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Create Test Layer

create_test_layer

Create new test layers in Allure TestOps to define taxonomy for categorizing test cases by type, such as Unit, Integration, E2E, UI, or API, using a name and optional project ID.

Instructions

Create a new test layer in Allure TestOps.

Test layers define taxonomy for categorizing test cases. Common examples include 'Unit', 'Integration', 'E2E', 'UI', 'API', etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName of the test layer (e.g., 'Unit', 'Integration', 'E2E').
project_idNoAllure TestOps project ID to create the test layer in.
output_formatNoOutput format: 'json' (default) or 'plain'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
nameNo
Behavior2/5

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

Minimal behavioral disclosure beyond creating a layer. Annotations are non-informative (no readOnly, idempotent, or destructive hints). Description does not state side effects, required permissions, or whether the layer is immediately usable. Context beyond schema is lacking.

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 concise sentences with no fluff. First sentence states the action clearly; second provides context about what test layers are. Information is front-loaded and easy to scan.

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?

Adquately covers purpose and one parameter hint, but lacks details on when project_id is needed and output_format effects. Output schema exists, so return values are not required. Overall minimal but meets basic needs.

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 covers 100% of parameters with descriptions. The description reinforces the name parameter with examples but adds no additional meaning to project_id or output_format. Since schema already explains, description adds marginal value.

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?

Clearly states the tool creates a test layer, defines what test layers are (taxonomy for categorizing test cases), and provides concrete examples ('Unit', 'Integration'). Distinguishes from sibling tools like update_test_layer and delete_test_layer by focusing on creation.

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?

No explicit guidance on when to use this tool versus alternatives. Does not mention prerequisites (e.g., requires a project) or when not to use it. Implied usage only from the purpose.

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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