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

With annotations covering safety (readOnly, openWorld, non-destructive), the description layers on substantial behavioral context: concepts may come from different filings, a period link does not verify every value, each metric has its own verified start/end dates, and durations may remain unknown. It also discloses that annual/interim periods are separate and standalone quarters are not inferred, which materially shapes how an agent should interpret 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?

The most important scope statement is front-loaded in sentence one, and each subsequent sentence carries genuine semantic content. It is dense and longer than typical, but nearly every clause earns its place; the period-duration passages are slightly repetitive.

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?

No output schema exists, so the description must explain return semantics, and it does: period dates, per-row filing links, per-metric date ranges, and unknown durations. For a single-parameter read tool this covers everything an agent needs to call and interpret it correctly.

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) with 0% schema description coverage, so the schema carries the pattern but no semantics. The description implies the ticker must be a US company identifier, which adds some meaning, but never addresses ticker format, exchange suffixes, or case expectations beyond what the pattern enforces.

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 first sentence names a specific verb-resource pairing ('Reads stored SEC Company Facts') and enumerates the exact data domains covered (revenue, earnings, assets, debt, cash flows, historical statements). The closing exclusions (no prices, valuation ratios, analyst forecasts, buy verdict) further sharpen its identity against price/forecast-oriented siblings like get_financial_quality or get_company_earnings.

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?

'Use this for a US company revenue...' gives clear positive trigger conditions, and the final sentence supplies explicit negative scope (no prices, valuation ratios, forecasts, verdicts). It stops short of naming a specific alternative sibling to use instead, so it is strong but not a full routing directive.

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