QASE MCP Server

create_plan

Create a new test plan in QASE by specifying code, title, and test cases to organize testing activities.

Instructions

Create a new test plan

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": {
      "code": "<code>",
      "title": "<title>",
      "cases": "<cases>"
    },
    "name": "create_plan"
  }
}

Input Schema

Name	Required	Description	Default
`code`	Yes
`title`	Yes
`description`	No
`cases`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedMay 18, 2025

TDQS

C2.6/5.0

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 of behavioral disclosure. 'Create a new test plan' implies a write operation, but it doesn't disclose permissions needed, whether creation is idempotent, error handling, or response format. It lacks details on behavioral traits beyond the basic action.

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?

The description is a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for a basic tool definition, though it may be too concise given the lack of detail in other dimensions.

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

Completeness2/5

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

Given the complexity (a creation tool with 4 parameters, no annotations, and no output schema), the description is incomplete. It doesn't explain return values, error conditions, or how parameters interact. For a tool that likely mutates data, more context is needed to guide an AI agent effectively.

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 description coverage is 0%, so the description must compensate for undocumented parameters. It doesn't add any meaning beyond the input schema—no explanation of what 'code', 'title', 'description', or 'cases' represent, their formats, or constraints. With 4 parameters and low coverage, this is inadequate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Create a new test plan' states a clear verb ('Create') and resource ('test plan'), but it's vague about what a 'test plan' entails and doesn't distinguish it from sibling tools like 'create_project', 'create_suite', or 'create_case'. It provides a basic purpose but lacks specificity about the domain or scope.

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 alternatives. Sibling tools include other creation tools (e.g., 'create_case', 'create_suite') and update tools (e.g., 'update_plan'), but the description doesn't mention prerequisites, context, or exclusions. Usage is implied only by the tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.