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

Annotations already cover the safety profile (read-only, idempotent, non-destructive), and the description adds substantive behavioral context: it discloses what the modeling computes and the categorical outputs (breakpoint, resilience rating scale, sector context). It stops short of stating limits such as whether results are cached or how sensitive the model is.

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?

Front-loaded with the core action and well organized, but it enumerates several return fields that the output schema already carries, making it longer than strictly necessary.

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 two-parameter read-only analysis tool with a full output schema, the description covers the modeling intent, the answers it produces, and the scenario customization path. Nothing an agent needs to invoke it correctly is missing.

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 coverage is 100%, with ticker format and scenarios defaults already documented in the schema. The description restates the default and the custom-scenario use case but adds no syntax or format meaning beyond what the schema provides, so the 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 specific verb and resource ('Stress-test dividend safety under recession scenarios') and specifies the modeling activity (earnings decline 20/30/50%). It is clearly distinct from sibling tools like get_dividends or get_dividend_cut_probability by framing itself as scenario modeling, though it never names an alternative to route the agent explicitly.

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?

Gives clear situational context via the framing question 'Is the dividend safe in a recession?' and directs custom analysis through the scenarios param. It does not, however, state when to prefer this over siblings like get_dividend_cut_probability or get_financial_distress.

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