Define required test data for a scenario. Identify preconditions, dependencies, edge cases, and necessary resource states to ensure comprehensive quality assurance.
Explain the test data a scenario needs ("what data do I need to test X"): entity characteristics, resource state, preconditions, dependencies, edge cases, and what not to use.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | No | ||
| question | Yes | ||
| environment | No |
Changes observed during successful MCP inspections.
v0.42.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world behavior. The description adds that this is an explanatory output covering entity characteristics, state, preconditions, dependencies, edge cases, and exclusions, but it does not describe the response format or any operational limitations.
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 front-loaded sentence with a compact list of what the explanation covers. It contains no repeated boilerplate or wasted clauses.
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 description is sufficient for understanding the tool's explanatory purpose but incomplete for its inputs, since domain and environment are undocumented, and there is no output schema to explain the answer format. For a three-parameter explanation tool, this is minimally adequate but has clear 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%, so the description must compensate for all three parameters. It clarifies the required 'question' parameter through the example phrase, but it does not mention what 'domain' or 'environment' mean or how they affect the explanation.
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 states a specific verb and resource: 'Explain the test data a scenario needs', and lists the dimensions of that explanation. It distinguishes itself conceptually from sibling data tools like find_test_data by focusing on explanation, but it does not explicitly name or contrast those alternatives.
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 quoted example 'what data do I need to test X' implies when the tool is appropriate, but the description gives no explicit when-not-to-use guidance or routing to siblings such as sumo_qa_find_test_data or sumo_qa_validate_test_data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.