mcp-testops

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create_test_plan

Creates a test plan in Allure TestOps from a name and optional project, tree, AQL base filter, and tree selection so teams can organize and run selected tests.

Instructions

Create a test plan and return {ok, id, name, projectId}.

base_rql is the AQL selection of the plan (e.g. tag.name = "smoke"). tree_selection_json: {"leafsInclude": [1001], "inverted": false} - the plan takes TreeSelectionDto, which has no filterId (that one belongs to running cases).

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": {
      "name": "<name>"
    },
    "name": "create_test_plan"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes
`tree_id`	No
`base_rql`	No
`project_id`	No
`tree_selection_json`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.5Nov 9, 2026

TDQS

B3.2/5.0

Behavior3/5

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

With no annotations, the description carries the full burden: it discloses the return payload and clarifies that tree_selection_json takes TreeSelectionDto (which has no filterId), which is genuinely useful domain context. However, it says nothing about permissions, side effects, validation failures, or whether tree_id/project_id are required for the plan to be usable.

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-loads the purpose and return value before the parameter notes. The tree_selection_json sentence is slightly compressed and cryptic, but no sentence is wasted.

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 the return-value explanation is a bonus rather than a requirement, and the two non-obvious parameters get examples. Still, for a five-parameter mutation with no annotations, the missing usage guidance and three undocumented parameters leave the definition only minimally complete.

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 must compensate. It does explain base_rql with an AQL example and tree_selection_json with a literal JSON example plus the filterId caveat, but leaves name, tree_id, and project_id completely unelaborated (e.g. defaults, mutual exclusivity, what tree_id refers to).

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 opens with a specific verb and resource ('Create a test plan') and even states the return shape {ok, id, name, projectId}, so an agent immediately knows what the tool produces. It does not explicitly differentiate itself from update_test_plan or list_test_plans, but the create verb is unambiguous.

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 such as create_test_case or update_test_plan, and no stated prerequisites (e.g. required project or tree). The agent must infer context entirely from the name.

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