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UditMahaldar

HP ALM MCP Server

by UditMahaldar

alm_add_design_steps

Add design steps to a checked-out test case in HP ALM. Specify steps with name, description, and expected result, optionally replacing existing steps.

Instructions

Add design steps to a test case (test must already be checked out).

Args: test_id: ALM ID of the test case (must be in Checked_Out state). steps: List of steps, each a dict with "name", "description", "expected". Example: [{"name": "Step 1", "description": "Open browser", "expected": "Browser opens"}] delete_existing: If true, deletes all current steps before adding new ones.

Returns: {"test_id": "", "steps_added": , "delete_existing": true/false}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
test_idYes
stepsYes
delete_existingNo
Behavior4/5

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

With no annotations provided, the description carries full behavioral disclosure. It explains the prerequisite (checked out state), the steps format with an example, the delete_existing behavior, and the return value. It does not mention potential side effects like version updates or permission requirements, but the core mutation behavior is clearly described.

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, well-structured, and front-loaded. It opens with the core purpose and precondition, then details parameters with example, and concludes with return value. Every sentence earns its place with no redundant information.

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

Completeness5/5

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

Given the tool's moderate complexity (3 parameters, no nested objects, no output schema), the description covers all necessary aspects: precondition, parameter semantics with example, behavioral options, and return structure. It is fully complete for an agent to select and invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It does so excellently: test_id is explained as 'ALM ID' with state requirement, steps are described as dicts with required keys and an example, and delete_existing has explicit behavior. This adds significant value beyond the schema's type-only definitions.

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 verb 'add' and resource 'design steps to a test case', with a crucial precondition ('test must already be checked out'). This distinguishes it from siblings like 'alm_create_test_case' which creates a test case from scratch, and 'alm_update_test_case' which modifies general test case fields.

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

Usage Guidelines4/5

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

The description provides clear context on when to use: the test must be checked out first. It explains the delete_existing option. However, it does not explicitly mention when not to use this tool (e.g., when the test is in another state) or suggest alternative tools like alm_update_test_case for non-step modifications.

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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