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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so "Reads stored data only; no external search or mutation" largely restates structured data. What it adds beyond annotations is the return shape hint ("ranked rows, coverage and inline SEC filing source URLs"), which is useful but partly redundant with the existing output schema.

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?

Purpose is front-loaded in the first sentence and the rest is a compact parameter glossary with almost no filler; given 18 undocumented parameters, nearly every fragment earns its place. The telegraphed, line-fragmented style is dense but readable, though a few entries (e.g. "compare_years: growth lookback") are terse to the point of ambiguity.

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 an 18-parameter screener with zero schema descriptions and no required parameters, the definition covers the tricky decisions an agent must make (period semantics, screening mode units, universe selection, ranking size). An output schema exists, so return-value detail is not required; only period_type and the exact accepted string forms for companies/industry are left thin.

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?

With 18 parameters and 0% schema description coverage, the description carries the full burden and does substantial work: enumerated metric and axis values, units for growth (percentages) versus value (USD) bounds, case-insensitivity for member_filter, top_n range 1–100, and the fiscal-versus-calendar clarification with a worked example (NVIDIA Q2 FY2027 ended 2026-07-26 → year=2026, quarter=3). Gaps remain: period_type is only implied, compare_years is a bare three-word gloss, and the accepted formats for companies/industry strings are not pinned down.

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?

"Rank stored US company segment rows by metric value or year-on-year growth" gives a specific verb (rank), resource (segment rows), and scope (US, stored data). The resource distinguishes it from screen_companies at a high level, but the description never explicitly names or contrasts the sibling screening tools, so the differentiation is left implicit.

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?

It supplies operational defaults ("Omitted: the newest period in scope", screen_mode value vs growth, period selection rules) which imply how to invoke it, but gives no explicit when-to-use-this-vs-alternative guidance against screen_companies, screen_companies_multi, or get_segment_financials. Nothing states a case where this tool is the wrong choice.

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