get_utReturns everything about one UT: its scenario (use cases → tasks), quantitative results, and all sessions with notes and transcript excerpts. The structured output includes scenario use-case and task ids — pass those to add_task / update_task when editing an existing draft.
| Name | Required | Description | Default |
|---|---|---|---|
| utId | Yes | ||
| includeFullTranscript | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already communicates the read-only nature. The description adds that the output includes scenario use-case and task IDs for downstream editing, and lists the data categories returned. No contradiction, but no additional behavioral details beyond that.
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?
Two sentences, front-loaded with a clear summary, and the second sentence provides actionable guidance without unnecessary detail. Every word earns its place.
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?
With no output schema, the description lists main data categories and downstream use of IDs, but omits any explanation of the includeFullTranscript parameter and does not describe the return structure in detail. It is adequate for a read-only fetch but leaves gaps.
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% and the tool description does not explain either utId or includeFullTranscript. The mention of IDs in the description refers to output values, not input parameters, leaving the optional boolean completely undocumented.
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 'Returns everything about one UT' and enumerates the contents (scenario, quantitative results, sessions with notes and transcript excerpts), making it distinct from sibling tools like get_session or get_quantitative_report.
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 clearly implies when to use this tool (when you need full context of a single UT) and gives actionable guidance to pass output IDs to add_task/update_task for editing. No explicit exclusions, but the context is clear.
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.