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 declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful semantic context by clarifying that the result counts active listings and is an inventory count rather than a valuation.

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 short sentences, with the trigger front-loaded and no filler. Each sentence adds distinct value: one gives the usage condition, the other clarifies the result type.

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?

While annotations and output schema cover safety and return shape, the tool has 24 optional parameters with low schema coverage, and the description gives no guidance on how to choose or combine them. An agent would struggle to identify which filters to populate for a given user request.

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?

With 24 parameters and only 4% schema description coverage, the description carries the burden of explaining parameter roles, but it provides no parameter-level guidance beyond the generic phrase 'explicit filters'. This leaves nearly all parameter semantics undocumented and uncompensated.

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 identifies a count of active listings with explicit filters, using a specific verb and resource. It distinguishes the tool from a market valuation, but it does not explicitly name or contrast sibling tools, 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 opening phrase 'Use this when the user asks how many active listings match explicit filters' provides a clear trigger condition. It also offers an exclusion ('not a market valuation'), though it does not mention alternative tools by name.

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?

Annotations already declare read-only/idempotent behaviorpin, and the description adds valuable operational traits: pagination must use the returned nextCursor with unchanged filters, and ambiguous locations must be resolved first. This goes beyond the structured safety hints and describes how to interact correctly.

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?

Three sentences, front-loaded with the primary use case, followed by compact, actionable guidance on location resolution and pagination. 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?

The description covers main usage triggers and pagination, but omits parameter semantics, filter combination logic, and guidance on choosing among location filter types. The output schema exists, yet the operational context for a complex search tool is only partially provided.

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 only 4%, leaving 26 parameters undocumented. The description references broad categories ('location, budget, rooms or amenities') but does not explain the meaning or interaction of specific filters such as bbox, radius, polygon, or how filters combine. This is insufficient for a 27-parameter tool.

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 identifies the tool as a search for public properties with specific filter dimensions (location, budget, rooms, amenities). It distinguishes itself from siblings like get_property_by_slug (single property) and compare_properties by being the general listing search.

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 states when to use the tool ('Use this when the user wants public properties by location, budget, rooms or amenities') and gives operational guidance (resolve ambiguous locations, use explicit filters, maintain cursor). However, it does not name alternatives or provide when-not-to-use exclusions, so it misses the highest bar.

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