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

The description adds the important behavioral note that the device must be restarted after configuration change, which supplements the annotations (destructiveHint=true, readOnlyHint=false). No contradiction with annotations is apparent.

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 concise sentences deliver all necessary information without extraneous text. The structure is clear: purpose, mode instructions, and post-configuration behavior.

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

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

Given the tool's complexity (6 parameters, output schema exists, annotations provided), the description is sufficient for an agent to understand the core functionality. Minor gap: missing explanation of the 'device' parameter, but overall adequate.

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

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

With 0% schema description coverage, the description adds meaning for 5 of 6 parameters by explaining the DHCP/static IP modes and which parameters belong to each. However, it does not explain the 'device' parameter, and it omits format details for IP addresses.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it configures network settings and explains the two modes (DHCP vs static IP). It is distinct from sibling tools like set_brightness or restart_device, though it could more explicitly mention it targets a 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?

No guidance is provided on when to use this tool versus alternatives, or when to choose DHCP versus static IP. The description only mentions parameter options without contextual usage advice.

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=true and destructiveHint=false. Description adds that the tool exports as CSV/Excel and explains selection logic and time ranges. However, it omits behavioral details like the max_points cap on data points and does not describe what the response contains (e.g., file path or download). For a read tool, the description provides adequate but not comprehensive transparency.

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?

Description is well-structured with clear sections (Selector, OUTPUT FORMAT, REQUIRED, TIME RANGE). Information is front-loaded in the first sentence. Every line serves a purpose without verbosity. Efficient and easy to parse.

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

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

Given 10 parameters, no output schema, and annotations only providing readOnlyHint, the description should cover return values and all constraints. It does not describe the output response type (e.g., file URL or binary), nor the max_points parameter behavior. Date format expectations are not specified. Sufficient for basic use but leaves gaps for advanced usage.

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%; description compensates by explaining 8 of 10 parameters: sensor, device, location, group, output_format, last_hours, from_datetime, to_datetime, timezone_name. It adds valuable context like mutual exclusivity of selectors and default export scope. However, max_points is not mentioned, leaving a gap in parameter understanding.

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?

Description starts with 'Export historical air-Q sensor data as CSV or Excel', which is a specific verb+resource. It distinguishes from sibling tools like get_air_quality_history (retrieve) and plot_air_quality_history (visualize) by focusing on file export. The purpose 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?

Description explains selectors (device, location, group) and when each applies, and states default behavior when none is specified. However, it does not explicitly contrast with sibling tools or provide 'when not to use' guidance. Alternatives like get_air_quality_history or plot_air_quality_history are not mentioned.

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 indicate readOnlyHint=true and destructiveHint=false. The description adds behavioral details: when using location/group, each device gets its own entry; the response includes a _sensor_guide field with documentation; and the option for averaged vs instantaneous readings. This goes beyond the annotations.

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

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

The description is concise and well-structured: the first sentence states the purpose, followed by a clear bullet-like list of query modes, then a sentence on response structure and a recommendation. Every sentence adds value without redundancy.

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

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

Given that an output schema exists, the description does not need to detail return values. It mentions that the response contains sensor names mapped to values and includes a _sensor_guide field. It covers the three main parameters and return_average, but misses two supplementary parameters. Overall, it is mostly complete for a 6-parameter tool with 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 coverage is 0% (no parameter descriptions), so the description must compensate. It explains the three mutually exclusive parameters (device, location, group) and return_average, but does not explain clip_negative or include_uncertainties. Thus, not all parameters are fully documented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool gets current air quality sensor readings from one or more devices. It distinguishes itself from siblings like get_air_quality_history (historical) and list_devices (device listing) by specifying the real-time nature and the options for single device, location, or group queries.

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 says to specify exactly one of 'device', 'location', or 'group', with examples for each. It recommends using return_average=True. However, it does not explicitly state when to use this tool over alternatives like get_air_quality_history or export_air_quality_history, though the sibling context provides some distinction.

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?

