analyze_time_series

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

No annotations are provided, so the description carries the full burden. It states the tool calculates trends and growth rates but does not disclose whether it is read-only, what happens on invalid input, rate limits, or other behavioral traits. This lack of transparency is a significant gap for a computation 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 concise (three sentences) and front-loaded: first sentence states purpose, second lists outputs, third provides critical usage note. Every sentence adds value, with no redundancy or fluff.

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 the tool's complexity (7 parameters, no output schema), the description provides essential prerequisite guidance but lacks details on return format, data interpretation, or constraints. It is minimally viable but leaves gaps for an agent to understand expected outputs fully.

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 100% coverage for parameter descriptions. The description adds value by explicitly linking objL1 and itemId to get_table_info for validation, providing additional semantic context beyond the schema. This justifies a score above the baseline of 3.

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 specifies that the tool analyzes time series trends and calculates growth rates. It provides a specific verb ('analyze') and resource ('time series of statistical data'). However, it does not explicitly differentiate from sibling tools like quick_trend, which may perform similar functions.

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 includes an important prerequisite: to first use get_table_info to validate objL1, objL2, and itemId. This provides clear context and a precondition. However, no guidance is given on when to choose this tool over alternatives like compare_statistics or quick_stats.

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