spending_by_category

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

No annotations are provided, so the description carries full burden. It discloses the output format behavior (text table vs dict, TSV table with Total/Avg columns when group_by is set) and the override relationship (group_by overrides verbose). It could add more about edge cases (empty periods, date validation) but the core behavioral traits are disclosed.

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 an overview sentence followed by a compact Args block. It front-loads the purpose and output format before parameter details. Slightly verbose with the full sentence explanations per arg, but each earns its place by adding meaning beyond the schema. Could be tightened but is efficient overall.

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?

With an output schema present and 5 parameters, the description handles the core behaviors well: output format switching, group_by multi-period behavior, and hierarchy depth. Minor gaps: no mention of what happens with overlapping dates or default period behavior, but for a read-only reporting tool the coverage is strong.

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 fully compensates. It documents all 5 parameters: start_date and end_date with format (YYYY-MM-DD), depth with hierarchy levels (1=top-level, 2=subcategories), verbose with programmatic consumer rationale, and group_by with valid values and behavioral effect (multi-period TSV, overrides verbose). Every parameter receives meaningful semantics beyond the bare 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 the verb ('Get spending breakdown'), the resource ('by expense category'), and the scope ('for a period'). It distinguishes itself from siblings like income_by_source (income vs spending) and vendor_spending_report (category vs vendor breakdown). The purpose is specific and immediately understandable.

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 explains the two output modes: default compact text table vs verbose structured dict for programmatic consumers/plotting, and the group_by override for multi-period analysis. This gives clear guidance on when to use verbose mode. However, it doesn't explicitly name alternatives or state when NOT to use this tool vs report siblings, though sibling differentiation is fairly obvious.

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