Goes beyond readOnlyHint and destructiveHint annotations: describes response size implications, sensors format (must be JSON array), timezone handling, response structure (timestamp, datetime, quality columns). No contradiction with annotations.

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

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

Well-structured with sections and bullet points; every sentence adds value. Slightly verbose but appropriate for the complexity of the tool.

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

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

Given 7 parameters (0 required) and output schema present, description covers all necessary information: parameter semantics, response format, and important caveats. No gaps for agent to select and invoke 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?

With 0% schema coverage, description fully explains all 7 parameters: time range options, sensor filtering, max_points downsampling, device, timezone_name. Includes examples and important formatting notes for sensors parameter.

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?

Clearly states 'Get historical air quality data stored on the device's SD card.' Uses specific verb and resource, and distinguishes from siblings like get_air_quality (real-time) and export_air_quality_history.

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 detailed when-to-use guidance: warns about response size, explains time range options, and gives examples. Lacks explicit exclusion for alternatives but context is clear.

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=true and destructiveHint=false, indicating a safe read operation. The description adds context about the return including day and night values, but does not disclose additional behavioral traits such as error handling or need for device existence. With annotations, this is adequate.

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

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

The description is a single, concise sentence that clearly conveys the tool's purpose. There is no extraneous information, making it efficiently front-loaded.

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

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

While an output schema exists (so return values are covered), the description lacks details on the device parameter. Given the tool's simplicity and the presence of annotations, it is minimally complete but could better address parameter semantics.

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%, meaning the 'device' parameter lacks any description. The main description only mentions 'of a device' without explaining parameter format, allowed values, or default behavior (null). The description fails to compensate for the missing schema details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'current LED brightness configuration (day and night values) of a device'. It effectively distinguishes from sibling tools like set_brightness (write) and get_config (general config), though it does not explicitly differentiate.

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 provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or limitations. It simply states what the tool does without context for appropriate usage.

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 indicate a safe read operation. The description adds behavioral context by noting the response includes a _config_guide field for interpreting keys, which advises a recommended workflow for agents. No contradiction with annotations.

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

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

Two sentences, front-loaded with the core purpose. Every sentence adds value without redundancy.

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

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

Given the tool's simplicity (1 optional param, read-only, output schema present), the description provides sufficient context about what it returns and how to interpret results. It covers the essential aspects for correct usage.

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 single parameter 'device' has 0% schema description coverage, yet the description does not explain its meaning, default behavior, or effect when omitted. This leaves a significant gap for the agent.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves the full configuration of a device as a JSON dict. This verb+resource combination is specific and distinguishes it from siblings that deal with individual settings or operations.

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 does not provide explicit guidance on when to use this tool versus alternatives. It implies a read-only context but omits scenarios or exclusions, such as when to use get_device_info instead.

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

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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds a list of returned metadata fields but does not disclose other behavioral traits such as default behavior when no device parameter is provided or any rate limits. It neither contradicts nor significantly enriches the annotations.

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

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

The description is a single, front-loaded sentence that efficiently conveys the tool's purpose without unnecessary words. Every part of the sentence earns its place.

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

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

Given the low complexity (one optional parameter, no required inputs, simple read operation), the description is largely adequate but misses explaining the optional device parameter. This gap reduces completeness for an AI agent reasoning about how to use the tool 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?

The schema describes one optional parameter 'device', but the description does not explain its purpose, format, or default behavior. With 0% schema description coverage, the description fails to compensate for this lack of detail, leaving the agent uncertain about how to use the parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves device metadata and lists specific fields (ID, name, model, etc.), which distinguishes it from siblings like list_devices (which lists all devices) and configure_network (which configures network settings).

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 for a single device's metadata, but does not explicitly state when to use this tool versus alternatives like list_devices. No guidance on prerequisites or exclusions is provided.

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

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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds no additional behavioral context beyond what annotations provide, such as authentication requirements or side effects. It is consistent but does not add value beyond annotations.

