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

With no annotations, the description carries the behavioral disclosure burden and does it well: it states the data source (SEC XBRL), the single-quarter caliber (cumulative values excluded), cross-company comparability, Chinese AI interpretation, and the 0.01 USDC price via x402. It does not detail possible payment side effects or failure modes, but the core behavior and cost are 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 front-loaded with 'Finance Signal Bundle - get live computed signal' and every clause adds selection-relevant detail. It is dense and long due to the ticker list and bilingual content, but contains no filler.

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 single-optional-parameter tool, the description provides enough scope, data source, metrics, language, and cost information to select it confidently. The main gap is no explicit output format or differentiation from overlapping siblings such as processed_us_stock_tech and signal_us_mega_cap.

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 coverage is 100%, and the sole optional wallet parameter is already documented in the schema; the description adds no parameter-specific meaning. The pricing rail is useful context but does not explain how the wallet parameter behaves.

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 uses a specific verb (get) and resource ('live computed signal') and enumerates exactly 15 tickers plus the metrics returned (revenue, net profit, net margin, annualized ROE, debt ratio). It is clear, but it never names a sibling or explicitly distinguishes itself from processed_stock_quote or signal_us_mega_cap.

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 use case (latest single-quarter fundamentals for these large US companies) is implied by the ticker and metric list, and the data-source/caliber notes reinforce it. However, there is no explicit when-to-use/when-not-to-use guidance or comparison to any of the many sibling signals.

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