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update_test_case

Partially update a test case by display_id, with a required dry_run to preview changes before committing. Supplying steps replaces all existing steps.

Instructions

Partially update an existing test case by display_id. If steps is provided, ALL existing steps are wiped and replaced (full-replace — not partial). REQUIRED: call with dry_run: true first. The dry-run shows the full before/after diff including steps. Only call with dry_run: false after explicit human approval.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoNew tags (optional, replaces all).
stepsNoIf provided: FULL REPLACE of ALL steps. Omit to leave steps unchanged.
titleNoNew title (optional).
dry_runNotrue → compute diff + return to caller, no write. false/omit → commit (only after human approval).
priorityNoNew priority (optional).
display_idYesTarget test case display_id, e.g. "APA-3".
descriptionNoNew description (optional).
preconditionNoNew precondition (optional).
platform_tagsNoNew platform tags (optional, replaces all).
automation_statusNoNew automation status (optional).
Behavior5/5

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

No annotations are provided, so the description carries full responsibility. It discloses a critical destructive behavior: 'ALL existing steps are wiped and replaced (full-replace — not partial)' and mandates a dry-run first for safety. This goes beyond a generic update description and alerts the agent to the mutating consequence.

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?

Three sentences, tightly packed. The purpose is front-loaded, followed by the two most critical safety warnings. Every sentence earns its place with zero filler.

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?

For a tool with 10 parameters, no annotations, and no output schema, the description covers the essential workflow and the most dangerous edge case (steps replacement). It doesn't mention that tags and platform_tags also replace-all, but the schema already documents those semantics, so the description is not incomplete. It could briefly note other replace-all fields but is otherwise adequate.

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?

The input schema has 100% description coverage, so baseline is 3. The description adds value by emphasizing 'by display_id', repeating the steps full-replace warning, and explaining that dry-run shows 'the full before/after diff including steps' — a detail not in the schema. This is a modest but meaningful addition.

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 'Partially update an existing test case by display_id', using a specific verb ('update') and resource ('test case') and key parameter. It distinguishes from sibling tools like create_test_case (create) and get_test_case (read), making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly requires 'call with dry_run: true first' and 'Only call with dry_run: false after explicit human approval', providing a clear mandatory workflow. It also clarifies the full-replace behavior for steps, giving the agent precise conditions for safe use.

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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