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

Annotations already declare readOnly, idempotent, and non-destructive behavior, and the description adds substantial context beyond that: plan truncation with _warnings, 403 PLAN_TIER_INSUFFICIENT_COVERAGE, US-only jurisdiction with 400 METRICS_UNSUPPORTED_FOR_<jurisdiction> and no credits charged, 10 credits, endpoint, and plan requirements. No contradiction exists.

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 description is front-loaded with purpose and return value, then requirements, then usage, then error/plan context. It is dense but every section earns its place; minor noise includes the formula_override note and endpoint/documentation reference, which are useful but slightly tangential.

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 does explain the core return concept (metric_group_id entries and filing metadata) and directs users to check _warnings for truncation. It covers key errors, credits, and plan limitations. It stops short of describing the full response shape, but for a discovery tool feeding into named siblings, this is reasonably complete.

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 coverage is 100%, so baseline is 3, but the description adds meaningful semantics not visible in the schema: the mandatory 'at least one of fiscal_year or as_of_date' rule, accepted form_types values (10-K / 10-Q / 20-F / 40-F), and the meaning of quarter for disambiguation. This materially helps correct invocation.

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 opens with a specific verb and resource: 'Discover computed metric snapshots for a ticker' and immediately states what is returned (metric_group_id entries and filing metadata). It also names the downstream consumers (get_metrics_bundle, get_metrics_subset), clearly distinguishing this discovery tool from the metric-fetching siblings.

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?

Explicit when-to-use guidance is provided: 'Use this when the user wants metrics but you only know ticker/year or as-of date.' It also names the alternatives (get_metrics_bundle or get_metrics_subset) and states required inputs and the at-least-one-of constraint, so an agent can route correctly.

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