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

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

The description is a single, front-loaded sentence of 14 words with no redundancy. Every word contributes to understanding the tool's action and scope.

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

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

While the description clearly states the tool's purpose and a potential output exists (output schema present), it lacks essential information about the sole parameter. Without parameter documentation, the description is incomplete for correct usage.

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

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

Schema description coverage is 0%, and the description does not explain the 'device' parameter, its format, or its role. The agent has no guidance on how to specify the device, making the tool difficult to invoke correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get', the resource 'current LED visualization theme', and the scope 'for both sides of a device.' It distinguishes itself from sibling tools like 'get_possible_led_themes' (lists all themes) and 'set_led_theme' (changes the theme).

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 for reading the current theme, but does not explicitly state when to use this tool versus alternatives like 'get_possible_led_themes' or 'set_led_theme'. No exclusions or prerequisites are mentioned.

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=true and destructiveHint=false, so safety is clear. Description adds minimal context about log entries; could mention what kind of logs or scope.

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?

Very concise (5 words) but under-specified. Lacks necessary details for effective tool use.

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

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

Given the presence of an output schema and many siblings, the description is too minimal. Does not cover log content, filtering, or how device parameter works.

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?

Parameter 'device' has 0% schema coverage. Description only implies device selection via 'from a device', but does not explain meaning, accepted values, or default behavior (null means all devices?).

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?

Description clearly states verb and resource (get log entries from device), but does not differentiate from sibling getters like get_config or get_device_info.

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?

No guidance on when to use this tool versus alternatives. Among many sibling getters, no context is provided for selection.

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

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description adds no further behavioral context beyond stating the verb 'Get'.

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

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

The description is a single sentence that is concise and front-loaded, with no extraneous 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?

Given the parameter semantics gap and low complexity, the description is partially complete but fails to clarify the parameter's role, relying on the output schema for 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%, and the description only mentions 'of a device' without specifying what device refers to (ID, name, etc.), leaving the meaning of the parameter unclear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool gets the night mode configuration of a device, which distinguishes it from set_night_mode and other getter tools like get_brightness_config.

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?

No explicit guidance on when to use this tool versus alternatives like get_config. The context is implied but lacks exclusions or prerequisites.

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 declare readOnlyHint=true and destructiveHint=false, so the description's 'list' action is consistent. However, the description does not add behavioral context beyond what annotations already provide, such as whether the device must be connected or the response format. It is adequate but not enhanced.

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

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

The description is a single sentence that is front-loaded and concise. Every word is necessary—no fluff or redundancy.

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

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

Given the tool's simplicity (one optional parameter, read-only, output schema exists), the description covers the primary purpose. However, it could be improved by noting the parameter's optionality and default behavior, but this is partly in the schema. Still, it is mostly complete for the task.

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 input schema has 1 parameter ('device') with 0% description coverage. The description does not explain the parameter's meaning, usage, or default behavior. Despite the parameter being optional, the absence of any elaboration fails to compensate for the low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool 'list all available LED visualization themes for a device.' It uses a specific verb ('list') and resource ('available LED visualization themes'), distinguishing it from siblings like 'get_led_theme' (current theme) and 'set_led_theme' (set theme).

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 for viewing available themes, but does not explicitly state when to use it versus alternatives (e.g., 'get_led_theme' for current theme) or provide context for when not to use it. The purpose is clear but lacks direct 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?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that the tool makes the device blink LEDs, which is a temporary visual effect, not a state change. This aligns with annotations, but there is no disclosure of any side effects or required permissions, limiting transparency.

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 concise sentences, front-loaded with the purpose. Every sentence adds value without redundancy. Ideal length for a simple tool.

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

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

The tool is simple with one optional parameter and an output schema (not shown). The description covers the core function and return value. However, it lacks details on parameter behavior and use cases, making it slightly incomplete for a fully autonomous agent.

