time_series_analysis

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 does not disclose whether the tool is read-only, what data freshness assumptions exist, or if side effects occur. The output format is not mentioned, leaving the agent uncertain about what to expect.

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 sentence, which is efficient and front-loaded with the core purpose. However, it is too concise at the expense of necessary detail, bordering on under-specification.

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 no output schema and 6 parameters, the description fails to explain return values, default behaviors (e.g., start_date not required), or what happens if dates are omitted. The tool lacks sufficient context for an agent to invoke it correctly without additional knowledge.

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 only 33%, and the description adds no additional meaning beyond the schema's parameter names. For example, 'metric' and 'geography' lack elaboration, and the description does not clarify valid metric values or date range implications.

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 'Analyze trends over time for specific health metrics,' which clearly indicates the tool's purpose of time series analysis on health metrics. However, it lacks specificity about the type of analysis (e.g., modeling, forecasting) and does not differentiate from sibling tools like compare_states or filter_data.

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 usage guidelines are provided. The description does not specify when to use this tool versus alternatives like compare_states or search_health_data. There is no guidance on prerequisites, data context, or limitations.

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