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Kanysh Basic

Kanysh Basic

by almukhanomr
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Python
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model_diff

Compare two immutable same-IJK model revisions with explicit tolerances: changed cells/properties, IJK CSV and region GRV/PV/HCPV impacts. Independently verifies geometry volumes.

Instructions

Compare two immutable same-IJK model revisions with explicit tolerances: changed cells/properties, IJK CSV and region GRV/PV/HCPV impacts. Independently verifies geometry volumes. No contact or Bo is inferred, so no STOIIP impact is invented. Rejects differing topology/coordinate metadata.

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": "model_diff"
  }
}

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

A4.4/5.0
Behavior5/5

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

Beyond the annotations, the description discloses important behavior: tolerance-driven comparison, CSV and region-impact outputs, independent geometry-volume verification, no inferred contact or Bo, no invented STOIIP impact, and rejection of incompatible topology/coordinate metadata. This is substantial behavioral context for a non-read-only calculation tool.

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 four tight sentences and is front-loaded with the core comparison purpose. Each sentence earns its place by adding scope, output expectations, verification behavior, or an important non-inference caveat.

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?

For a complex nested-schema tool with no output schema, the description gives a solid account of what is compared and what kinds of outputs to expect, plus key constraints. It stops short of describing job/response handling or all execution-policy implications, but those are largely covered by the schema.

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?

Schema description coverage is 100%, so the detailed nested schema already documents the request fields, tolerances, execution policy, and artifact references. The description reinforces that tolerances are explicit and revisions must be same-IJK, but adds little parameter-level meaning beyond the schema.

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: compare two immutable same-IJK model revisions with explicit tolerances. It also names the output categories (changed cells/properties, IJK CSV, region GRV/PV/HCPV impacts), making it distinguishable from siblings like simulation_compare or regional_volumes.

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?

Usage context is clear: the two revisions must share IJK shape, and differing topology/coordinate metadata is rejected. It does not name alternative tools or explicitly say when to choose those instead, so it falls short of a full when/when-not/alternatives treatment.

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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