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

No annotations are provided, so the description must carry the full behavioral burden. It does not state whether this requires specific permissions, what happens on duplicate serial numbers or errors, or any rate limits. The parameter hints (e.g., 'tel_password: only digits') add minor context, but overall behavioral disclosure is thin for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear purpose sentence followed by parameter explanations. It is appropriately sized for a 9-parameter tool, though it slightly lacks front-loading of critical usage constraints. Each line earns its place by clarifying a parameter.

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?

An output schema exists, so return values need not be explained. However, with no annotations and 0% schema description coverage, the description leaves gaps in behavioral aspects like authentication requirements, error conditions, and whether the device is immediately usable. It is adequate but not complete for a creation tool with nine parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does so by providing human-readable explanations for all nine parameters, including examples for devtype (T100, T102, L1000, etc.), format for wifi_credentials, and constraints like 'tel_password: only digits'. This significantly improves parameter understanding beyond the bare 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?

The description opens with a specific verb+resource: 'Добавить новое устройство в аккаунт пользователя ZONT' (Add a new device to the ZONT user account). It clearly distinguishes from siblings like zont_delete_device and zont_update_device, which perform different operations on devices.

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 implies usage by stating it adds a device to a user account, but offers no explicit when-to-use vs alternatives, no prerequisites, and no exclusions. For a creation tool, guidance on needing an authenticated account or conflicts with existing serial numbers would be valuable but is absent.

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 behavioral burden. It usefully discloses that clear_data removes accumulated data and clear_access revokes other users' access, clarifying destructive side effects, but it omits irreversibility, required permissions/ownership, and whether the action can be undone.

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 one-sentence purpose is front-loaded, followed by a compact per-parameter glossary with no filler. Slightly terse on behavioral context, but every line earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter, annotation-free mutation tool with an output schema (so return values need not be described), the definition covers purpose and all parameters adequately. It stops short of the permission/irreversibility context an agent should know before deleting a device.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does: every one of the five parameters is explained, including the conditional rule that transfer_username applies only when transfer=true. This adds genuine meaning beyond bare parameter names.

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 verb+resource ('Удалить устройство из аккаунта пользователя ZONT') and immediately names the alternative behavior (transfer to another user), making its scope unambiguous. An agent can easily distinguish it from siblings like zont_add_device and zont_update_device.

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 that transfer is an alternative to deletion, but never states when to choose deletion over the sibling tools zont_update_device or zont_add_device, nor any prerequisites or confirmation requirements for this destructive operation. Usage is implied by the tool name rather than explicitly 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 must carry the full behavioral burden. It discloses that it writes a file to disk and depends on a prior generate step, but says nothing about overwrite behavior, permissions, size limits, or failure modes for a local-write operation.

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 one-line purpose followed by two tight parameter notes; every sentence carries information and nothing is redundant.

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?

An output schema exists, so return values need no explanation, and both parameters plus the upstream dependency are covered. Only minor behavioral details about the local file write 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 coverage is 0%, so the description must compensate, and it does: it explains archive_id comes from zont_generate_archive and that output_path is the destination file for the zip. Both parameters gain meaning beyond the bare schema titles.

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 (download), a specific resource (the zip archive previously created by zont_generate_archive), and the effect (save to disk). It also clearly distinguishes itself from its sibling zont_generate_archive by naming it as the prerequisite producer.

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 establishes the key precondition: the archive must have already been created by zont_generate_archive, which sequences the workflow correctly. It does not, however, state exclusions or alternatives beyond that dependency.

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 behavioral burden. It usefully discloses the creation-then-download handoff and the archive_id artifact, but says nothing about whether the job is async/long-running, permission requirements, or behavior for very large ranges.

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 purpose, then the workflow handoff, then a compact per-parameter glossary. Every block earns its place with 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 4-required-param generation tool with an output schema, the description covers purpose, workflow, and all parameters adequately. The only gap is operational context (async nature, limits), which is minor given the output schema handles return values.

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 0%, so the description must compensate and it does: it defines all four parameters, gives units and inclusivity for mintime/maxtime (unix time, включительно), and explains split_by as per-day vs per-month file splitting with the literal enum values.

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 with scope: 'Запросить создание архива со всеми данными устройства за период времени'. It also names the downstream sibling (zont_download_archive), making the tool trivially distinguishable from 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?

Explicitly tells the agent what to do next: the returned archive_id must be passed to zont_download_archive, establishing the two-step workflow. It does not state when not to use it or any preconditions, so it stops short of full routing guidance.

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 credential precondition, that the token is long-lived, and how the result is meant to be reused (ZONT_TOKEN). It stops short of describing failure modes or error behavior when credentials are missing/invalid.

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, followed by the precondition and the token-reuse note; the trailing client_name line reads slightly like an appended schema note rather than integrated prose but wastes no words.

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?

