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spss-studio-mcp

spss-studio-mcp

by CongJyu
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Python
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Spss Get Method Schema

spss_get_method_schema

Retrieve the JSON schema for any registry-backed SPSS method to inspect parameters and orchestrate structured analysis before execution.

Instructions

Get the JSON schema for a registry-backed SPSS method. Useful for structured orchestration and parameter inspection before execution.

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": {
      "tool_name": "<tool_name>"
    },
    "name": "spss_get_method_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
tool_nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden, and it does convey that the method must be registry-backed and that this is a read-style inspection. However it omits error behavior for unknown method names, and says nothing about the safety/permission profile beyond the implied read-only nature.

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?

Two tight sentences, front-loaded with the action and followed by the use case. Every clause earns its place with no filler.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and this is a simple one-parameter read tool. Still, the definition leaves the agent without guidance on valid method identifiers or the relationship to sibling lookup tools, which is the main gap given no annotations.

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 coverage is 0% and the single parameter (tool_name) has no description in the schema. The description hints the argument is a registered method name, but it never states the expected format or how to discover valid values (e.g., via spss_list_supported_methods), so it only partially compensates for the gap.

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?

States a specific verb and resource ("Get the JSON schema for a registry-backed SPSS method") that an agent can distinguish from siblings like spss_list_supported_methods and spss_get_method_support. It is clear what it returns, though it never explicitly contrasts itself with those adjacent tools.

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?

Gives clear context for when to use it ("before execution", "parameter inspection", "structured orchestration"), so the agent knows this is a pre-flight inspection step. It does not name alternatives or state when not to use it, keeping it just below a 5.

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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