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Kanysh Basic

Kanysh Basic

by almukhanomr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

calculation_plan

Prepares a static volumetrics plan that checks scientific inputs, returns NEEDS_INPUT for missing data, and pins input bytes, assumptions, and runtime without running numerical jobs.

Instructions

Prepare static volumes plan. Missing scientific inputs return NEEDS_INPUT/questions without compute. READY plan pins input bytes, assumptions and runtime. No numerical jobs run.

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": "calculation_plan"
  }
}

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

A3.8/5.0
Behavior4/5

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

Annotations only say it is a non-destructive, non-idempotent write; the description adds real behavioral value by disclosing the two possible outcomes (NEEDS_INPUT with questions and no compute, or READY pinning input bytes, assumptions, and runtime). It stops short of saying the READY plan is persisted as an artifact that later tools consume, which matters given readOnlyHint=false.

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?

Three short sentences, front-loaded with the action and immediately followed by the two outcome modes. Nothing is redundant with the title or the schema.

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 deeply nested schema with no output schema, the description correctly focuses on return semantics (NEEDS_INPUT vs READY) rather than repeating field docs. It could say more about the READY payload contents or that the plan feeds calculation_run/plan_validate, but the core call decision is covered.

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% and every nested field (bo, grid, zones, inputs, contacts, uncertainty, execution) carries its own doc string, so the schema does the heavy lifting. The description adds no parameter-level guidance such as which fields drive NEEDS_INPUT, so the baseline 3 applies.

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?

"Prepare static volumes plan" gives a specific verb and resource, and "No numerical jobs run" separates it from compute siblings like calculation_run or volumetrics_calculate. It never names those siblings explicitly, so the distinction has to be inferred from context rather than stated.

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

Usage Guidelines3/5

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

The NEEDS_INPUT/READY framing implies this is a pre-flight step, but the description never says when to choose this over plan_validate, calculation_run, or ensemble_plan. The agent must infer the intended sequence from the outcome states alone.

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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