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

With no annotations provided, the description carries the full burden. It discloses that results are keyword-matched sentences and may include both forward guidance and recent reported results, warning the user to read carefully. This is meaningful behavioral context beyond the schema, though it doesn't describe return format or potential limitations like date ranges.

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 concise and well-structured. The first sentence states the core purpose, the second provides usage context, and the note adds a critical caveat. Every sentence serves a clear function, with no redundant or filler text.

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 simple tool with one parameter and no output schema, the description is complete. It explains what the tool does, when to use it, what the output looks like (`keyword-matched sentences`), and a significant caveat about historical vs. forward-looking content. This is sufficient for an agent to select and invoke the tool correctly.

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 only one parameter, `ticker`, with 0% description coverage. The description compensates by stating `by ticker symbol` in the first sentence, making it clear the input is a stock ticker. Though it doesn't specify format (e.g., uppercase), the single parameter is self-explanatory and the mention adds value.

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 extracts forward-looking guidance language from SEC filings by ticker symbol. This is a specific verb+resource+scope that distinguishes it from sibling tools like get_filings or get_transcript, which focus on raw filings or transcripts.

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 guidance on when to use the tool (`Use this when asked what a company said about future performance, revenue outlook, margin expectations, or other forward-looking statements`). However, it does not explicitly name alternatives or state when not to use it, though the context is clear enough for most agent decisions.

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