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 input schema has one parameter 'device' with no enum or description. The description does not explain what the parameter does, allowed values, or behavior when null. With 0% schema description coverage, the tool is missing crucial parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action: make a device blink LEDs in rainbow colors for visual identification. The verb 'identify' and resource 'device' are specific. However, it does not explicitly distinguish from sibling tools like list_devices or get_device_info, but the unique visual function sets it apart.

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?

No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, limitations, or scenarios where this is appropriate, leaving the agent without decision support.

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=true and destructiveHint=false, so safety is clear. The description adds what the output includes but does not disclose additional behavioral traits such as pagination, sorting, or rate limits. Given the low complexity, this is adequate but minimal beyond annotations.

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

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

The description is a single, front-loaded sentence that efficiently conveys the tool's action and output. Every word serves a purpose; no 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 zero parameters and an output schema existing, the description sufficiently lists what information is returned. No additional context is needed for a straightforward list operation.

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 are zero parameters, so no parameter documentation is needed. Per rubric, '0 params = baseline 4'. The description does not attempt to explain nonexistent parameters, which 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 explicitly states the verb 'List' and the resource 'all configured air-Q devices', and lists the returned fields (names, addresses, locations, groups). This clearly differentiates it from siblings like 'get_device_info' which likely targets a single 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?

The description implies use for retrieving all devices but does not explicitly state when to use this tool versus alternatives like 'get_device_info' for a specific device, or provide exclusions. With zero parameters, usage is straightforward, but no guidance is 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?

Annotations already declare readOnlyHint=true and destructiveHint=false. Description adds value by detailing output formats (png, webp, svg, html), time range handling, and timezone behavior. It doesn't contradict annotations and provides transparency beyond structured fields.

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?

Description is well-structured with clear sections (purpose, when to use, selector, output format, required, time range). Every sentence adds value; no redundancy or fluff. Concise yet comprehensive.

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

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

Given 15 parameters, 1 required, no output schema, the description covers essential aspects: data selection, required sensor, time range, output formats, and timezone handling. It lacks clarity on combining multiple selectors and details on chart_type/dark mode, but overall provides sufficient context for an AI agent.

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%, but the description compensates by explaining critical parameters: sensor, device/location/group selectors, time range (last_hours, from/to_datetime), output_format, and timezone_name. It misses some parameters like title, axis titles, chart_type, dark, max_points, but covers the most important ones.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Generate a chart of historical air-Q sensor data' with a specific verb (Generate) and resource (historical air-Q sensor data). It distinguishes from sibling tools like get_air_quality_history which likely returns raw data, not a chart.

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?

Description has a 'WHEN TO USE THIS TOOL' section explicitly stating to call it when user asks for a graph, chart, plot, or visual representation. It explains selector logic (device, location, group) and output format options. Lacks explicit when-not-to-use, but context implies alternatives.

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?

Adds the behavioral detail that the device will be unreachable for about 30 seconds, which goes beyond the annotations' destructive hint.

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 sentences with no filler; every word adds value.

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

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

Provides essential behavioral context but omits prerequisites, concurrent operations, or return value; adequate for a simple 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?

The description does not explain the 'device' parameter at all, despite 0% schema coverage, leaving the agent unsure of its meaning.

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?

Clearly states the action 'Restart a device' and a key consequence. However, it does not distinguish from sibling 'shutdown_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?

No guidance on when to use or when not to use, nor any mention of alternatives.

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 idempotentHint=true, readOnlyHint=false, destructiveHint=false. The description adds parameter context (default range, optional night) but does not disclose additional behavioral traits like side effects or permissions.

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 extremely concise at two sentences, front-loaded with the core action. Every sentence adds value without redundancy.

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

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

The tool is simple with 3 parameters and an output schema. However, the description omits explanation for the 'device' parameter and does not discuss value bounds or error cases, leaving some gaps for complete understanding.

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

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

With 0% schema coverage, the description partially compensates by explaining 'default' (0-100%) and 'night' (optional night brightness) but ignores the 'device' parameter. This leaves ambiguity for the device field.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Set LED brightness' with a specific verb and resource. It distinguishes from sibling tools like get_brightness_config by indicating a write operation. The mention of 'default' and 'night' aligns with input parameters.

