failed-tests-summary

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

With no annotations, the description carries the full burden. It discloses the time window (24h-ish) and aggregation behavior but does not mention read-only nature, permissions, or what happens with no failures. It is adequate but not fully explicit.

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 extremely concise with a single sentence stating purpose and a parenthetical listing replaced tools. No wasted words, front-loaded.

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 absence of an output schema, the description partially compensates by indicating the output includes grouped data and most recent failing rows. It could be more detailed about exact structure, but is sufficient with sibling context.

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%, but the description adds value by linking recentRuns to dbt runs and sinceHours to DQ checks, providing context beyond the generic schema descriptions. This clarifies how the parameters relate to the data sources.

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 provides an aggregated view of dbt failed tests and DQ check failures grouped by dataset with the most recent rows. It also explicitly mentions it replaces three other tools, distinguishing it 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?

The description explicitly tells when to use this tool by stating it replaces three specific sibling tools (dbt-failed-tests, dq-failed-checks-by-dataset, dq-list-checks), providing clear guidance on usage context.

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