find_correlations

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

With no annotations, the description carries the full burden. It discloses that an absolute threshold is used and that it finds pairs, but does not mention whether the operation is read-only, how missing values are handled, or the exact nature of the output. It adds some behavior (absolute threshold) but lacks depth expected for an unannotated tool.

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 a single sentence of twelve words, front-loaded with the action verb. Every word contributes meaning, with no redundancy or filler.

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 simple analysis tool with an output schema, the description provides adequate core context. The main gap is the ambiguous 'path' parameter, but overall the tool's simplicity and output schema reduce the burden on the description. The threshold behavior is clearly disclosed.

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 0%, so the description must compensate. It clarifies that 'threshold' is an absolute threshold on correlation strength, but 'path' is left unexplained (likely a dataset path, but not stated). Only one of two parameters receives any semantic enhancement.

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 'Finds strongly correlated numerical feature pairs above a specified absolute threshold' uses a specific verb ('finds') and resource ('correlated numerical feature pairs'), with a clear scope condition. It clearly distinguishes from sibling tools like dataset_shape or detect_outliers, which address different analysis tasks.

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 usage for correlation analysis but provides no explicit guidance on when to use this tool versus alternatives, or any exclusions (e.g., non-numerical data). The context from sibling names suggests a data analysis suite, but no clear when-to-use/when-not-to-use is stated.

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