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

With no annotations provided, the description carries the full behavioral disclosure burden. It discloses the output nature (derived metric rows, ratio examples, period options, default last 4 periods) and the 'trend' aspect, giving the agent a solid understanding of what to expect. It does not add details like pagination or edge cases, but for a simple read-only tool the description is sufficiently transparent.

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 two sentences, front-loaded with the core purpose and followed by usage guidance. Every word earns its place; there is no redundancy or filler. It efficiently communicates the tool's purpose, output examples, defaults, and when to invoke it.

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?

For a three-parameter, read-only tool with no output schema, the description adequately covers the main aspects: what data is returned, the alternative period frequencies, default window, and the intended use case. It does not explain the exact return shape or pathioning, but that is not necessary given the absence of an output schema and the simplicity of the tool. It is slightly less complete than ideal because it does not explicitly explain how 'limit' influences results, but it is sufficient for correct invocation.

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 schema has zero description coverage, so the description compensates by explaining period values ('quarterly, annual, or TTM') and the default limit ('last 4 periods'). The ticker parameter is self-evident from the tool name and description. A slight gap is that 'limit' is only implied as a default count rather than explained as a configurable maximum, but the description goes beyond the schema's bare types/enums.

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 identifies the tool as returning derived financial-metric rows (P/E, ROE, margins, FCF yield, debt ratios) per period for a ticker. It distinguishes this from raw statement tools by explicitly mentioning derived ratios and contrasting with 'raw statement line-items.' The verbs and scope are specific, and the mention of 'trend' implies a time series, which differentiates it from snapshot 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?

It provides an explicit call condition: 'Call this when the user asks about valuation or quality ratios and their trend without needing raw statement line-items.' This gives clear context for when to use, but it does not name specific alternative tools or state explicit 'when not to use' scenarios beyond the raw statement contrast. Sibling tools like fundamentals_income_statements are implied but not named.

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