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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, closed-world, so safety needs no restating. The description adds real behavioral context beyond that: it explains that missing lines are explained per market, that coverage shares are quantified, and that global rules (dating, signs, annual-only cash-flow lines, small employers) are included. It does not indicate response size or that the call is unfiltered and therefore returns everything.

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 opening sentence is well front-loaded and states the resource and its four components efficiently. However, the final two-thirds is a long comma-separated inventory of ~26 line-item codes plus 4 calculated codes, which is dense, hard to scan, and largely discoverable from the tool's own output; it dilutes the structure of an otherwise tight definition.

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 carries the burden of describing returns, and it does so thoroughly: contents, per-market sourcing, coverage measurement, formulas, and shared rules. What is missing is any sense of scope or size (all markets, all metrics in one payload) that would help an agent plan around the response.

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?

The tool takes zero parameters, which is the baseline-4 case, and the empty schema leaves nothing to interpret. The trailing code inventory usefully enumerates the identifiers the dictionary defines, which pre-answers the agent's question of whether a code exists, though it is not a parameter in the schema.

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 description names the exact resource (the data dictionary of detailed line items) and enumerates its contents: per-metric definitions, the source filed line per market, the measured share of company-periods carrying it, calculated figures with formulas, and cross-cutting rules. It also states that company.industry and company.status are defined here, so an agent can distinguish this metadata tool from get_latest_fundamentals or get_fundamentals_history without opening a schema.

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 stated concretely: 'Use it before comparing a line item across markets, or to learn what a line-item code means.' That gives a clear triggering condition. It stops short of naming alternatives (e.g., get_coverage) or saying when not to call it, so it falls short of a 5.

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