Kvartiry-Phuket: Phuket real estate and travel data

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds real value beyond that: data provenance (/ceny/), that aggregates are dated, that sample sizes accompany the medians, the listing-vs-transaction distinction, and a CC BY 4.0 license note.

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?

Purpose is front-loaded and the sentence is information-dense, but the closing English sentence ('Dated asking-price aggregates, not transaction prices') merely restates content already present in the Russian text, and the whole definition is presented bilingually. The duplication costs it conciseness without adding new information.

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 compensates by explaining what the response contains — medians, ranges, and sample sizes — which is exactly what an agent needs. A single optional parameter plus complete annotations means little else is required; only the sibling-routing gap remains.

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?

Only one optional parameter, and the schema already documents it at 100% coverage including slug and Cyrillic/English examples. The description mentions 'districts' as a slicing dimension, which lightly corroborates the parameter, but adds no syntax or format detail beyond the schema. 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 (asking-price aggregates for Phuket apartments/condos) with verb-like specificity, plus granularity (medians, ranges, sample size) and slicing dimensions (bedrooms, budgets, districts). It does not explicitly distinguish itself from the sibling get_condo_assessment, so sibling differentiation is missing, but the purpose itself is unambiguous.

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 'asking prices, not transaction prices' caveat implies the appropriate use case (market-listing analysis rather than sold-price analysis), which is useful implied guidance. However, there is no explicit when-to-use statement and no routing to alternatives such as get_condo_assessment, so usage is only inferred.

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 readOnly/idempotent/non-destructive, yet the description adds substantial extra context: the data sources (NOAA WAVEWATCH III, OpenStreetMap bay shape), the 2017–2026 coverage window, that it is multi-year statistics rather than a forecast, that ranges reflect uncertainty in the sea-point estimate, that lifeguard flags are the real-world authority, and the instruction to cite the returned URL.

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 when-to-use trigger is correctly front-loaded and no sentence is pure filler, but the body is dense with stacked parentheticals (sources, range logic, lifeguard caveat) that slightly dilute readability. Efficient overall.

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 carries the burden of explaining returns and does so: a 25-beach ranking by share of calm days, day counts, range handling, and ranked-by-lower-bound logic. An agent has everything needed to call and interpret 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 100%, so both parameters (month, limit) are already fully documented in the schema, including the month numbering example. The description's 'in August / July' phrasing mirrors rather than extends that, so 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 verb+resource (returns a ranking of calm-swimming Phuket beaches for a given month) and explicitly distinguishes itself from the sibling get_sea_today. An agent can select this tool 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?

Opens with an explicit trigger ('Вызывайте, если спрашивают...'), gives concrete examples (no waves in August, quiet sea in July), and names the alternative for a different need ('про сегодня — get_sea_today'). Both when-to-use and when-to-use-something-else are covered.

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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds real value beyond that: the provenance of the numbers (ERA5 reanalysis, Météo-France sea temps, airport station) and the instruction to cite the returned URL, which is an operational requirement not encoded anywhere else.

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 dense sentences with the dataset scope front-loaded, followed by the calling modes and the citation instruction. The field list is long but each item is substantive; nothing reads as 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 no output schema, the description must carry the return-value burden, and it does by enumerating the metrics and their sources, the time coverage, and the two response shapes. Minor gaps remain (units, whether waves are significant-height, how the URL is surfaced), but an agent has enough to call and interpret 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 coverage is 100%, so the baseline is 3, and the description goes beyond the schema by specifying the default behavior (absent parameter = all-12-month overview) and the effect of supplying month (single month, more detail). That default-vs-explicit semantics is the one thing the schema cannot express.

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 (monthly climate normals for Phuket 2015–2025) and enumerates the exact datapoints returned — precipitation median/mean, rain days, air and sea temperature, waves, cloud cover — plus the underlying sources (ERA5, Météo-France, airport station). This clearly separates it from current-condition siblings like get_weather_now, get_observed_weather and get_sea_today.

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 explicitly defines the two calling modes: without the parameter it returns an overview of all 12 months, with month (1–12) it returns one month in detail. That is clear invocation guidance, but it never names the current-weather/sea siblings an agent should prefer for 'now' data, so the when-not 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?

Annotations already establish read-only, idempotent, closed-world, non-destructive behavior, so the bar is lower. The description adds genuine context beyond them: the data source (Thai Treasury Department), the unit (THB/m²), and a clear warning that these are statutory assessed values, not market prices — an important interpretive caveat.

