time_analysis

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It names trend, growth/decline, and moving average as outputs, but does not explain return shape, side effects, prerequisites, or how missing data or invalid columns are handled. This is thin for a tool operating on table data.

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 concise phrase that front-loads the core purpose and mentions the main analytical outputs. However, it is too sparse to be fully useful, so it earns high marks for brevity but not the top score due to missing elaboration.

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?

Although an output schema exists, the description is incomplete for an analysis tool with five parameters and no schema-level descriptions. It does not explain required columns, how period granularity works, how the moving-average window is applied, or how this tool relates to similar siblings like predict_trend.

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 for undocumented parameters. It mentions moving average, which maps to moving_avg_window, but gives no explanation of date_column, value_column, period, or table_name semantics beyond what their titles already state. Most parameter meaning is left to inference.

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 states 'Time series analysis: trend, growth/decline, moving average,' which names the resource and the kind of computations performed. While it does not explicitly differentiate from siblings like detect_anomalies or predict_trend, the mention of specific analytical outputs makes the purpose reasonably distinct.

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 given about when to use this tool versus alternatives such as detect_anomalies, predict_trend, or smart_summary. The intended context is only implied by the phrase 'time series analysis,' leaving the agent to infer when this tool is preferred.

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