get_analytics

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

With no annotations provided, the description carries full burden and excels: it details side effects (read-only, stateless), authentication, rate limits (10/day free, unlimited pro), error handling (structured errors), idempotency, and data privacy. This is exemplary transparency.

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-structured with clear sections but is verbose and contains redundancy (e.g., 'Behavior' and 'Behavioral Transparency' overlap). It could be more concise without losing 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?

The description covers behavioral aspects thoroughly but lacks detailed parameter guidance and doesn't fully clarify the analytics scope (e.g., what frameworks or standards?). With an output schema present, return values are assumed covered, but overall completeness is moderate.

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 0% description coverage, and the description's 'Args' section provides only minimal one-liners (e.g., 'The month to analyze or process'). No format, examples, or constraints are given, failing to compensate for the schema gap.

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 the tool 'Get spending analytics' and explains it provides structured analysis/classification. However, it does not explicitly distinguish it from similar sibling tools like get_category_spending, leaving some ambiguity.

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 explicit 'When to use' and 'When NOT to use' sections, providing clear context for appropriate invocation. It correctly notes it is not for real-time production decisions, but lacks comparison to alternative sibling tools.

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