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 use for setting brightness but provides no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives or prerequisites, which is adequate for a simple setter but lacks clarity on context.

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

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

Annotations already indicate idempotency and non-destructiveness. The description adds the display effect but omits behavior for unspecified optional device parameter or return 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?

Two concise sentences, front-loaded with the primary purpose. No superfluous 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?

For a simple rename tool with output schema (not shown) and sibling tools, the description provides basic intent but lacks detail on return values, error scenarios, or behavior when device parameter is null.

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

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

With 0% schema description coverage, the description does not elaborate on the 'name' or 'device' parameters, leaving the agent to infer constraints or expected formats from context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool renames a device and adds the effect on the display. However, it does not distinguish this from other device configuration tools like set_brightness or set_led_theme.

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?

No guidance on when to use this tool versus alternatives (e.g., identify_device or list_devices). Missing prerequisites or exclusion criteria.

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

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

Annotations already indicate idempotentHint=true, so the description adds value by listing common theme values and noting that themes are named. It aligns with annotations (readOnlyHint=false, destructiveHint=false) and does not contradict them.

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 concise sentences with no redundant information. The first sentence states purpose, the second adds helpful examples and a pointer to another tool. Every sentence earns its place.

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

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

Covers the main purpose and provides theme examples. Output schema exists, so return values need not be described. However, it does not clarify behavior when both parameters are null or the effect of setting only one side. Still, it is mostly complete for a simple setter.

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 parameter descriptions are absent (0% coverage). The description partially compensates by mentioning 'one or both sides' and listing example theme names, but does not explicitly describe each parameter (left, right, device) or their allowed 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?

The description clearly states the verb 'set' and the resource 'LED visualization theme', specifying the scope 'for one or both sides of the device'. It effectively distinguishes from sibling tools like get_led_theme (get vs set) and other set 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?

Provides explicit examples of common themes and directs users to get_possible_led_themes for a complete list. This gives clear context on how to use the tool, though it does not explicitly state when not to use it.

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?

The description adds behavioral context beyond annotations, explaining actions like wifi_night_off caching data and alarm_night_off still allowing fire/gas triggers. Annotations are minimal, so the description effectively fills gaps.

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 concise, front-loaded with purpose, and uses efficient bullet-point-like structure. Every sentence adds value without redundancy.

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

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

Given 9 parameters and a required field, the description covers all parameters with sufficient detail, including edge cases (fire/gas still trigger). The presence of an output schema further reduces the need to explain returns.

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

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

With 0% schema description coverage, the description fully explains each parameter (e.g., brightness percentages, boolean flags with side effects), adding critical meaning beyond names and types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Configure night mode' and provides specific details about time format and parameter effects, distinguishing it from siblings like get_night_mode.

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 lacks explicit guidance on when to use this tool versus alternatives, such as when to use get_night_mode for reading or set_brightness for brightness only. The context is implied but not directive.

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

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

Annotations already indicate destructiveHint=true. The description adds critical context: the device must be manually powered on after shutdown. This is valuable behavioral information beyond what annotations provide, and there is no contradiction.

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

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

Two sentences with zero waste. Every word serves a purpose, and the description is front-loaded with the core action.

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

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

The tool is simple, and the description covers the main function and a key behavioral note. However, lack of parameter documentation leaves a gap in completeness. An output schema exists, so return values need not be explained.

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

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

With 0% schema description coverage, the description should compensate but does not explain the 'device' parameter at all. It merely repeats the parameter name without adding meaning about format, defaults, or allowed values. Users cannot infer how to specify the device.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Shut down a device') and distinguishes it from sibling tools like restart_device by noting it must be manually powered on again. It is specific and 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 description includes 'Only use if explicitly requested,' which provides strong guidance on when to use this tool. However, it does not explicitly compare to restart_device or other alternatives, missing an opportunity for even clearer differentiation.

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