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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the data source (SEC EDGAR), quarterly frequency, and a $0.02 USDC cost, but does not explain return format, filtering behavior, date inclusiveness, or any side effects. This is a sparse disclosure for a tool that could involve external API calls and cost.

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 a single, well-structured sentence that front-loads the core purpose, gives concrete examples, and includes a relevant cost detail. Every part earns its place, and there is no verbose or redundant 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?

The description is adequate for a simple data-retrieval tool, but it lacks several contextual details that would help an agent invoke it correctly: what the response shape is, whether all metrics are returned by default, and how date filtering interacts with quarterly data. Given the absence of an output schema and annotations, the description leaves meaningful gaps.

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 description coverage is 100%, providing baseline clarity for all four parameters. The description adds value by naming example metrics (revenue, EPS, margins) that clarify what 'fundamentals' means and thus what the 'metrics' filter likely accepts, but it does not elaborate on date parameters or whether to_date/from_date are optional.

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 identifies the tool as providing quarterly fundamentals from SEC EDGAR, with examples (revenue, EPS, margins) that make the resource specific. It distinguishes from siblings like get_stats or get_company by naming the data source and frequency, though it lacks an explicit action verb like 'get' or 'retrieve'.

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 gives no guidance on when to use this tool versus alternatives such as get_stats, get_company, or get_filings. There is no mention of preferred use cases, exclusions, or when another sibling would be more appropriate. The only contextual hint is that it is specifically for SEC EDGAR fundamentals.

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