Irish rent benchmarks and house price comps

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

With no annotations, the description carries the full burden and does reasonably well: it discloses the free tier, an explicit rate limit (20 calls/day per client), the upstream data source, the fact that legal rules are summarized as 'information, not legal advice', and the aggregate granularity of the result. It omits any authentication or failure/empty-result behavior, which keeps it short of 5.

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?

It is a compact block of roughly 60 words that front-loads the user-facing question and then immediately gives scope, source, limits, and disclaimer. No sentence is filler, and the practical constraints (free, rate-limited) appear before the caveat.

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 no output schema and one simple parameter, the description does the work of describing what comes back (average asking rent plus a rent-control rules summary), the data vintage, and the cost/limits. It is close to complete; only result-shaping details such as units or update lag are unstated.

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?

There is a single parameter with 100% schema description coverage, so the schema already carries the syntax and the 'Dublin 4' / 'Ardee' examples. Baseline 3 is appropriate; the description adds only the scope note that results are county-level aggregates regardless of how specific the area input is.

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 a specific verb+resource: it returns the latest average asking rent for an Irish county plus a summary of Irish rent-control rules, and it names the data source (CSO/RTB RIQ02). It hints at paid siblings via the 'Free:' framing but never names them, so sibling differentiation is implicit rather than explicit.

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 context is implied rather than stated: 'Free:' and the '(all bedrooms, all property types)' scope suggest this is the low-cost county-aggregate option and that bedroom-specific queries belong elsewhere. No sibling tool is named and no explicit when-not condition is given, so the agent must infer the routing.

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 no annotations, the description carries the full behavioral burden. It usefully discloses that the call is 'Free' — meaningful context given siblings named paid_comps and paid_rent_check — and that it enumerates all queryable areas. However, it says nothing about read-only nature, auth requirements, or rate limits, which is a real gap for a zero-annotation 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?

Three short sentences, front-loaded with the purpose question followed by what is returned and the cost. No wasted text, though the rhetorical-question opener is slightly less direct than a plain declarative would be.

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 zero-parameter list tool with no output schema, the description covers what is returned (counties, towns, Dublin postal districts) and that it is free. It is close to complete, with only the return shape/ordering left unstated, which is minor for an enumeration endpoint.

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?

The tool takes zero parameters, so there is no parameter semantics to document; baseline 4 applies. The description correctly does not invent or imply any inputs.

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?

States a specific verb (lists) and resource (Irish areas: every county, town, and Dublin postal district) with the scope of the listing made explicit. The framing as the set of areas 'you can query' implicitly separates it from the rent-lookup siblings, so an agent can tell it is the discovery/index tool rather than a data-retrieval tool.

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?

'Which Irish areas have rent data?' and 'you can query' imply this should be called before a rent lookup to resolve valid area names, but no sibling is named and no explicit when/when-not condition is given. Usage is inferable rather than stated.

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 no annotations, the description carries the full burden and does so unusually well: it discloses pricing ($0.05 USDC), the exact payment protocols (x402 on Base, MPP on Tempo), that the server holds no wallet and never pays, that it returns HTTP 402 requirements plus the target URL, and that the caller must retry after paying.

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 first sentence front-loads the purpose and the rest is dense but every clause carries needed information (source, metrics, payment flow, URL). Slightly crammed into one long sentence, but no 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?

For a paid tool with no annotations and no output schema, the description covers what is returned, the source, the payment mechanics, and the retry workflow. An agent has everything needed to attempt the call and handle the 402 response.

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%, so county, segment, and quarters are already documented in the schema. The description reinforces segment semantics (new vs second-hand) and the trailing-12-month framing of quarters, but adds no syntax or defaults 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?

States a specific verb+resource (Irish residential sale-price comps by county) and enumerates exactly what is returned: median/p25/p75 per quarter and trailing 12 months, new vs second-hand, sourced from the PSRA Property Price Register. This is clearly distinguishable from the rent-oriented siblings (county_rent, paid_rent_check).

