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

Annotations only mark it read-only, but the description adds substantial behavioral detail: the exact return shape ({ticker, flags, count}), flag structure, that severity is only 'red' or 'amber' and sorted red-first, that 'absence is not an all-clear', and that caveats arrive in tool_notes. This is far beyond what the annotation provides.

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, then progressively discloses screens, return shape, and interpretive caveats. The parenthetical list of screens is long but earns its place by telling the agent what signals matter; overall dense but not wasteful.

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?

There is no output schema, yet the description fully describes the return contract and interpretation semantics, which is exactly what an agent needs here. Nothing critical is missing for correct invocation and result handling.

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?

Only one parameter (ticker) and schema description coverage is 100%, so the schema already documents it fully with an example. The description adds nothing about the ticker beyond what the schema states, making the baseline 3 appropriate.

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 ('Run 15 red-flag screens on a ticker') and enumerates the actual screens, so the agent knows precisely what this computes. It also names the sibling tools it pairs with (get_fundamentals, ol_intrinsic_value), distinguishing it from generic data fetchers.

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?

Says to pair it with get_fundamentals and ol_intrinsic_value and explains how to read an empty result ('absence is not an all-clear') and warns it is not a sell signal. There is clear context, but no explicit when-not-to-use or which alternative to pick if the agent only wants raw fundamentals.

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