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 and unit, then constraints, then search axes — a good order. The trailing English sentence 'Official statutory assessment rates, not market prices' is a near-duplicate of the opening line, a minor redundancy that bilingual delivery partly excuses.

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 carries the return-value burden and does so: min, median, max across residential categories plus a record count. Combined with the data provenance and the non-market caveat, an agent has everything needed to call and interpret this tool.

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 parameters are already documented in the schema, including the district values and the bilingual matching note. The description repeats the same district names and search facets, adding no format or syntax 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 verb+resource: official statutory assessment rates (THB/m²) from the Thai Treasury Department, scoped to Phuket condominiums. It explicitly contrasts itself with market pricing, which separates it from the sibling get_asking_prices without the agent opening either 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?

The line 'Это не рыночная цена / not market prices' effectively signals when this tool is the right one versus a price-lookup sibling, and it names the supported search axes (Thai name or condominium_id, and amphoe). It never names the alternative tool explicitly, so the routing is implied rather than spelled out.

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 the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds real value beyond them: it discloses that the price row is conditionally present only when published, and instructs the agent to cite the returned URL.

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?

Purpose and content are front-loaded in a single compact clause, with the conditional caveat placed at the end. The bilingual restatement is somewhat redundant but does not obscure the core information.

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 carries the return-value burden and does so by enumerating the content sections the agent should expect. Annotations handle the safety profile, so nothing essential is missing for a single-param read tool.

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%, with the slug's pattern and its provenance (from list_districts) fully documented in the schema itself. The description only restates 'по slug' without adding format or example detail, so the baseline 3 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 (get/overview) and resource (district), then enumerates the returned content (location, infrastructure, pros/cons, who it suits, related guides, price row). This clearly distinguishes it from sibling list_districts and the various get_* tools.

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 is only implied via 'по slug' and the conditional note that the price row appears only if published. The description never explicitly says when to prefer this over list_districts or get_guide; that routing hint lives in the schema's param text, not the description.

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 readOnly/idempotent/non-destructive/closed-world, lowering the bar. The description adds real value for a tool with no output schema by disclosing the exact returned fields and the Markdown-vs-outline behavior. It omits error/not-found behavior but is otherwise solid.

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 what is returned and dense with useful detail. The bilingual duplication (Russian then a condensed English restatement) is slightly redundant, but the English line still earns its place by adding the URL-citation instruction.

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 tool with no output schema, the description covers both invocation modes and the full return shape, so an agent knows how to call it and what to expect. Nothing essential 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 fully documented in the schema itself. The description's mention of the section parameter adding Markdown largely restates what the schema already says, so the baseline 3 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?

States a specific verb (returns) and resource (a guide), and enumerates exactly what is returned: title, URL, description, update date, intro, and H2 sections. It also distinguishes its two distinct modes (full outline vs. single-section Markdown), which cleanly separates it from search_guides.

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?

Clear context for both modes: without 'section' you get the structure, with 'section' you get one section's Markdown, plus an explicit instruction to cite the returned URL. It does not explicitly name search_guides as the discovery prerequisite, though the slug schema description covers that.

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, non-destructive and closed-world, but the description adds substantive context beyond them: data source (METAR VTSP, Iowa Environmental Mesonet archive), the returned time window (last full month plus past-year average), a data timestamp, and a source URL that may be a month page or JSON. That is rich operational detail not derivable from 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 trigger condition is front-loaded and every element (returns, source, timestamp, contrast with forecast and climate) earns its place. The prose is a dense run-on sentence rather than cleanly separated points, which slightly hurts scannability.

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 carries the burden and does so well: it explains the return content, comparison to normal, data timestamp, and the URL/page-vs-JSON behavior. An agent has everything needed to call it correctly.

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 'month' parameter is already well documented (1=January, 9=September, returns the last complete such month). The description echoes the 'latest matching month' semantics without adding format or edge-case detail beyond the schema, so the baseline of 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 verb+resource: it returns observed weather (rainy days, thunderstorms, long daytime rains) for the latest matching month on Phuket, plus the multi-year average. It explicitly distinguishes itself from siblings by naming get_climate and by declaring it is a past fact, not a forecast.

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 an explicit trigger ('Вызывайте, если спрашивают, как было на самом деле...') and names the alternative for climate norm (get_climate). It does not explicitly rule out get_weather_now for current conditions, so the boundary with that sibling 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?

