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

Annotations already cover the read-only, non-destructive, open-world safety profile, so the bar is lower. The description adds genuine behavioral context beyond them: the data derives from the latest 10-K XBRL and values are null where inputs are missing, warning the agent about annual staleness and sparse results.

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 tight sentences: the payload (what is computed and from where) is front-loaded, and the caveat about nulls is a compact trailing clause. No filler or repetition of the tool name.

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?

With no output schema, the description compensates by enumerating the exact metrics returned and disclosing null behavior for missing inputs. For a single-parameter read tool this gives the agent everything needed to call it and interpret the result.

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?

There is one parameter (ticker) with 100% schema description coverage and an example (AAPL), so the schema fully carries the semantics. The description adds nothing further about the parameter; baseline 3 applies.

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?

States a precise resource (financial ratios) plus the exact ratios returned (gross/operating/net margins, ROE, ROA, debt-to-equity, FCF) and the data source (latest 10-K XBRL). This enumeration clearly separates it from sibling tools like get_financial_statement or get_annual_growth, which return raw statements or growth series rather than computed ratios.

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?

Usage is only implied: pass a ticker to get ratios for that company. The description never says when to prefer this over get_financial_statement, nor flags that 'latest 10-K' means annual-only data (no quarterly), which is an implicit exclusion left for the agent to infer.

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