An output schema exists, so return-value explanation is unnecessary. For a one-parameter auth tool the description covers purpose, prerequisites, and downstream usage adequately; only error/permission edge cases are unaddressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for the single required parameter, so the description must compensate — and it does, defining client_name as the human-readable name of the requesting application. Only minor ambiguity remains (format/length expectations).

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 and resource ('Получить долгоживущий аутентификационный токен ZONT') and is clearly distinct from every sibling, which are all device/command/archive operations rather than authentication. An agent can recognize this as the auth/bootstrap tool 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 gives the decisive precondition (the server must be launched with ZONT_LOGIN and ZONT_PASSWORD) and explains the follow-up use of the token via ZONT_TOKEN for subsequent runs. It does not enumerate alternatives or when-not-to-use, but no sibling overlaps this purpose, so the context is effectively complete.

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?

No annotations are provided, so the description carries the full burden. It does disclose that results include device settings and that io carries per-device current states when requested, but says nothing about authentication needs, scope limits, or result size/pagination.

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 short lines, front-loaded with the main action; the parameter note is separated and terse. No filler, though the load_io line is slightly clipped rather than fully formed.

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?

An output schema exists, so return-value detail is not required here, and a read-only listing tool with one optional boolean has modest demands. The only real gap is the absence of any guidance about when this enumeration is preferable to the other list/event 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 0% — the schema only offers the bare title 'Load Io'. The description rescues that gap by explaining load_io controls whether current per-device states are returned in the io field, which the schema alone would not convey.

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: retrieving the list of the user's ZONT devices along with their settings. This clearly separates it from the write-oriented siblings (zont_add_device, zont_delete_device, zont_update_device), 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?

There is no guidance on when to call this versus zont_load_data, zont_raw_events, or the per-device tools; the agent must infer that this is the enumeration entry point. The load_io note explains a parameter, not a usage condition or prerequisite.

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 disclose meaningful traits: multi-device batching, the timestamp convention (unix seconds since 1970-01-01 UTC), and the valid data_types vocabulary. It is silent on authentication requirements, rate limits, result size/pagination, and whether the call is read-only, leaving real gaps for a data-fetch 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 purpose sentence followed by the request format and accepted values. The data_types enumeration is long but earns its place as the only source of that vocabulary; otherwise there is little waste.

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?

An output schema exists, so return values need not be explained, and the input format is fully documented despite zero schema coverage. What remains missing is operational context: auth needs, limits on how many devices/time ranges can be batched, and how it differs from the archive siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the nested item schema is opaque (additionalProperties: true with no properties), so the description is the only documentation. It compensates well by spelling out the request object shape (device_id, data_types, optional mintime/maxtime) and enumerating valid data_types values, adding substantial meaning 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?

The description states a specific verb and resource (load device data history) and enumerates the concrete content it covers: temperature sensor readings, thermostat operation, GPS tracks, events, controller state. An agent immediately knows what it retrieves, though it does not explicitly contrast itself with the archive siblings (zont_generate_archive/zont_download_archive) or zont_raw_events.

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 rather than stated: it notes that multiple devices and data types can be requested in a single call, which hints at batching behavior. However there is no explicit when-to-use versus when-to-use-alternatives guidance, nor any exclusion of the archive or raw_events siblings.

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?

No annotations are provided, so the description carries the full behavioral burden. 'Получить историю' makes the read-only nature obvious and the parameter notes add context (unix time, inclusive bounds), but there is no mention of authentication, result-size limits, or pagination behavior for potentially large event histories.

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 in the first sentence, followed by a scannable parameter list. Every line earns its place; the only mild redundancy is the short event-type illustration line.

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?

An output schema exists, so return values need no prose. With all five parameters documented and the time-range semantics pinned down, an agent has enough to invoke it correctly; only the vocabulary of event types remains unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it largely does: all five parameters are explained, with mintime/maxtime specified as inclusive unix timestamps and except_ linked to the API's 'except' field. The one gap is that valid event-type strings for only/except_ are never characterized.

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+scope: retrieve a device's event history for a given time interval, and enumerates representative event kinds (arm/disarm, alarms, GPS/GSM, autostart). It is clear what the tool returns. It does not distinguish itself from plausible siblings such as zont_load_data or the archive tools, 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?

The event-type examples imply when the tool is useful, but there is no explicit when-to-use vs. alternatives (e.g. archive generation/loading) and no exclusions or prerequisites. 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?

No annotations are provided, so the description carries the full behavioral burden. It implies a mutating action on a physical device but never states whether the command is reversible, what authorization is needed, or whether the command must be pre-configured before this call will succeed beyond a passing mention.

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 purpose sentence, then supplies prerequisite context, then the parameter notes — no filler. The per-parameter lines are slightly redundant given the schema but keep the block readable.

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?

An output schema exists, so return-value explanation is not needed, and the description does cover purpose plus the origin of command_id. For an unannotated mutation tool targeting physical hardware, it is still thin on side effects and failure conditions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does document both parameters. However, 'device_id: ID устройства' merely restates the field name; only command_id adds real meaning by pointing to custom_controls as its source.

