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create_test_case

Generate a standardized MCP test case by defining the tool name, input data, and expected result. Use it to validate MCP tool behavior consistently.

Instructions

Create a standardized MCP test case.

Args: name: Short name of the test.

tool_name:
    MCP tool being tested.

input_data:
    Input that should be passed to the tool.

expected_result:
    Expected behavior/result.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes
`tool_name`	Yes
`input_data`	Yes
`expected_result`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 13, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It says 'Create' (a mutation) but does not disclose where the case is persisted, whether it is durable, whether duplicates are allowed, or what permissions are needed. For a write tool with zero annotation coverage this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded with the core action, followed by a clean parameter list. It is slightly padded by restating obviously-named fields, but nothing is wasted at length.

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. Still, for a mutation tool with no annotations and 0% schema coverage, the description should cover persistence/side-effect and uniqueness behavior, which it omits.

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 0%, so the description is the only documentation for the four parameters, and it does name and gloss each one. However the glosses are minimal and largely echo the parameter names ('name: Short name of the test'), adding little beyond the schema structure.

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?

The description states a specific verb and resource: 'Create a standardized MCP test case.' It clearly distinguishes itself from the validate_* siblings by action, though it doesn't explicitly say how it differs from them beyond the verb.

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

Usage Guidelines2/5

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 the validate_github_result and validate_rag_result siblings, nor any prerequisites such as whether a test suite must already exist. The agent must infer usage entirely.

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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