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 clear context for when and how to use it (paid endpoint, pay with your own x402/MPP client and retry the URL) and an exclusion ('Not a valuation'). It does not explicitly contrast with county_rent/paid_rent_check, so the routing between siblings is only implied.

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 no annotations, the description carries the full burden and does so well: it discloses the paid cost ($0.05 USDC), that the server holds no wallet and never pays, and that it returns HTTP 402 payment requirements via x402 on Base USDC or MPP on Tempo. This is substantial behavioral context an agent needs. It does not describe the return payload's shape, keeping it from a 5.

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 dense sentences, front-loaded with the multi-country purpose, then payment mechanics. Every sentence carries load, though the payment explanation is somewhat packed and could be separated for readability.

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 paid aggregation tool with no annotations or output schema, the description covers the aggregation scope, attribution, cost, and payment flow well. The main gap is that two parameters (beds, type) go unexplained, but nothing critical to calling it correctly is missing.

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 67% (beds and type are undocumented). The description clarifies the area parameter ('Irish housing report for an area, default Dublin') and ties the remaining fields to their report sources, but adds no detail for beds/type beyond what the schema lacks. Baseline 3 for partial coverage is appropriate.

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 and resource ('Housing picture for Ireland, Spain, France and Italy in one call') and enumerates the four component reports, which map to sibling tools like paid_ie_housing_report and paid_fr_house_prices. The 'in one call' phrasing implicitly distinguishes it from the per-country siblings, though it never explicitly says to prefer it.

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 explicit when-to-use/when-not or naming of alternatives such as paid_eu_house_prices. However, the 'in one call' framing and the four-country scope imply the use case: a multi-country comparison request. Usage is implied rather than stated.

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 no annotations, the description carries the full burden and does so well: it discloses the $0.03 USDC cost, that the server holds no wallet and never pays, that it returns 402 payment requirements (x402 on Base / MPP on Tempo), the exact retry URL, the Destatis license/attribution, and a 'not financial advice' disclaimer. This covers behavioral traits far beyond a normal tool description.

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-loads the core question ('How have German house prices moved?') before the payment mechanics. The payment detail is verbose but every sentence carries necessary information for a paywalled tool; only minor tightening is possible.

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 no-param tool with no output schema, the description fully specifies what data comes back (index base, dwelling breakdown, latest and change figures) and how to actually obtain it. Nothing an agent needs to invoke it correctly is missing.

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?

Zero parameters and 100% schema coverage, so the baseline is 4. There is nothing parameter-level the description needs to add, and it correctly avoids implying any inputs.

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?

States a specific resource (Destatis quarterly German house price index) and its exact contents: base 2025=100, all/new/existing dwellings, latest, 4-quarter and 12-quarter change. The Germany scoping cleanly distinguishes it from the sibling country variants (paid_es_house_prices, paid_fr_house_prices, etc.) without opening any schema.

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?

Makes the selection context clear (use this for German data vs. the other country tools) and lays out the exact workflow: this tool returns HTTP 402 requirements, the caller pays with their own x402/MPP client, then retries the given URL. It stops short of explicitly naming siblings or stating when-not-to-use, so it is a strong 4 rather than 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?

With no annotations, the description carries the full burden and does well: it discloses the payment schemes (x402 on Base, MPP on Tempo), the price, and crucially that the server holds no wallet and never pays, returning only 402 requirements and a URL. That is unusual and important behavioral context. It stops short of error modes, rate limits, or cache/freshness behavior, so it is not exhaustive.

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 purpose question is well front-loaded, but the body is dense and partially redundant — the URL is stated, then the instruction to 'retry that URL' repeats it, and licensing/endorsement boilerplate is interleaved. Much of the payment detail is genuinely needed for a paid tool, but it crowds out description of the returned data.

