sample_failing_rows

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

With no annotations, the description must convey behavioral traits. It discloses that the tool fetches rows and that the limit is intentionally small. It also implies the operation is read-only via the verb 'Fetch'. However, it does not describe error behavior for invalid test_name, response format, or what happens when no rows exist. This leaves some transparency gaps, but the provided details are meaningful.

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 succinct and well-structured. It opens with a one-sentence purpose, followed by a clear Args list. Every sentence earns its place, with no fluff or repetition. The format is front-loaded and easy to parse.

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 output schema is present, the description does not need to detail return values. It covers the tool's purpose, parameter semantics, and usage sequence, which is sufficient for a simple read operation. It could mention edge cases (e.g., no failing rows) but these are likely covered by the output schema. Overall, it is complete for its complexity.

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?

Even though schema descriptions are absent (0% coverage), the description's Args section compensates fully. It explains test_name as 'the test's name or unique_id' from list_failing_tests, and limit as 'maximum rows to return (kept small on purpose)'. This adds meaning beyond the bare schema and clarifies how to supply each parameter 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's function: 'Fetch the actual rows that caused a test to fail.' This is a specific verb+resource combination that distinguishes it from sibling tools like list_failing_tests (which lists tests) and run_summary (which provides summaries). The purpose is unambiguous and immediately recognizable.

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 provides explicit usage context by stating test_name is 'as returned by list_failing_tests', indicating the workflow of calling list_failing_tests first. It also adds the caution that limit is 'kept small on purpose', setting expectations for output size. However, it does not explicitly state when not to use this tool or mention alternative tools for other scenarios, so it falls short of a perfect score.

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