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

Annotations already establish the safe-read/closed-world profile, and the description adds real context beyond them: the estimate is a median of live asking prices, the askingPrice input triggers percentile positioning (below cheapest 10%, around median, above dearest 10%), and it is explicitly not a valuation. This tells the agent how much to trust the number, though nothing is said about data freshness or coverage limits.

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?

Front-loaded with the core explanation, followed by the optional askingPrice behaviour and the use-case phrases — a logical order with no filler sentences. The opening sentence is long and densely packed, which costs some readability, but every element earns its place.

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 values, so what remains is covered: calculation method, geographic scope, the askingPrice extension, and the not-an-appraisal caveat. An agent has everything required to call this correctly and interpret the result.

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 the baseline is 3, but the description goes further by explaining what location scoping means (oblast capital or its квартали), that area is multiplied against the per-m² figure, and what askingPrice actually does behaviourally. That is meaningful interpretation layered on top of the schema rather than repetition.

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?

Names a specific operation and resource — a sale/rent asking-price estimate for a Bulgarian property — and spells out the method (median asking price per m² of live listings × area). It is clear what the tool produces, but it never distinguishes itself from the sibling realistimo_market_stats, which is implied by the phrase 'the figures of its price statistics pages' yet not named.

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 concrete trigger phrases in Bulgarian ('колко струва апартаментът ми', 'колко наем да искам', 'скъпа ли е тази обява') and an explicit exclusion, 'Not an appraisal.' It does not, however, route the agent toward or away from the sibling tools (market_stats, market_index, deal_cost), so the boundary with alternatives is left implicit.

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