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Kanysh Basic

Kanysh Basic

by almukhanomr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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horizon_convert_domain

Convert horizon interpretations between time and depth domains using constant velocity or a time-depth table, with datum and origin-Z controls for subsurface model outputs.

Instructions

horizon_convert_domain

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": {
      "request": "<request>"
    },
    "name": "horizon_convert_domain"
  }
}

Input Schema

NameRequiredDescriptionDefault
requestYesTool arguments object (all fields documented; Z is positive upward).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

D1/5.0
Behavior1/5

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

The description adds zero behavioral traits beyond what the basic annotations already imply. Since the description is identical to the name, it offers no contextual value regarding operational constraints or execution behavior.

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

Conciseness1/5

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

While extremely short, the definition fails because the single sentence serves zero informative purpose. It is concise but completely empty of useful content.

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?

Given the complexity of the input schema (highly nested objects, specific engineering concepts like Datum, Interpretation, and Execution policies), a description consisting only of the tool's name is profoundly incomplete for practical use.

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

Parameters1/5

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

Despite the input schema being 100% covered, the description provides no semantic value or interpretive meaning to the complex nested parameters. It fails to add information beyond the structured data.

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

Purpose1/5

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

Tautological: description restates name/title.

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 usage guidelines or operational context are provided in the description. The AI has no guidance on when or why this tool should be chosen over others, even within its highly specialized domain.

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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