Annotations already cover the safety profile (readOnly/idempotent/non-destructive), yet the description still adds substantive behavior: NOAA WAVEWATCH III source with 6-hour refresh, a hard freshness cutoff ('данные старше 12 часов не выдаются: ответ «нет свежих данных»'), the open-sea/bay-shape model caveat, the warning that lifeguard flags are decisive, plus inclusion of NOAA OISST water temperature and a citation URL.

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 trigger condition, then the return payload, then freshness and caveats – a sensible order. It is dense and runs long across several clauses, so some tightening is possible, but nearly every clause carries information.

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 carries the return-shape burden and does so fully: wave class, wave height estimate, water temperature, data timestamp, URL, and the empty-result case ('нет свежих данных'). Nothing an agent needs in order to call and interpret it 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 'beach' parameter is fully documented there, so the baseline is 3. The description adds meaning beyond the schema by stating the output scoping: with the parameter you get one beach, without it all 25 – a behavioral consequence the schema does not express.

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?

Stated with a specific verb-and-resource framing: it answers 'where is the sea calm in Phuket today' and returns wave class, wave height, water temperature, data time and a URL for 25 beaches. The scope is unmistakable. However, it never names or distinguishes itself from the overlapping sibling get_calm_beaches (and get_weather_now), so an agent cannot tell which to prefer from the text alone.

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?

Explicit trigger conditions are given in the opening clause ('Вызывайте, если спрашивают, где... нет волн, на каком пляже сейчас спокойное море...') plus the English 'Call it for ...'. This is clear context for when to reach for the tool. It stops short of exclusions or naming alternatives, so it is not 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 declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond that: the upstream data source (MET Norway model), the exact field set returned, the forecast horizons (24h hourly, 10 days daily), and the obligation to cite the returned URL. It does not disclose freshness/caching or rate-limit behaviour, so it stops short of 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?

Front-loaded with the core purpose, then the field list, then the forecast horizons, then the citation requirement — a sensible ordering with no filler. The field enumeration is long, but each item maps to a real returned value, so only minor trimming would be 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?

With no output schema, the description responsibly enumerates return content (temperature, heat index, wind, humidity, cloud, next-hour precipitation, sunrise/sunset, hourly and daily outlooks), which is exactly what an agent needs to plan a response. It is incomplete only in the routing dimension — nothing tells the agent when this beats get_observed_weather or get_climate.

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 both optional lat/lon parameters carry their own bounds and defaults in the schema. The description adds nothing about coordinates — not even that the tool is constrained to Phuket — so the baseline 3 applies rather than any upside.

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 and resource ('Текущая погода на Пхукете по модели MET Norway') and enumerates the returned fields precisely, so an agent knows exactly what it gets. It does not, however, distinguish itself from close siblings like get_observed_weather or get_climate, leaving the agent to guess which weather tool is authoritative for a given request.

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 is only implied: the wording 'сейчас / current weather' signals a real-time snapshot, and the closing instruction 'cite the returned URL' is a concrete usage requirement. There is no explicit when-to-use or when-not-to-use guidance, and no mention of get_observed_weather or get_climate as alternatives, which is a real gap given the crowded weather-tool neighbourhood.

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 readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds the scoping rule (only districts with an overview page) and the field contents, which is genuinely useful, but it says nothing about ordering, counts, or pagination. With annotations carrying the main burden, this is an adequate mid-level contribution.

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 Russian and English sentences convey essentially the same content, making the second sentence largely redundant. It is front-loaded and readable, but it wastes a sentence instead of using the space for ordering, filtering, or pagination details.

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 carries the return-value burden and does list the key response fields (slug, name, URL, snapshot presence), which is sufficient for a simple zero-parameter list tool. Minor gaps around ordering and completeness of coverage, but nothing an agent needs to invoke it 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly implies no input is needed since it simply enumerates districts.

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 (list) and resource (districts) and defines the exact inclusion criterion — only Phuket districts that have an overview page on Kvartiry-Phuket. It also enumerates the returned fields (slug, name, URL, snapshot presence). Distinguishable in intent from the singular get_district sibling, though it never names that 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?

Usage is only implied: the plural name and 'list' verb suggest enumerating all districts, while get_district presumably fetches one. There is no explicit 'use this when you want all districts, use get_district for a single one' routing statement, so the agent must infer the division of labor from naming alone.