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 one-optional-param tool with no output schema and no annotations, the description covers the essentials: data source, geographic granularity, metric breakdowns (general/new/second-hand, latest, 4- and 12-quarter change), and the full payment handshake. The main gap is that per-region coverage limits or the response shape are not described, though the latter is understandable without an output schema.

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 optional 'region' param is documented in the schema itself, so the baseline of 3 applies. The description's mention of 'Spain and each autonomous community' loosely reinforces the regional scope but adds no format or default behavior beyond the schema example ('e.g. madrid').

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 opening question plus the parenthetical states a specific resource: the INE quarterly housing price index (IPV) for Spain and each autonomous community, with general/new/second-hand breakdowns and change windows. That clearly differentiates it from siblings like paid_fr_house_prices and paid_eu_house_prices, which are country-specific analogues. However, the payment mechanics consume most of the text, so the core purpose competes with logistics rather than leading cleanly.

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 tells the agent this is a paid call, the price ($0.03 USDC), and the exact flow (expect HTTP 402, pay with your own x402/MPP client, retry the URL), which is actionable usage context. It never says when to choose this tool over paid_eu_house_prices or the county-level siblings, nor whether region omission defaults to national, so the routing guidance is implied rather than explicit.

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 no annotations, the description carries the full burden and does it well: it discloses the price ($0.03 USDC), that the call returns HTTP 402 payment requirements, the two payment protocols (x402 on Base, MPP on Tempo), that the server holds no wallet and never pays, and the exact URL to retry. This is unusually complete behavioral disclosure for a paid 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?

It is front-loaded with the core question and packs a lot of value, but the closing payment sentence is wordy and partially restates the URL that appeared earlier. Dense but mostly earning 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?

No output schema and no annotations, yet the description covers the returned values (index, 4/12-quarter changes, rank), the data source (Eurostat prc_hpi_q, CC BY 4.0), the payment flow, and a disclaimer. Nothing an agent needs to call it correctly is missing.

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 both parameters are already documented (metric enum-ish values and the ISO 3166-1 alpha-2 country code). The description hints at which metrics exist via the output description but adds no syntax or format guidance beyond the schema, 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?

States a specific resource (latest quarterly house price index at 2015=100, plus 4- and 12-quarter % change and EU rank) and a specific scope (an EU country). The domain is clearly distinct from the rent/comps siblings, so an agent can separate it without opening the schema.

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 explains the mechanics of use (this is a paid tool; pay with your own x402/MPP client and retry the URL), which is genuinely useful context. But it never states when to prefer this over alternatives or what the prerequisite state must be before calling; usage is implied rather than guided.

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 no annotations, the description carries the full burden and does so well: it discloses the paid cost, that the server holds no wallet and never pays, that it returns HTTP 402 payment requirements (x402 on Base, MPP on Tempo) plus the target URL, and that the caller must pay with its own client and retry. This is exactly the behavioral context an agent needs before invoking a paywalled 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?

Front-loaded with the core question so the agent immediately knows the purpose, followed by cost, return fields, coverage gaps and payment mechanics in a logical order. It is dense and slightly long, but nearly every clause carries operational weight for a paid tool; only the 'Information, not financial advice' line is arguably disposable.

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?

There is no output schema, and the description compensates by enumerating the returned fields (sales count, mean and median EUR/m2 for apartments and houses) and their source (official DVF statistics, aggregates only, Licence Ouverte 2.0). Combined with the coverage exclusions and payment protocol details, nothing essential for correct invocation is missing.

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% and the single 'code' parameter already documents departement (75, 2A, 971) and INSEE commune (33063) formats with examples. The description's phrasing 'French departement or commune' reinforces that dual interpretation but adds no syntax or format detail beyond the schema, 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?

States a specific question-verb/resource ('property price per m2 in a French departement or commune') and enumerates the returned metrics (sales count, mean/median EUR/m2 for apartments and houses from official DVF statistics). It is clearly distinguishable from paid_eu_house_prices, paid_nl_house_prices and the other sibling price tools by its France-specific DVF scope.

