add_taskAdd a task to a use case (title required; optional successCriteria, instruction, observationPoints[], probingQuestions[], observerMeasurementEnabled, participantRatingEnabled). Returns the new taskId. Only works on use cases of PREPARING drafts.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | ||
| useCaseId | Yes | ||
| instruction | No | ||
| successCriteria | No | ||
| probingQuestions | No | ||
| observationPoints | No | ||
| participantRatingEnabled | No | ||
| observerMeasurementEnabled | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only indicate readOnlyHint=false. The description adds useful behavioral context by stating the return value ('Returns the new taskId') and the draft-state limitation, which goes beyond the simple mutation flag and helps the agent anticipate side effects.
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 a single, compact sentence that front-loads the action and includes a parenthetical parameter list. Every word earns its place, with no redundancy or filler.
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 simple add operation with no output schema, the description covers purpose, return value, and an important precondition. It doesn't explain the semantics of optional fields, but given the tool's straightforward nature and the availability of sibling tools for context, this is acceptable.
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 description lists all parameters (title, successCriteria, instruction, observationPoints, etc.) and marks title as required, matching the schema. However, with 0% schema description coverage, it doesn't explain the meaning of each field (e.g., what successCriteria represents), so it only partially compensates for the schema's lack of detail.
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 task to a use case') with a specific verb and resource, distinguishing it from sibling tools like add_use_case, update_task, and delete_task. The scope is 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?
It provides a clear precondition: 'Only works on use cases of PREPARING drafts,' which tells the agent when this tool is applicable. It doesn't explicitly name alternatives, but the constraint effectively guides usage by excluding non-draft use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.