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add_test_cases_bulk

Add multiple test cases to TestRail at once using a section ID or hierarchy path (auto-creates missing sections). Returns the IDs of the created cases.

Instructions

Push a batch of test cases to TestRail in one call. Returns the IDs created.

cases items are in the shape returned by prepare_cases_* — each has {title, preconditions, steps:[{step, expected}]}. The server maps that into TestRail's payload format (custom_steps_separated etc.).

Targeting: either section_id directly, or section_hierarchy like 'Auth > Login > Smoke' — missing nodes are created.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
casesYes
suite_idNo
project_idNo
section_idNo
section_hierarchyNo
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses creation behavior, the expected shape of cases items, mapping to TestRail format, and targeting with auto-creation of missing hierarchy nodes. However, it omits potential errors or rate limits.

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 concise with three short paragraphs, each adding essential information. The purpose is front-loaded, and the bullet-like list for cases structure is clear. No extraneous content.

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 the tool's complexity, lack of output schema, and no annotations, the description covers input format and targeting well. It explains the core behavior but could detail the return format further or address error scenarios. Still adequate for an agent to use effectively.

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 coverage is 0%, so the description must add meaning. It explains the complex `cases` parameter structure and the `section_id`/`section_hierarchy` targeting. The `suite_id` and `project_id` parameters are not described but have defaults. Overall, it significantly enhances understanding 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?

The description clearly states the tool's purpose: push a batch of test cases to TestRail and return the IDs created. It effectively differentiates from siblings like create_test_case (single) and add_result (results).

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

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains how to target sections (section_id or section_hierarchy) but does not provide explicit when-to-use or when-not-to-use guidance compared to alternatives like create_test_case. The usage context is implied rather than stated.

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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