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

Annotations already establish readOnly/idempotent/non-destructive/closed-world, so the description's job is to add method and caveats — and it does: Eurostat methodology, IMGW-PIB station source, the 20-season norm baseline, cold index scaled at 100, and the important caveat that the season forecast with an 80% interval is emitted only when the backtest gate passes, otherwise the reason is returned. That conditional-output behavior is genuinely useful context not present in annotations. It does not discuss latency, coverage limits, or caching.

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?

All content sits in one long run-on sentence that front-loads two Polish-language metric names before saying what the tool actually returns. The information density is high and little is wasted, but the structure is hard to scan and the bilingual naming (Indeks chłodu sezonu finwire…) delays comprehension.

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 an output schema present, the description need not explain return shapes, and it adequately covers data content, methodology, baselines, and the forecast-gating caveat. The only substantive gap is the absence of routing guidance relative to the many energy/housing/cost siblings.

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 description coverage is 100% and the single city parameter is exhaustively documented in the schema (slug list, aliases, omit-for-all-Poland behavior). The description adds no parameter-level meaning beyond what the schema states, so the baseline 3 applies.

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 resource precisely (heating season in Poland) and enumerates its contents: heating degree days since 1 July, cold index, season cost, monthly means vs norm, coldest/warmest seasons since 1966/67. It also ties itself to the sibling index family (finwire_heating_season_index, finwire_heating_season_cost), so an agent can tell what data it returns. It stops short of explicitly differentiating itself from adjacent tools like get_energy_prices or get_housing_costs.

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?

There is no when-to-use guidance, no mention of when to prefer this over get_energy_prices / get_housing_costs / get_finwire_index, and no stated prerequisites. Usage is only implied by the data inventory. The description also says nothing about the optional city argument's effect on the result shape, leaving routing entirely to the schema.

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