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Kanysh Basic

Kanysh Basic

by almukhanomr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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simulation_compare

Compare simulation result artifacts or ensembles by date and metric to reveal performance differences and rank outcomes for model analysis.

Instructions

simulation_compare

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": "simulation_compare"
  }
}

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

D1.7/5.0
Behavior1/5

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

Annotations declare readOnlyHint=false, idempotentHint=false, destructiveHint=false and openWorldHint=false, but the description adds nothing: it does not say what the comparison mutates or persists, that it submits an asynchronous job, or that idempotency_key exists for retry safety. For a non-read-only tool whose schema contains execution policy, timeout, retry, and partial-failure controls, zero behavioral disclosure is a serious gap.

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?

It is one token, but this is under-specification rather than conciseness: there is no front-loaded sentence explaining the operation and nothing to trim. Brevity here comes from omission, not economy.

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?

The tool takes a deeply nested argument object with mutually exclusive results/ensemble inputs, metric selection, report ordering, and a full execution policy block, and has no output schema. Given that complexity, the description must carry the load of explaining semantics and results — it provides none, leaving an agent unable to invoke this correctly from the description alone.

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% — every nested field (dates, metric, results, ensemble, execution, allow_partial, idempotency_key) carries its own description. Under the stated rule, a fully documented schema sets the baseline at 3, and the description adds nothing beyond it, so 3 is the ceiling rather than a judgment of description quality.

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?

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?

There is no guidance on when to use this tool versus alternatives. Sibling names such as scenarios_compare, ensemble_compare, model_diff, and simulation_results make discrimination essential, and the description offers no routing information at all.

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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