update_use_caseUpdate a use case in a draft UT (any of: title, description). Use cases group related tasks. Only works on use cases of PREPARING drafts.
| Name | Required | Description | Default |
|---|---|---|---|
| title | No | ||
| useCaseId | Yes | ||
| description | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already indicate readOnlyHint=false and idempotentHint=true. The description adds meaningful behavioral context beyond annotations by restricting operation to PREPARING drafts and stating which fields can be modified. It does not contradict annotations and provides useful constraints, though it does not discuss errors or reversibility.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences, front-loaded with the primary action. The sentence 'Use cases group related tasks' adds useful domain context, and the constraint about PREPARING drafts is essential. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (3 params, no output schema) and the description covers the core operation, scope, and restrictions. It does not mention what happens if the draft is not in PREPARING state or the return value, but for this low complexity and given annotations, it is adequate and sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. It explains that title and description are the updatable fields ('any of: title, description'), which adds meaning beyond the raw schema. However, it does not describe the useCaseId parameter's format or purpose, leaving some gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update a use case') and the resource scope ('in a draft UT'), distinguishing it from siblings like update_ut, update_task, and add_use_case. It also specifies the updatable fields ('title, description'), 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear context: it is for updating title/description of use cases and includes a specific exclusion ('Only works on use cases of PREPARING drafts'). However, it does not explicitly name alternative tools for when this tool should not be used, so it falls short of a full 5.
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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Every tool targets a distinct resource and action. Even get_ut, which returns comprehensive data, doesn't replace the specialized get_session, get_transcript, or get_quantitative_report for detailed views. No two tools have overlapping purposes.
All names follow a verb_noun pattern with underscores (e.g., add_task, get_ut, list_workspaces). The main inconsistency is using 'create' for UTs (create_ut) but 'add' for child entities (add_use_case, add_task), and having a separate update_scenario instead of folding it into update_ut, but the convention is still predictable.
With 18 tools, the set is slightly above the typical 3-15 well-scoped range, but the domain of usability testing requires distinct operations for drafting (use cases, tasks, scenario), reading results (reports, sessions, transcripts), and comparison. Each tool has a clear role, so the count feels reasonable rather than excessive.
The tool surface covers the core lifecycle: create, read, update, and delete for tasks/use cases, plus comprehensive retrieval of results and notes. Minor gaps include no delete_ut (UTs cannot be removed) and no explicit status change or cloning mechanism, but these are likely intentional app-side actions, so the surface is not severely incomplete.