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 clear usage context: it is a paid ($0.03 USDC) endpoint and lists coverage exclusions (Alsace, Moselle, Mayotte not covered), which tells the agent when the tool will not work. It does not explicitly name sibling alternatives for non-French markets, so it falls short of a full when/when-not/alternatives statement.

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 no annotations, the description carries the full behavioral burden and does well: it discloses the $0.05 USDC cost, that the server holds no wallet and never pays, that it returns HTTP 402 payment requirements, and names the two payment protocols and the endpoint URL. A retry/payment round-trip is fully traceable from this text.

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 question framing and then the payload, price and payment mechanics. Dense but every sentence is load-bearing; the rhetorical opening question is the only slightly wasteful element.

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?

No output schema exists, but the description enumerates the returned bundle components and their sources (CSO/RTB RIQ02, PSRA), plus the full payment contract, which is enough for an agent to decide and act. Minor gap: no indication of response format or whether the 402 is the only possible failure mode.

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%, so area, beds and type are already documented with examples and value lists in the schema. The description adds nothing about parameters, 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?

States a clear resource (Irish area housing report) and enumerates the bundle contents: rent benchmark, 4- and 12-quarter trend, rent-control summary, county ranking, sale-price comps. This differentiates it from narrow siblings like county_rent or paid_rent_trend, though it never names a sibling 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 explains the payment workflow well (returns 402 requirements, pay with your own x402/MPP client, retry the URL), but gives no guidance on when to choose this bundle over cheaper siblings such as paid_rent_check, paid_rent_trend or paid_comps. Usage is implied by the bundle contents rather than stated.

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 no annotations present, the description carries the full burden and does so thoroughly: it discloses the payment requirement, that the server holds no wallet and never pays, the exact 402 response contents (x402 on Base, MPP on Tempo), the target URL, and the required retry flow. It also adds licensing and a non-advice disclaimer.

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?

Dense but front-loaded: the data summary comes first, followed by the payment mechanics that an agent must act on. The license and disclaimer sentences are slightly boilerplate, but for a paid tool the length is largely justified.

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?

No output schema exists, yet the description specifies the index base, the dwelling breakdown (all/new/existing), the metric windows (latest, 4-quarter, 12-quarter change) and the payment handshake. Only the physical response envelope is left unstated, which is a minor gap.

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 beyond it by enumerating the concrete coverage set the region parameter accepts (Italy, macro-areas, Torino/Milano/Roma) and the national level, which supplements the schema's bare 'e.g. milano' example.

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?

Opens with a specific question and names the exact resource: ISTAT quarterly house price index (IPAB, base 2025=100) covering Italy, macro-areas and Torino/Milano/Roma. This cleanly distinguishes it from siblings like paid_de_house_prices, paid_es_house_prices and paid_fr_house_prices.

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 $0.03 USDC paywall and the explicit retry instructions make the usage context clear, and the data dimensions tell the agent what it can retrieve. It stops short of naming a free alternative or stating when NOT to use it, so it lands at 4 rather than 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?

With no annotations, the description carries the full burden and does so unusually well: it discloses the price ($0.02 USDC), the payment protocols (x402 on Base, MPP on Tempo), that the server holds no wallet and never pays, and that this call returns HTTP 402 requirements rather than data until the caller pays and retries. That is exactly the non-obvious behavior an agent would otherwise get wrong.

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?

Dense and front-loaded: the metric and geography come first, then scope caveats, then the payment mechanics. The rhetorical opener 'What are homes advertised for in Luxembourg?' is slightly wasteful filler before the substantive answer, but the remainder has virtually no redundant text.

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 no annotations and no output schema, the description supplies source, licence, units, time window, geography levels, property types, and the full payment handshake, so an agent can invoke it correctly. The only gap is the shape of the returned payload (fields, per-area minimum-sample or suppression behavior), which matters somewhat given no output schema.

