analyze_data_insights

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

No annotations are provided, so the description carries the behavioral transparency burden. It supplies useful behavioral detail: modes are mutually exclusive, date_range must be an object rather than an integer, defaults are given, and the result is JSON. It does not explicitly state that the tool is read-only, but its analysis-only framing makes that risk minor.

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 organized into clearly titled sections, with each parameter explained in one line and concrete examples at the end. There is no fluff: every sentence conveys needed selection, invocation, or formatting 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?

Given a five-parameter tool with an empty schema and no annotations, the description is unusually complete. It covers all parameters, default values, mode-specific applicability, return format, and examples—an agent can call it correctly without further inference. The output schema is present elsewhere, so the terse return description suffices.

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?

The schema has 0% description coverage and loose date_range typing, while the description fully compensates by defining meaningful semantics for all five parameters. It enumerates valid insight_type values, clarifies which modes topic belongs to, gives explicit object syntax for date_range, and documents defaults for min_frequency and top_n.

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 names a specific unified tool for data insight analysis and clearly enumerates three distinct insight modes. Each mode is associated with a concrete purpose, which differentiates this tool from sibling news-fetching, crawling, and system-status tools.

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 provides clear mode-by-mode context with examples showing which parameters apply to each insight type. It does not explicitly state when to avoid this tool in favor of a specific sibling, but the scope is obvious enough that an agent can select it appropriately.

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