check_correlations

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

With no annotations, the description carries the burden and does well: it discloses default vs optional methods, target-correlation leakage flag (r>0.95), the 50-column cap, and output structure (top 50 pairs + full matrix artifact). It does not mention permissions, error cases, or missing-data behavior, so not a 5.

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 reasonably compact and front-loaded with the core purpose, then parameter specifics and output behavior. Minor artifacts like 'Level 2' and line breaks are acceptable; each sentence contributes useful 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?

The description explains key limitations (50-column cap), output destinations (result vs artifact), and target-leakage behavior, and an output schema exists to cover return fields. It does not explain source_id semantics or when-to-use guidance, which keeps it from being fully 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 0%, but the description adds meaning for 'methods' (pearson default, spearman optional) and 'target' (triggers target-correlations and leakage flag). 'source_id' is not described, though it is inferable from the tool context. This is partial but not full compensation.

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 identifies the tool as 'Pairwise correlation analysis (Level 2)' and specifies its behavior: methods, target handling, leakage flagging, column cap, and output. This distinguishes it from sibling tools like check_multicollinearity, check_leakage, and plot_correlation_heatmap.

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 implies when to use the tool (when pairwise correlations are needed) and details options like methods and target, but it does not explicitly state when to prefer this over alternatives or mention exclusions/prerequisites. No sibling alternatives are named.

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