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x402-inverse-lerp

Inverse Lerp: Inverse Lerp

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aNoA to process
bNoB to process
valueNoValue to process

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / a
      Added value: +{
      +  "description": "A to process",
      +  "type": "string"
      +}
    • addedInput schema / properties / b
      Added value: +{
      +  "description": "B to process",
      +  "type": "string"
      +}
    • addedInput schema / properties / value
      Added value: +{
      +  "description": "Value to process",
      +  "type": "string"
      +}
  2. First observed

TDQS

D1.5/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden, yet it discloses nothing: not the math being performed, not the behavior when a==b (division by zero), not the output range, not whether it is pure/idempotent. A one-line tautology gives the agent zero behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely short but not concise in a useful sense: the phrase 'Inverse Lerp' is duplicated verbatim with no additional information, so the text is under-specified rather than efficient. Nothing is front-loaded because nothing is said.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations, no output schema, no real parameter documentation, and no explanation of the operation or its edge cases, the definition is wholly inadequate for an agent to invoke this tool correctly in a catalog of hundreds of math siblings.

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

Parameters2/5

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

Schema description coverage is nominally 100%, but each parameter's description is a placeholder ('A to process', 'B to process', 'Value to process'), which conveys no semantics at all. The description adds nothing, so the agent cannot tell that 'a' is the range start, 'b' the range end, and 'value' the point to invert, nor why numeric inputs are typed as strings.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is 'Inverse Lerp: Inverse Lerp', a pure restatement of the tool name with no verb or explanation of what the operation computes (the t such that lerp(a,b,t)=value). It does not distinguish the tool from siblings like x402-lerp, x402-lerp-value, x402-map-to-range, x402-remap, or x402-interpolate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance whatsoever on when to use this versus lerp-family or range-mapping siblings, and no statement of prerequisites or input constraints. The agent must guess entirely from the name.

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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