delete_use_caseDelete a use case from a draft UT, including every task inside it. Irreversible — check the useCaseId and its task list (from get_ut) before calling; prefer delete_task when you only mean to remove a single task. Only works on PREPARING drafts.
| Name | Required | Description | Default |
|---|---|---|---|
| useCaseId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructive intent, but the description adds irreversibility ('Irreversible'), scope ('including every task inside it'), and a state constraint ('Only works on PREPARING drafts'). These go beyond what annotations communicate and help the agent understand the full impact.
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 compact and front-loaded. The first sentence states the core purpose, and the second packs necessary warnings and alternatives without fluff. Every clause contributes useful information.
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?
For a destructive single-parameter tool, the description covers what is deleted, irreversibility, a verification step, the state constraint, and an alternative tool. No output schema is needed, and the information provided fully equips an agent to call the tool correctly.
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?
The schema provides only the raw string type for useCaseId with 0% coverage. The description adds meaning by referring to 'the useCaseId' and suggesting to check its task list from get_ut, making it clear this is the identifier of the use case. It doesn't detail format, but the name is self-explanatory and the guidance is sufficient for a single simple parameter.
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 explicitly states 'Delete a use case from a draft UT, including every task inside it' with a specific verb and resource, and distinguishes from delete_task by noting it removes the entire use case including its tasks.
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?
It provides direct alternatives ('prefer delete_task when you only mean to remove a single task') and a state constraint ('Only works on PREPARING drafts'). It also advises verifying the useCaseId via get_ut before calling, acting as a clear precondition.
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.