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academic-stats-advisor

academic-stats-advisor

by ganlin770
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

check_assumptions

Lists assumptions for a chosen statistical test, details how to verify each, and provides steps to address violations.

Instructions

List the assumptions of a specific test, how to check each, and what to do if violated.

Pass a test_id from recommend_test / list_supported_tests (e.g. 'independent_t', 'one_way_anova', 'pearson', 'chi_square_independence').

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": {
      "test_id": "<test_id>"
    },
    "name": "check_assumptions"
  }
}

Input Schema

NameRequiredDescriptionDefault
test_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It describes the read-only nature (listing assumptions) and corrective actions, but gives no detail on side effects or post-conditions. Adequate for low-risk 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?

Two sentences: first states purpose, second provides usage guidance. No redundant information, front-loaded.

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?

Given simple tool with one parameter and no output schema, description covers purpose, parameter source, and return content (list). Could mention output format but not necessary.

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

Parameters4/5

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

Schema has 0% description coverage for the only parameter, test_id. Description compensates by specifying that the value must come from recommend_test/list_supported_tests and providing example strings, adding essential context 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?

Description clearly states the action: 'List the assumptions of a specific test', identifies the resource (test_id), and differentiates from siblings like interpret_result and recommend_test by specifying what it returns.

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?

Explicitly instructs to pass a test_id from recommend_test/list_supported_tests, with examples. Does not state when not to use, but context is clear.

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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