SEC-derived annual fundamentals (revenue, net income, assets, margins; plus price-based valuation when available) for a US public company, by ticker symbol. Data traces to SEC EDGAR filings.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | US ticker symbol, e.g. AAPL |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries burden. Discloses data source and type (annual, from SEC). Does not discuss edge cases (invalid ticker), rate limits, or destructive potential (none), but adequate for a read-only retrieval tool.
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?
Two concise sentences, front-loaded with core purpose and data source. No wasted words.
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 one parameter and no output schema, description provides essential context (data source, content, scope). Could mention that data is annual only, but overall complete for a simple retrieval tool.
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 covers 100% of the single parameter ('ticker'). Description adds context ('US public company', 'by ticker symbol') clarifying usage, exceeding mere repetition.
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?
Clearly states it retrieves SEC-derived annual fundamentals (revenue, net income, etc.) for a US public company by ticker. Differentiates from sibling screen_companies.
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?
Implies use case (fundamental data for specific company) and data source (SEC EDGAR), but lacks explicit when-not-to-use or alternative guidance beyond sibling name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.