failed-tests-summary

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

No annotations are provided, so the description carries the full burden. It discloses the aggregated nature, the 24h-ish time window, and that it includes the most recent failing rows. However, it does not explicitly state side effects, auth requirements, or whether it is read-only. For a composite tool, a bit more detail on behavior would be beneficial, but what is provided is adequate.

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 two sentences: the first introduces the aggregated view and grouping, and the second explains that it replaces multiple tool calls. Every word earns its place; no fluff. Front-loaded with key information.

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's complexity (composite with 3 parameters, no output schema), the description provides a good overview: aggregation, grouping by dataset, time window, and replacement of multiple calls. It could have included a bit more detail on the exact structure of the response, but for a 3-param tool it is largely complete.

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 coverage is 100%, with each parameter having a clear description. The tool description does not add additional meaning beyond what the schema already provides; it only mentions defaults implicitly. Therefore, baseline 3 is appropriate.

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 what the tool does: it aggregates dbt failed tests and DQ check failures grouped by dataset with the most recent failing rows. It explicitly distinguishes itself from siblings by noting it replaces three separate tool calls (dbt-failed-tests, dq-failed-checks-by-dataset, dq-list-checks), making its composite nature clear.

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 explicitly states that this tool replaces 3+ separate tool calls, giving strong guidance on when to use it (when a consolidated view is needed). It does not provide explicit exclusions or when-not conditions, but the context is clear enough for an agent to infer appropriate usage.

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