Company fundamentals

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety and side effects. The description adds valuable behavioral detail: the specific data fields returned (revenue, net income, EPS, etc.), the period types (10-K/10-Q), and the source (EDGAR XBRL). It also discloses the limitation 'No prices, estimates or valuations,' which extends transparency without contradicting the annotations.

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 three sentences with no filler. The first sentence immediately states the core purpose, the second enumerates the returned data, and the third states limitations. Every sentence earns its place, and the structure is front-loaded with the most important 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?

For a single-parameter tool with an output schema present, the description is complete. It lists the key financial figures returned, the filing types, and the limitation on other data types. An agent can decide when to use this tool and what to expect without needing any additional information.

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 provides no description for the sole parameter 'ticker' (0% coverage), so the description must compensate. It does so by giving concrete examples (AAPL, NVDA, TSLA) and the context 'US-listed SEC registrant,' which makes the expected input unambiguous. While it doesn't explicitly define 'ticker' as a stock symbol, the examples and pattern in the schema suffice for an agent to infer the meaning.

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 opens with a clear, specific statement: 'Latest reported financials and filings for a US-listed SEC registrant, from EDGAR XBRL.' This defines the verb (returns), resource (financials/filings), and scope (US-listed SEC registrant). The mention of 'No prices, estimates or valuations' further distinguishes it from market-data tools like search_markets or market_overview, so it is clearly differentiated from siblings.

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 clear context for when to use this tool: it returns fundamentals (10-K/10-Q data) and explicitly states what it does NOT return (prices, estimates, valuations). This implies that for price-related queries one should use another tool, but it does not explicitly name sibling alternatives, so the guidance is strong but not fully explicit.

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