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

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so the safety profile is covered. The description adds genuinely non-obvious context beyond that: no API key required, the shape of each returned record (label, unit, kind as duration flow vs instant snapshot, ordered source tags), and the important semantic that a missing concept means the company reports none of its source tags rather than an estimate. That last point meaningfully prevents misinterpretation.

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 sentences, front-loaded with the count and identity of the concepts, then the call-site guidance, then the caveat. The parenthetical concept list is long but functions as concrete disambiguation rather than filler, and the trailing absence-semantics sentence earns its place by preventing a real misreading.

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 carries the burden of describing returns, and it does so field by field (label, unit, kind, ordered source XBRL tags). Combined with the no-parameter schema and full annotation coverage, an agent has everything needed to call it and interpret results.

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?

Zero parameters, so per the rubric the baseline is 4. The description correctly does not waste space on argument semantics and instead spends its budget on describing the returned records.

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?

A specific verb ("Lists") plus a precisely scoped resource ("the 22 standardized financial concepts this API builds from SEC XBRL") with a parenthetical enumeration of what those concepts are. It is unmistakably different from get_metric_history or get_financials, which retrieve data rather than reference definitions.

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?

States the exact downstream use case: "Use to discover valid `concept` values before calling get_metric_history," naming the sibling tool and the sequencing. It also implicitly excludes itself from data retrieval, so an agent knows this is a discovery step, not a data step.

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