update_taskUpdate a task in a draft UT (any of: title, successCriteria, instruction, observationPoints[], probingQuestions[], observerMeasurementEnabled, participantRatingEnabled). Only works on tasks of PREPARING drafts.
| Name | Required | Description | Default |
|---|---|---|---|
| title | No | ||
| taskId | 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 already provide readOnlyHint=false and idempotentHint=true. The description adds the draft-status constraint and the partial-update nature ('any of'). However, it does not explain side effects, permission requirements, or what happens if the task is not in PREPARING state. Some behavioral context is added but not extensive.
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 extremely concise: one sentence with the core action plus a parenthetical list of editable fields, and a second sentence stating a key constraint. There is no wasted language, and the most important information is front-loaded.
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?
Given the tool has 8 parameters, no output schema, and only basic annotations, the description could be more complete. It covers purpose and the draft constraint, but omits details like return values, error handling, and whether partial updates are true (e.g., unspecified fields remain unchanged). It is adequate for a simple update but not fully comprehensive.
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 has 0% descriptor coverage, so the description must compensate. It lists the updatable fields, matching the schema property names, which helps the agent know which are editable. However, it does not explain the meaning of each field (e.g., successCriteria, probingQuestions) beyond their names, nor the required taskId parameter. Partial compensation only.
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 specifies the verb 'Update' and the resource 'a task in a draft UT', and enumerates the exact fields that can be modified. This distinguishes it from sibling tools like add_task and update_ut, which target different resources or operations. 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?
The description gives a clear usage context: use this to update task fields within a draft UT, and explicitly states a constraint ('Only works on tasks of PREPARING drafts'). It does not explicitly name alternative tools for non-PREPARING states, but the draft constraint implies when it should be used. This is sufficient guidance for most 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.