Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Although readOnlyHint is already declared, the description adds behavioral context by explaining the return shape (names and row counts, or columns and rows with dataSetId) and the prerequisite of project context. It does not mention error cases or edge behavior, but the read-only nature is clearly implied.

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 concise, with no redundant information. It packs essential details (what it lists, when to use, what dataSetId does, prerequisite) into three clear sentences.

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?

Despite no output schema, the description summarizes the return format (names and row counts, or columns and rows for a single set). It also covers the prerequisite for project context and the alternative to manage, making it self-contained for an agent to decide and invoke 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?

Schema already describes each parameter, but the description adds crucial relationships: testSuiteId is required unless dataSetId is provided, and dataSetId returns the set with rows. This goes beyond the schema and helps the agent choose parameters correctly.

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 tool lists test data sets of a test suite, and contrasts with manage_test_data_set for creation/import. It also explains the behavior when dataSetId is provided (returns rows), making the purpose specific and distinct from siblings.

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?

Explicitly says 'Use this to browse data sets' and directs to manage_test_data_set for create/change/import. Also notes requirement for project context and clarifies testSuiteId is required unless dataSetId is given, providing clear when-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.