correlation_matrix

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

No annotations are provided, so the description must fully disclose behavioral traits. However, it only states the computation and identification of pairs, without mentioning read-only nature, computational cost, data requirements, or output specifics. The agent lacks insight into side effects or required permissions.

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 with no extraneous information. It front-loads the core action and purpose, making it highly scannable for an AI agent.

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?

While the description explains what the tool does, it does not mention output format or additional context like return structure (e.g., matrix with tickers and correlation values). Given the absence of an output schema, the agent may be uncertain about the result. More details on the output would improve completeness.

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 each parameter having detailed descriptions (e.g., ticker constraints, lookback_days range, method enum meanings). The tool description adds no additional parameter semantics beyond the schema, so baseline score of 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?

The description clearly states the tool computes a pairwise correlation matrix for assets and identifies correlated pairs and diversification opportunities. This is a specific verb+resource that distinguishes it from siblings like 'analyze_risk' or 'optimize_portfolio'.

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?

No guidance is provided on when to use this tool versus alternatives. It does not mention preconditions, exclusion criteria, or refer to other tools. The description implies usage for correlation analysis but lacks explicit when-to-use or when-not-to-use context.

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