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 readOnly/idempotent/no-destruction, so safety is covered. The description adds genuine behavioral context beyond them: the status is 'honest' (live or offline plus last-checked time), results include coordinates and links, and the agent is told to cite the returned URLs.

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 trigger is front-loaded and the total length is short. However, the same content is stated twice (Russian then English: 'Список веб-камер Пхукета с честным статусом' / 'Lists the Phuket webcams with their honest status'), which is mild 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?

With no parameters and no output schema, the description carries the return-value burden and does so adequately, listing status, coordinates, links and weather. For a simple zero-param read tool this is close to complete.

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 there is nothing for the description to disambiguate. Baseline 4 applies; no parameter-level meaning is missing.

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 ('Список веб-камер Пхукета') and enumerates the returned fields (status, coordinates, page links, weather). It is clearly distinguishable from weather-oriented siblings like get_weather_now and get_observed_weather, though it never explicitly contrasts itself with them.

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 an explicit trigger: call this when asked which cameras are live now or where to view Phuket beaches online. There is no 'when not to use' or named alternative, so it falls 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 cover the safety profile (readOnlyHint=true, openWorldHint=false, idempotentHint=true, destructiveHint=false), lowering the bar. The description adds that it compares/returns URLs to cite, which is mild useful context, but says nothing about result format, match behavior, or ranking. With annotations doing the safety work, a 2 reflects thin added behavioral value.

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 brief and front-loads the comparison attributes, but it is slightly garbled ('Ищет по сравнению пляжей') and mixes Russian and English awkwardly. It is not wasteful, but the structure is rough enough to cost precision.

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 simple two-parameter read-only search with full schema coverage and no output schema, the description is barely adequate. It conveys scope and the comparison dimensions, but does not explain result shape, match semantics, or how it differs from sibling lookup tools.

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 parameters (query and limit) are already documented in the schema, including the 1-10 bound. The description adds no syntax or format detail beyond what the schema provides. Baseline 3 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: it searches/compares Phuket beaches by named attributes (side of island, shore length, airport road, walking-distance infrastructure, nearby live cam). This is clear and concrete, though it does not explicitly distinguish itself from sibling search tools like search_faq or search_guides.

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 guidance, no mention of alternatives, and no exclusion criteria. The 'cite returned URLs' instruction is an output-usage note rather than selection guidance. An agent must infer that this is a lookup-by-name tool.

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 readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond that: results include the source page URL and an update date, which matters because there is no output schema to convey return shape.

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 verb and corpus scope; the citation instruction is a useful closing note. The parallel Russian and English sentences are largely duplicative, costing a little conciseness, but nothing is 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 two-parameter search tool with full schema coverage and rich annotations, the description covers purpose, corpus, and the key return fields (URL, update date) in the absence of an output schema. Only the absence of sibling routing keeps it from being fully complete.

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 both parameters (query, limit) carry their own descriptions and constraints (1-10, maxLength 200). The description adds nothing about parameter 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?

States a specific verb (searches) and resource (site FAQ) and scopes the content corpus: questions from guide, district, monthly-weather and beach pages. That cross-domain aggregation implicitly distinguishes it from the narrower search_beaches/search_guides siblings, though it never names them 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?

Usage is implied by the described coverage (aggregated FAQ across several domains), and there is a citation directive ('cite the returned URLs'). But there is no explicit when-to-use vs. when-not, and no alternative sibling is named for selecting between this and search_guides/search_beaches.

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 the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds real value the annotations lack: it discloses that up to 10 guides are returned with title, URL, description and update date, and that results are Russian-language only.

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 what is searched and what is returned. The bilingual duplication (Russian then English) is somewhat redundant, but each line is otherwise tight and purposeful.

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 usefully enumerates the returned fields, and all parameters plus the safety profile are covered by schema and annotations. It is complete enough to call correctly, with only sibling routing left implicit.

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%: query (with examples and language note) and limit (1–10) are fully documented in the schema. The description only echoes the 'up to 10' ceiling and adds no format or syntax beyond what the schema provides, 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 verb (searches) and resource (published Kvartiry-Phuket guides) plus the topical scope (buying, renting, taxes, visas, Phuket life). An agent can distinguish it from get_guide by the verb/scope, though the description never names that 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?

Usage is implied by the topical scope and the English line instructing to cite returned URLs, but there is no explicit when-to-use vs get_guide or search_faq routing, nor any exclusion guidance.

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