analyze_data_insights

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

No annotations are provided, so the description must disclose behavioral traits. It does not explicitly state that this is a read-only, non-mutating analysis operation, nor does it mention any side effects, rate limits, or dependencies on underlying data. The description focuses on parameters and return format, leaving the safety and side-effect profile largely undisclosed.

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 well-organized with 'Args', 'Returns', and 'Examples' sections, making it easy to scan. Each parameter entry is informative and relevant, and the examples illustrate real usage. No filler; the length is justified by the tool's multi-modal nature.

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 covers all five parameters, their meanings, and provides examples for all three insight types, which is strong for a multi-mode tool. However, it leaves some ambiguities, such as whether date_range is required for platform_activity, and doesn't mention any prerequisites or data dependencies. Overall, it is sufficiently complete given the output schema exists.

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 input schema has zero descriptions; the description fully compensates by documenting every parameter, its possible values (insight_type enum), applicable modes, defaults, and the required object format for date_range. It even provides an explicit warning that date_range must not be an integer, adding critical semantic detail beyond the schema.

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 it is a unified data insight analysis tool integrating multiple analysis modes and enumerates three specific modes (platform_compare, platform_activity, keyword_cooccur), each with a brief explanation. This distinguishes it from sibling tools like analyze_topic_trend or analyze_sentiment by covering these specific comparative/co-occurrence analyses.

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 examples and clarifies which parameters apply to which insight mode (e.g., 'topic' for platform_compare; 'min_frequency' and 'top_n' for keyword_cooccur), giving implicit usage context. However, it does not explicitly state when to choose this tool over siblings such as analyze_topic_trend or analyze_sentiment, nor does it provide any exclusion criteria.

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