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lends-mcp-server

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Lends Math Scale Price To E8

lends_math_scale_price_to_e8
Read-onlyIdempotent

Scales a positive oracle price to 8 decimals (e8) by adjusting for the provided decimal count, producing a normalized integer for protocol use.

Instructions

Normalize a positive oracle answer to 8 decimals.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "answer": "<answer>",
      "decimals": "<decimals>"
    },
    "name": "lends_math_scale_price_to_e8"
  }
}

Input Schema

NameRequiredDescriptionDefault
answerYes
decimalsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description's main contribution is specifying the input ('positive oracle answer') and target precision. It adds useful semantic context but does not describe the actual scaling/rounding behavior or output form; with annotations covering the safety profile, a 3 is appropriate.

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

Conciseness4/5

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

The description is a single front-loaded sentence with no filler or redundant phrases. It is appropriately terse, though the terseness sacrifices critical parameter-level detail that could have been added without bloat.

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

Completeness2/5

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

For a simple read-only math function with 2 parameters and strong safety annotations, the description is close but incomplete: the meaning of 'decimals' remains ambiguous, and with no output schema the return format is also unspecified. These gaps are enough to cause an agent to call the tool with the wrong parameter semantics.

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 0%, so the description must define both parameters. It explains 'answer' as a positive oracle answer but gives no explanation of the 'decimals' parameter, which is essential for understanding how to use the tool. An agent cannot determine whether 'decimals' is the input's current scale, the target scale, or something else.

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

Purpose4/5

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

The description names a specific action ('Normalize'), a specific input class ('positive oracle answer'), and a target format ('8 decimals'), which distinguishes it from the health/liquidation/collateral math siblings. It does not explicitly use the word 'price' from the tool name or contrast itself with lends_math_convert_decimals_exact, so it falls just short of fully differentiating itself.

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

Usage Guidelines2/5

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

No guidance is given about when to use this tool instead of the many sibling math tools, particularly lends_math_convert_decimals_exact which likely performs a related decimal conversion. The description implies it is for normalizing oracle answers but does not state prerequisites, exclusions, or alternatives.

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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