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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so safety is covered. The description adds genuinely new behavior: sector-conditional panels, that specialized panels carry SEC tags, source periods, methodology and coverage limits, and that missing source values are returned as null rather than omitted — an important expectation for downstream handling.

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?

Three front-loaded sentences: core output first, then sector-specific extensions, then data-quality caveats. No filler or restatement 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 must carry return-value context, and it does: it enumerates ratio families, the bank/utility add-on panels, per-panel metadata, and null semantics. It stops short of describing units, how many periods are returned, or the response structure, but the coverage is solid for the tool's complexity.

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 only 33%: only `period` is documented, and its TTM/averaging caveat lives in the schema, not the description. The description never explains `limit` (max 15, default 5) or clarifies that `ticker` must be a US-listed symbol, so it does not compensate for the coverage gap on two of three parameters.

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 — computing margins, liquidity, leverage, return, and working-capital ratios — and bounds the scope to a US-listed company. It further specifies conditional outputs for SIC-classified banks and regulated utilities, which distinguishes it from generic data-retrieval siblings such as get_financials.

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: an agent can infer this is the ratio-derivation tool for a single US-listed company, and that sector-specific panels appear automatically. There is no explicit when-to-use/when-not, and no routing to alternatives like get_financials, get_valuation, or peer_compare.

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