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Moltline Business Suite

Target Price

target_price
Read-onlyIdempotent

Compute the selling price needed to hit a target margin percentage. FREE.

Typical input {"unit_cost": 12, "target_margin_pct": 60} returns {"required_price": 30.0, "unit_margin": 18.0, "equivalent_markup_pct": 150.0}.

The inverse of unit_economics - solves for price from a target margin. Use when the margin is the fixed requirement. Not when the price is already set. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "target_margin_pct must be between 0 and 100"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unit_costYesVariable cost per unit; must be 0 or greater, e.g. 12.0.
target_margin_pctYesDesired gross margin percentage, strictly between 0 and 100, e.g. 60 for a 60% margin.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds critical behavioral details: error handling never raises a protocol error but returns a structured error object, and it explicitly states the tool is read-only and idempotent, reinforcing the annotations. No contradictions.

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 well-structured and compact. It starts with the core purpose, immediately gives a concrete example, then explains usage context, error behavior, and safety. Every sentence earns its place with no redundancy.

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's simplicity (2 parameters, no nested objects, output schema present), the description covers all necessary aspects: purpose, example, usage guidelines, error handling, and safety. The output example effectively documents the return structure. No gaps.

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?

Schema coverage is 100%, so baseline is 3. The description adds value by providing a complete example input and output, which illustrates the expected JSON structure and how the parameters map to the result. This goes beyond the schema's text descriptions and helps the agent understand the tool's behavior.

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 verb and resource: 'Compute the selling price needed to hit a target margin percentage.' It also distinguishes from the sibling tool 'unit_economics' by stating it is the 'inverse' and 'solves for price from a target margin,' making the purpose unmistakable.

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?

The description provides explicit guidance: 'Use when the margin is the fixed requirement. Not when the price is already set.' It also mentions the relationship to unit_economics, helping the agent choose between siblings. The retry safety note ('always safe to retry') further guides usage.

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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