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

Annotations already cover read-only, idempotent, closed-world safety, yet the description adds genuinely new operational semantics: the model is recomputed daily, frozen three working days before publication, then settled against the actual reading, and carries backtest accuracy against naive benchmarks. That freshness/versioning lifecycle is exactly what an agent needs to interpret staleness and trust, and nothing contradicts the annotations.

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?

Content is dense but front-loaded: what the model forecasts comes first, then output form, then the recompute/freeze/settle lifecycle, then the disclaimer. The opening 'Finwire Nowcast, the finwire.pl statistical model' is slightly redundant with the title, but no sentence is wasted.

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?

Because an output schema exists, return values need not be explained, and the description still covers uncertainty intervals, refresh timing and model-vs-consensus status. The only meaningful gap is the absence of routing guidance against the many sibling macro tools, which keeps it from a 5.

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%, with both the 'history' default of 6 (max 24) and the cpi/core/rpp enum fully documented in the schema, so the baseline is 3. The description names the three indicators implicitly through its enumeration of CPI, core and RPP but adds no defaulting or pagination semantics beyond 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 precisely enumerates the resource: model forecasts of CPI y/y, core y/y with point and 80% interval, plus RPP cut/hold/hike probabilities, and clarifies it is a model estimate rather than a consensus. That level of specificity makes the tool's content unmistakable. It stops short of explicitly contrasting itself with siblings like get_macro_indicator (actual readings) or get_macro_calendar, so it earns a 4 rather than a 5.

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 only implied: the forecast-vs-actual framing lets an agent infer this is for forward-looking inflation/RPP questions, but there is no explicit 'use this when...' or 'do not use this for actual historical readings, use X instead'. The closing 'not a consensus and not investment advice' is a caveat, not routing guidance.

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