compare_financials

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

No annotations are present, so the description carries the behavioral disclosure burden. It adds useful context about non-December fiscal year ends being handled automatically and about returning actual reported values, but it does not mention read-only status, error behavior, or data limitations.

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 purpose is front-loaded, and the Args/metric list is well-organized. The metric list is long but earns its place because XBRL concept names are not obvious and the schema provides no descriptions.

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 0% schema coverage and no annotations, the description is nearly complete: all four parameters are explained and the metric dictionary removes guesswork. It does not specify units/currency or invalid-ticker behavior, but the output schema covers return structure.

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 explains tickers format, maps XBRL concept names to human-readable metrics, clarifies year default behavior, and defines quarter semantics. This goes well 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?

States a specific verb ('Compare'), a specific resource ('a financial metric across multiple companies'), and a data source ('SEC XBRL data'). It also clarifies that it returns actual reported values, which helps distinguish it from normalized or adjusted comparison tools.

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 clearly implies the use case: cross-company metric comparison from SEC filings. However, it never explicitly states when to prefer this over siblings like compare_stocks, compare_sectors, or compare_industries, nor does it mention exclusions or alternatives.

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