get_correlated_failures

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

No annotations are provided, so the description carries the disclosure burden. It adds genuine interpretive value by explaining what a high correlation means, but it says nothing about return format, result limits, or ordering, and does not explicitly confirm the read-only nature of the call.

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?

Two tight sentences; the core operation is front-loaded and the second sentence earns its place by explaining the diagnostic significance of the result.

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?

For a five-parameter read-only analysis tool with full schema coverage and no output schema, the description covers what the tool does and how to interpret its output. Only the shape of the returned result is left unaddressed.

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 100%, with all five parameters (including defaults for days and min_correlation) documented in the schema itself. The description adds no parameter meaning beyond that, so the baseline 3 applies.

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?

States a specific verb ('Find') and resource ('tests that tend to fail together with a given test'), including the analytical relationship being computed. It does not explicitly differentiate itself from near-neighbors like get_failure_patterns, so it falls short of a 5.

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 second sentence ('shared setup issues, test pollution, or dependencies') implies the diagnostic scenario in which this tool is useful, but there is no explicit when-to-use, when-not-to-use, or named alternative among the nine siblings.

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