essential information without redundancy or unnecessary detail.

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?

Given the tool's moderate complexity (cost calculation with one parameter) and lack of annotations or output schema, the description is reasonably complete. It explains the purpose, usage context, and output breakdown, but could be more comprehensive by detailing behavioral traits or error scenarios, which slightly limits completeness.

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?

The schema description coverage is 100%, with the parameter 'duration_minutes' fully documented in the schema. The description does not add any additional semantic information about the parameter beyond what the schema provides (e.g., why duration matters for cost calculation), so it meets the baseline score of 3 without compensating value.

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 specific action ('Calculate the cost'), resource ('AI podcast editing order'), and scope ('before submission'), distinguishing it from siblings like barevalue_submit (which submits orders) and barevalue_list_orders (which lists existing orders). It explicitly mentions what the tool does rather than restating the name.

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 when to use this tool ('before submission'), implying it should be used prior to submitting an order. However, it does not explicitly state when not to use it or name alternatives (e.g., barevalue_submit for actual submission), which prevents a perfect score.

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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