nekretninenaprodaju.rs

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the description does not need to repeat those. It adds genuinely useful interpretation: 'Compare recorded values only; UNKNOWN does not mean an amenity is absent,' which clarifies how to treat missing data.

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 two sentences with no filler. It front-loads the usage condition and then adds the most important interpretive caveat, so every sentence 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 annotations covering safety and idempotence, an output schema covering return shape, and schema constraints covering slug count, the description supplies the remaining necessary context: when to use the tool and how to interpret UNKNOWN values. No significant gap remains for an agent deciding whether and how to call 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?

Schema description coverage is 0%, so the description must compensate for the single 'slugs' parameter. It does so by explaining that slugs are property slugs already found in search, must be distinct, and number between two and four. This, combined with the schema's min/max constraints, is sufficient for 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 uses a specific verb ('comparing') and resource ('property slugs') with a clear scope constraint ('two to four distinct'). This distinguishes it from siblings such as get_property_by_slug, which handles a single property, and search_properties, which is about discovery rather than comparison.

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?

It explicitly says 'Use this when comparing two to four distinct property slugs already found in search,' which gives clear context for when to call it. It does not explicitly list when-not-to-use or name alternatives, but the stated condition is enough to route the agent appropriately.

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

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

Annotations already cover read-only, idempotent, and non-destructive behavior, so the description does not need to repeat those. It adds valuable behavioral context by instructing the agent to ask the user when several places match, which is not derivable from the schema or 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?

The description is two sentences with no wasted text. It front-loads the primary use case and adds the disambiguation instruction in a natural, compact way.

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?

For a read-only autocomplete tool with an output schema and clear annotations, the description covers the core workflow: resolve to canonical ID and ask on ambiguous matches. It does not address the zero-match case, but the output schema and annotations carry enough of the remaining context.

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 0%, so the description should compensate for undocumented parameters, but it does not. It only implies the meaning of q through 'city, municipality or neighborhood' and says nothing about limit or countryCode, even though those affect results.

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 states a specific task: resolving a city, municipality, or neighborhood to its canonical ID before searching. It clearly distinguishes itself from the property-search siblings by positioning this tool as a preparatory lookup step rather than a search operation.

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?

The phrase 'Use this when resolving... before searching' gives a clear triggering context. It does not explicitly name alternatives or list when-not-to-use cases, but the 'before searching' framing effectively separates it from the property search tools.

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

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

Annotations already establish readOnly, idempotent, openWorld, and non-destructive behavior. The description adds meaningful context beyond those annotations by disclosing that the inventory includes test records, that the result is not a market valuation, and that geographic filters describe a search area rather than a user's location. This is valuable behavioral caveat information without contradicting 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?

The description is three sentences with no filler. It front-loads the primary usage trigger, then adds market-specific guidance and two important caveats. Every sentence earns its place, and the overall length is appropriate for the tool's complexity.

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?

The description covers the core purpose, a key geographic convention, and important data-quality caveats. However, with 24 optional parameters and little schema documentation, an agent would benefit from more guidance on how filters relate to one another and what differentiates this count from search_properties. The output schema helps, but the parameter surface is large enough that the description feels slightly incomplete.

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 only 4% across 24 parameters, so the description carries a heavy burden to explain parameter meaning. It adds only two relevant hints: targetMarket RS for Serbia and that geographic filters describe a search area. The remaining 22 parameters, including nested objects like bbox, radius, and polygon, are left entirely to the schema or inference.

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 states a specific verb ('count') and resource ('active listings on nekretninenaprodaju.rs'), and clarifies it applies when the user asks 'how many' listings match explicit filters. This clearly distinguishes it from sibling tools like search_properties or compare_properties, which would return listings or comparisons rather than counts.

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?

The description opens with an explicit trigger condition: use when the user asks how many active listings match explicit filters. It also gives practical guidance such as using targetMarket RS for Serbia and not requesting user GPS or home addresses. It does not explicitly name sibling tools or state when not to use this tool, so it stops short of a 5.