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 ('send a custom command to a device') and names the supported device families (ZTC-7xx, Mega SX), which is more than a restatement of the name. It does not explicitly contrast itself with the sibling zont_send_z3k_command, but 'custom command defined in the configuration utility' provides enough specificity to distinguish intent.

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 a concrete prerequisite and discovery path: commands come from the device's custom_controls setting, and points the agent at zont_list_devices to obtain the ID. It stops short of stating when to prefer this over zont_send_z3k_command, so no exclusions or alternatives are given.

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 that the method is absent from official ZONT API docs, was reconstructed by intercepting web-interface traffic, that it should be used cautiously, and that results should be verified with zont_list_devices. It omits what happens on delivery failure or whether commands are reversible, keeping it 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 caution and example, then a clean per-parameter list. Slightly redundant in restating parameter meanings already shown in the inline example, but no sentence is 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 6-parameter, reverse-engineered mutation tool with nested command_args and an output schema present, the description covers purpose, risk, sourcing of IDs, and a worked example. It does not address error/failure semantics, but the output schema covers return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does: every one of the 6 parameters is explained, including where to source object_id (z3k_config.heating_circuits / boiler_adapters), where firmware_version comes from and that omitting it drops the field, and is_guaranteed's meaning and default. This adds real meaning the schema lacks.

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 (send) and resource (undocumented z3k command) with the target device families named, so the agent knows exactly what the tool does. However, it never distinguishes itself from the sibling zont_send_custom_command, which an agent could easily confuse with this one.

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?

Provides a concrete usage example (changing heating-circuit target temperature) and a caution plus a verification step via zont_list_devices, which is genuinely useful context. It stops short of stating when to prefer this over zont_send_custom_command or any when-not conditions.

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?

Нет аннотаций, поэтому описание несёт полную нагрузку. Оно сообщает, что команда доставляется только при наличии связи с устройством, и что это изменяющая состояние операция. Однако не описаны права доступа, возможные побочные эффекты (например, что произойдёт при отключении охраны), или формат ответа. Для мутирующего инструмента без аннотаций этого недостаточно.

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?

Описание состоит из четырёх предложений, каждое из которых несёт информацию. Оно структурировано, но незначительно избыточно в перечислении значений. В целом эффективно и сфокусировано.

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?

Для инструмента с 4 параметрами, без аннотаций, но с выходной схемой, описание заполняет большинство пробелов: объясняет назначение, условие доставки и семантику параметров. Не хватает информации о правах доступа и возможных ошибках, но в целом достаточно для корректного вызова.

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?

Схема не содержит описаний параметров (0% coverage), но описание подробно объясняет семантику каждого параметра: portname — имя состояния, type — тип значения, value — конкретные значения в зависимости от type. Это значительно превосходит базовый уровень и компенсирует отсутствие описаний в схеме.

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?

Статья указывает конкретный глагол и ресурс: «Отправить устройству команду на изменение состояния», и перечисляет управляемые состояния (guard-state, siren, engine-block, webasto, auto-ignition). Это отличает инструмент от других командных инструментов (send_custom_command, send_z3k_command), хотя не уточняет, чем именно он отличается от них.

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?

Указано условие «Команда доставляется, только когда устройство на связи», что является важным контекстом использования, но нет явных указаний, когда использовать этот инструмент вместо send_custom_command или send_z3k_command. Также отсутствуют предупреждения о необратимости команд.

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?

No annotations are provided, so the description carries the full burden. It does disclose a meaningful behavioral trait — the merge/partial-update semantics where unspecified fields retain their previous values — but says nothing about authentication requirements, reversibility, validation failures, or any rate limits on a clearly mutating 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 purpose is front-loaded and the sentences are short and functional, with the behavioral note about partial updates placed before the parameter documentation. The sentence deferring the full settings list to external documentation is somewhat loose but still earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values need not be described, and the description covers how to call the tool, what happens to unspecified fields, and where to find the full settings catalog. The main remaining gap is the absence of any permission/error context for an un-annotated mutation 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 0%, so the description must compensate, and it largely does: it identifies device_id as the device ID and explains settings as a changeable-settings object with a concrete nested example {"thermostat_mode_temps": {"comfort": 21}} plus a pointer to the API's device-parameters section. It doesn't enumerate the full settings catalog, but it adds real meaning beyond the bare 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?

The opening sentence states a specific verb (Изменить) and resource (настройки устройства ZONT), and the examples (thermostat mode, target temperatures, trusted numbers) make the scope concrete. It does not explicitly distinguish itself from siblings like zont_set_io_port or zont_send_custom_command, 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 gives useful invocation guidance — pass only the fields to change and the rest keep prior values — which implicitly tells the agent this is a partial-update tool, not a full overwrite. However, it never says when to choose this tool over alternatives such as zont_send_custom_command, so selection guidance remains 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.