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%, so both optional parameters (commune, property) are already documented in the schema. The description echoes the same semantics (commune, Luxembourg-Ville quartier, national; apartment or house) without adding syntax, casing rules, or defaults beyond what the schema says. 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?

States a specific resource and metric: mean ASKING prices (explicitly advertised, not sale, prices) and EUR/m2 for apartments and houses for sale in Luxembourg, at national/commune/quartier granularity over the latest 12 months. This is clearly distinguishable from the country-sibling tools (paid_de_house_prices, paid_fr_house_prices) and from the rent-oriented siblings.

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 clear context for use: 'Sale only' excludes rental queries, the data source and vintage (Observatoire de l'Habitat, CC0, latest 12 months) are named, and the payment precondition is spelled out step by step (call, receive 402, pay with your own client, retry the URL). It does not name an explicit alternative sibling for rent queries, so it stops short of a full when/when-not routing.

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 no annotations, the description carries the full burden and does so well: it discloses the paid nature ($0.03 USDC), that the server holds no wallet and never pays, the exact 402 flow, the payment protocols (x402 on Base, MPP on Tempo), the data license (CC BY 4.0), and a disclaimer. This is unusually complete behavioral disclosure for a mutation-adjacent paid call.

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 prose is dense and front-loaded with the question and data list, then the payment mechanics. The long URL and protocol details are necessary for invocation but make the block heavier than ideal; nothing is wasted, though it could be split more cleanly.

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 no output schema, the description enumerates the returned fields and time ranges, states the source table, and explains the entire payment handshake. An agent has everything needed to decide to call it and to complete the transaction.

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?

The tool takes zero parameters, so the baseline is 4. The description correctly implies no input is needed beyond payment handling, and the schema confirms an empty object.

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 opens with a specific question framing the resource ('How have Dutch house prices moved?') and enumerates exactly what data comes back (index, average price, sales, 12-month/5-year change, 24 months). This clearly distinguishes it from siblings like paid_eu_house_prices or paid_ie_housing_report by naming the Dutch market and the CBS table.

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 gives strong operational guidance: the tool returns HTTP 402 payment requirements, the agent must pay with its own x402/MPP client, then retry the listed URL. It does not explicitly say when to prefer this over paid_eu_house_prices, but the payment mechanics are unambiguous.

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 no annotations provided, the description carries the full burden and does so well, disclosing it is paid ($0.02 USDC), that the server holds no wallet and never pays, that it returns HTTP 402 payment requirements (x402 on Base, MPP on Tempo) rather than the data, and the exact URL to retry. This is exactly the non-obvious behavior an agent must know before calling.

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?

Dense but front-loaded: the cost question and covered items come first, then the payment mechanics. The embedded URL is long but necessary. Every sentence carries weight, with little padding.

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 payment-gated tool with no annotations and no output schema, the description covers the payment protocol, cost, and retry target adequately. It leaves the exact return payload shape somewhat open, but the enumerated components give the agent enough to act.

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 adds genuine meaning by tying its outputs to parameters: LTI/LTV checks imply income/deposit/mortgage, and the Help to Buy estimate implies first_time/new_build.

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?

States a specific resource and outcome — the cost to buy a home in Ireland — and enumerates what the result covers (stamp duty, Help to Buy, LPT, legal/registration fees, LTI/LTV checks). It is clearly a paid computation tool, though it does not explicitly distinguish itself from the overlapping siblings stamp_duty_rates or paid_ie_housing_report.

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 explains the mechanical usage path well: pay with your own x402/MPP client and retry the URL. However, it gives no guidance on when to choose this tool over stamp_duty_rates or paid_ie_housing_report, so the selection decision is left implicit.

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 no annotations, the description carries the full burden and does well: it discloses the $0.02 cost, that the server holds no wallet and never pays, the HTTP 402 response shape, and the two payment protocols (x402 on Base, MPP on Tempo). It stops short of describing what the paid data payload contains beyond the trend/field hints.