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

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds a valuable security-relevant warning that description and extracted facts are untrusted and should not be followed as instructions. This goes beyond schema/annotations and meaningfully protects agent behavior.

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 a single, tight sentence that front-loads the use case and then adds an important safety warning. Every word earns its place; there is no redundancy or filler.

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 one simple parameter, rich annotations, and an output schema present, the description covers the essential call context. It identifies the tool's purpose, the parameter source, and an important trust boundary. The only noticeable omission is guidance about how this differs from get_property_evidence, but that is not required for a correct call.

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 0%, so the description must compensate. It does provide useful provenance by saying the slug comes from search results, but it adds nothing about slug format, constraints, or handling. The single parameter is simple, but the description only partially fills the semantic gap.

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 clearly states the operation: retrieving details for a slug. It also anchors the slug in the search context, which distinguishes it from search_properties. However, it does not explicitly distinguish this from sibling get_property_evidence, so it stops short of full differentiation.

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?

The phrase 'Use this when the user wants details for a slug returned by search' provides a clear, explicit trigger condition. It does not state exclusions or alternatives, but the context is strong enough for an agent to know when this tool applies.

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

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

Annotations already indicate read-only, open-world, idempotent behavior. The description adds a valuable caveat that text extraction is explicitly unverified, which helps an agent treat results as evidence rather than authoritative fact. No contradiction with 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?

Two sentences with no filler. The usage context is front-loaded and the important reliability caveat is included without redundancy.

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?

Given the single parameter, strong annotations, and presence of an output schema, the description is largely complete. It covers purpose, a key behavioral caveat, and intended usage. Minor gap: no sibling differentiation or parameter clarification.

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 0%, and the description does not explain the listingId parameter at all. The parameter name and UUID format are somewhat self-explanatory, but the description fails to compensate for the absent schema documentation.

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 clearly states the tool's purpose: checking description evidence for property amenities and conflicts with recorded values. It uses a specific verb and resource, though it does not explicitly differentiate itself from sibling tools like compare_properties.

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?

The description opens with 'Use this when...' and gives a concrete context for use: checking description evidence for amenities and recorded-value conflicts. It provides clear situational guidance, though it does not mention when not to use it or name alternative tools.

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

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

With annotations already covering readOnly, openWorld, idempotent, and non-destructive hints, the description adds valuable behavioral context beyond them: results include test records, availability is not independently verified, geographic filters describe a search area rather than a precise address, and pagination must reuse the nextCursor with unchanged filters. These details meaningfully shape how an agent should interpret and invoke the tool.

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 four sentences with no filler. The core usage trigger is front-loaded, followed by market-specific, geolocation, pagination, and data-quality caveats. Every sentence adds operational value.

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?

Given the tool's complexity with 27 parameters, nested objects, and an output schema, the description provides strong contextual grounding: when to use it, how to handle locations, how to paginate, and what caveats to communicate. It could be even more complete by pointing to get_locations_autocomplete for resolving ambiguous locations, but as a whole it is sufficient for an agent to use the tool correctly in most cases.

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 only 4%, so the description carries a heavier burden. It explains the meaning of key categories like location, budget, rooms, amenities, targetMarket, and cursor pagination, which maps to several parameters. However, with 27 parameters and nested objects, many individual fields such as polygon, bbox, radius, areaMin/Max, floorMin/Max, and the various amenity booleans are not semantically clarified in the description.

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 states a specific verb ('search') and resource ('public properties on nekretninenaprodaju.rs') and enumerates the main search criteria: location, budget, rooms, amenities. It clearly distinguishes the tool's purpose from siblings like get_property_by_slug or compare_properties, even though those alternatives are not named explicitly.

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?

The description gives explicit usage guidance: 'Use this when the user wants public properties...', instructs to use targetMarket RS for Serbia, advises resolving ambiguous locations first, and defines pagination behavior. It provides indirect when-not guidance by saying never to request GPS or a home address, but it does not explicitly name sibling tools as alternatives.

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