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update_run_test_case

Update the assignee and result status for a test case in a manual run. Accepts case key, RTC ID, or _id, and sets the status to passed, failed, blocked, skipped, or retest.

Instructions

Set the assignee and/or result for one test case inside a manual run — exactly what clicking 'Assign to' and changing the result pill does in the UI. Requires write permission. rtcRef accepts the caseKey ('TC-156'), the internal tcm_rtc_... RTC ID, or the underlying test case _id. Works for both already-touched cases and 'untested' virtual cases (the server auto-creates the per-case record on first edit). IMPORTANT: updates.assigneeUserId accepts an email OR a User _id — both work. updates.result canonical values are 'untested', 'passed', 'failed', 'blocked', 'skipped', 'retest' — pass display ('Passed', 'Blocked') or canonical form, server normalizes lowercase+underscored. To assign or update multiple cases at once, call this tool in parallel (one call per case).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runIdYesInternal run _id or counter-style ID e.g. 'RUN-12' (required).
rtcRefYesPer-case record reference — `tcm_rtc_...` _id, caseKey ('TC-156'), or underlying test case _id (required).
updatesYesFields to update. Quick verdict fields: assigneeUserId (email or _id, pass null to unassign), result/status (display or canonical form), elapsed (seconds). Detailed-mode fields: comment (HTML), linkedIssues, attachments, stepResults (e.g. [{order, status, comment}]). Quick and detailed are mutually exclusive — mixing an assignee with detailed fields is rejected server-side.
projectIdYesProject ID (required).
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses write permission requirements, that the server auto-creates records on first edit, that rtcRef accepts multiple ID formats, that assigneeUserId accepts email or _id, that result values are normalized, and that mixing quick and detailed fields is rejected.

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 dense and front-loaded with the core purpose, but it is on the longer side. However, every sentence adds essential behavioral or parameter detail, so no information is wasted. The 'IMPORTANT:' marker helps prioritize key facts.

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 complexity of a nested 'updates' object, no annotations, and no output schema, the description is remarkably complete. It covers input formats, server behavior, permission requirements, normalized values, and usage for multiple cases. It leaves little room for ambiguity.

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?

Although schema coverage is 100%, the description substantially enriches parameter meaning: it gives concrete examples for rtcRef (TC-156, tcm_rtc_..., _id), clarifies assigneeUserId accepts email OR _id, enumerates canonical result values, and explains the mutually exclusive updates modes. This goes well beyond the schema's baseline.

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 opens with a specific verb and resource: 'Set the assignee and/or result for one test case inside a manual run.' It uses a UI analogy to clarify the exact action and clearly distinguishes itself from sibling tools like update_manual_test_case by scoping to 'inside a manual run.'

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: requires write permission, works for both touched and untested cases, and explicitly advises calling in parallel for multiple cases. It does not explicitly name alternative tools or say when not to use this tool, but the UI analogy and run-specific scope make the intended use clear.

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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