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 rhetorical opening question is mildly wasteful but quickly grounds the use case, and the payment mechanics follow in tight sentences. The critical constraint (no wallet, returns 402) is front-loaded before the URL, so the structure works.

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 no output schema and no annotations, the description does the heavy lifting on the payment contract, which is the hard part of invoking this tool. It is only slightly incomplete in not sketching the rent data returned after payment.

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%, so the schema already documents area, beds, and type with examples and value lists. The description restates the same concepts (town/postal district, bedroom/type filters) without adding syntax or format beyond the schema, 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 states a specific resource (average rent for a town or Dublin postal district) with filters (bedroom/type) and trends (4- and 12-quarter), so the verb+resource are clear. It does not differentiate itself from the siblings county_rent or paid_comps, leaving the agent to infer the boundary, which holds it below 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?

It gives a clear usage sequence for the payment flow (get 402 requirements, pay with your own x402/MPP client, retry the URL), which is real guidance. However, it never says when to prefer this paid tool over the free-looking siblings county_rent or list_areas, so selection guidance is only implied.

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 no annotations, the description carries the full burden and does so unusually well: it discloses the $0.03 USDC cost, that the server holds no wallet and never pays, that it returns HTTP 402 payment requirements (x402 on Base, MPP on Tempo), and the exact retry URL. It adds stale flags as a data caveat. It omits pagination/response-shape details, keeping it just under a 5.

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: a hook question, the data description, and the payment mechanics — each earns its place with no filler. The payment sentence is dense but necessary given the no-annotations, paid-invocation context. Front-loading is adequate, though the hook question precedes the concrete deliverable.

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 paid tool with no output schema and no annotations, the description covers what data is returned, its source, the paid nature, the payment protocols, and the retry URL — enough to invoke it without guessing. Only finer return-format details (row structure, ordering guarantees implied by sort) are absent.

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 no enums are declared, so the schema already documents n, beds, sort, and type with defaults and value lists. The description adds no parameter-level meaning beyond that, which is the baseline 3 when the schema does the heavy lifting.

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 opens with a specific question framing and states the deliverable: a county ranking by latest average rent plus 4- and 12-quarter % change, with the data source (CSO/RTB RIQ02). This is a clear verb+resource. It does not, however, explicitly distinguish itself from siblings like county_rent or paid_rent_check, so it stops short of 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?

It conveys the key usage condition that this is a paid call and requires an external x402/MPP client, then explains the pay-and-retry workflow. However, it never says when to prefer this over county_rent or paid_rent_check, nor any when-not conditions, so usage selection versus alternatives is left to inference.

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 no annotations, the description carries the full burden and does well: it discloses the free tier, a concrete rate limit (20 calls/day per client), the included VAT note for new builds, and that results come 'with source and date'. It stops short of describing error/empty behavior or response shape beyond the rate bands, which keeps it from a 5 for a zero-annotation 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?

Front-loaded with the resource, then the concrete contents, the exclusions, the rate limit, and the disclaimer — every sentence carries information. The interrogative opening is slightly stylized but still efficient; no filler sentences.

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?

There is no output schema, so the description must describe the return, and it does: rate bands, VAT note for new builds, source and date. Combined with the rate limit and disclaimer, an agent has everything needed to call it and set expectations.

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?

The schema has zero parameters, so there is nothing to disambiguate and the baseline is 4. The description correctly implies no input is required to fetch the bands.

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?

States a specific verb+resource (Irish residential stamp duty rates) and goes further by enumerating the actual rate bands returned (1%/2%/6%), so the agent knows exactly what payload to expect. It also differentiates itself from siblings by naming paid_purchase_cost as the calculation alternative.

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?

Explicitly draws the boundary: 'Does not calculate for a price; the paid purchase-cost tool ($0.02) does.' This tells the agent both when to use this tool (rate lookup) and when to route elsewhere (price calculation), and the price is even disclosed.

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