add_use_caseAdd a use case to a draft UT's scenario (title required, optional description). Use cases group related tasks. Returns the new useCaseId to use with add_task. Only works on PREPARING drafts.
| Name | Required | Description | Default |
|---|---|---|---|
| utId | Yes | ||
| title | Yes | ||
| description | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide readOnlyHint=false, confirming a write operation. The description adds valuable behavioral context: the state requirement (PREPARING drafts) and the return of a useCaseId. No contradictions found. This exceeds the baseline set by annotations.
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?
Three concise, front-loaded sentences deliver the core action, use case, return value, and constraint. No unnecessary words or redundancy.
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 has no output schema, but the description explains the return value (useCaseId) and the prerequisite state (PREPARING drafts). It also indicates the sequential relationship with add_task. For a simple create operation with three parameters, this is reasonably complete, though it omits error handling or detailed side effects.
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?
Schema description coverage is 0%, so the description must compensate. It clarifies that title is required and description is optional, but does not explicitly explain utId (though 'draft UT's scenario' implies it is the UT identifier). The description adds some meaning beyond the raw schema but leaves the utId parameter somewhat implicit.
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: 'Add a use case to a draft UT's scenario' with specific verb and resource. It also distinguishes from sibling tools like add_task and update_use_case by focusing on creation of a use case within a draft scenario.
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 context for when to use the tool: it groups related tasks and returns a useCaseId for use with add_task. It also specifies a critical constraint: 'Only works on PREPARING drafts.' However, it does not explicitly contrast with update_use_case or delete_use_case, but the usage context is 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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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.