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

With no annotations provided, the description carries full burden for behavioral disclosure. It explains that the tool returns a 'single TTM row'—indicating a bounded, read-only result—and describes the content as 'valuation and quality ratios,' giving the agent a clear expectation of what to deliver. However, it omits potential edge cases like missing data or symbol validation, but these are not critical for such a simple read operation.

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 concise sentences. The first sentence defines the tool's output clearly and the second provides usage and alternative. Every sentence earns its place with no fluff or repetition. Highly front-loaded with the essential 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?

Given the tool's simplicity—one parameter, no output schema, no annotations—the description is remarkably complete. It states the exact output structure ('a single TTM row'), the content type ('valuation and quality ratios'), and gives concrete examples ('P/E, profitability'), while also covering when to use it vs. the alternative. An agent can confidently select and invoke this tool based on this description alone.

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 one parameter 'ticker' with 0% description coverage, so the description must compensate. It does mention 'for a ticker' in the first sentence, which minimally clarifies the parameter's role, but it does not add format details (e.g., uppercase, exchange suffix) or constraints. For a single self-explanatory parameter, this is adequate but does not go beyond what the schema suggests.

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's purpose with a specific verb and resource: 'Latest financial-metrics snapshot for a ticker — a single TTM row of valuation and quality ratios.' It explicitly differentiates itself from the sibling tool 'fundamentals_metrics' by contrasting snapshot vs. per-period history, making it distinguishable.

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 provides explicit when-to-use guidance: 'Call this for a quick "what's the P/E, how profitable is X right now?" check.' It also names the alternative tool to use for different needs: 'use fundamentals_metrics when the user needs the per-period history.' This fully meets the usage guideline criteria.

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