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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so safety is covered. The description adds genuine behavioral context beyond them: results are point-in-time with no future revisions, and the stress probability uses a 2-state Markov-switching model, which tells the agent how to interpret the numbers.

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?

Lead sentence front-loads the resource and the point-in-time cutoff, then the parenthetical enumerations spell out the label set. The lists are dense but each item is a distinct returned field, so they earn their place; the methodology parenthetical is only marginally necessary.

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 return-value burden itself and does so by enumerating every label group plus the nowcast and stress probability. Combined with the point-in-time caveat and single optional parameter, an agent has everything needed to call and interpret it.

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?

Single parameter with 100% schema coverage, which the schema already documents fully (format, default, look-ahead rationale). The description still reinforces the semantics by framing the whole output as 'as known on as_of' and stressing no future revisions, adding interpretive value rather than repeating 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?

States a specific verb and resource ('The FinzData Quantitative Model as known on as_of') and then enumerates exactly which readings are returned: regime labels, quadrant, nowcast, and stress probability. No sibling tool covers macro regime labels, so the agent can route here without ambiguity.

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?

Gives three concrete example questions it answers ('what macro regime are we in', 'are financial conditions tightening', 'condition a backtest on regime'), which is strong situational guidance. It stops short of naming alternatives — get_macro_vintage and get_fundamentals_pit exist and are not explicitly contrasted, so the boundary between this and vintage macro data is left implicit.

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