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

With no annotations, the description carries the full burden of behavioral disclosure. It adds minimal value by indicating recency and pagination, but does not explain ordering, the scope of 'activities', what data is returned, or any side effects. This is insufficient for a tool with no annotation support.

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 and is efficiently front-loaded with the core action. The parenthetical pagination note is compact, though slightly cryptic. No unnecessary words are present.

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?

Even though an output schema exists, the description is not complete enough for an agent to correctly choose this tool among many sibling activity-related tools. It lacks a definition of 'activities', any usage conditions, and clarification on how it differs from get_fitness_activities or get_activity_detail.

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

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

Schema description coverage is 0%, so the description must compensate for the undocumented limit and start parameters. It does identify them as pagination controls, which adds some meaning beyond the bare schema, but it does not explain how start is used as an offset or what the default behavior implies.

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 lists recent activities and mentions pagination, which defines a specific verb and resource. However, it does not distinguish 'activities' from siblings like get_fitness_activities or get_activity_detail, so the meaning of 'activities' remains ambiguous.

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 given about when to use this tool instead of similar tools such as get_fitness_activities or get_daily_summary. The description only states what the tool does, not when it is appropriate or inappropriate to call 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?

No annotations are provided, so the description carries the full behavioral disclosure burden. It only says 'Details' without explaining whether this is a safe read operation, what the response contains, what happens for invalid IDs, or any authentication requirements.

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 one short sentence with no filler and the key identifier is front-loaded. It is concise, but the brevity comes at the expense of needed context.

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

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

With no output schema, no annotations, and a large sibling set, this description is too thin. An agent cannot tell what 'details' means, how this tool relates to get_activities or get_activity_map, or whether a single activity_id is sufficient.

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

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

The schema has 0% description coverage for activity_id, and the description only repeats the parameter name in parentheses. It does not explain what an activity is, where a valid activity_id comes from, or any constraints beyond the schema's integer type.

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 returns details for a single activity identified by activity_id, which distinguishes it from plural list tools like get_activities. However, it does not explicitly address siblings like get_activity_map, and it lacks a direct verb such as 'returns'.

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 about when to use this tool versus alternatives such as get_activities, get_fitness_activities, or get_activity_map. There is no mention of prerequisites like obtaining an activity_id from a prior list call.

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 must bear the full burden of behavioral disclosure, but it only states that map data is returned. It does not describe the return format (e.g., coordinates, polyline, URL), potential error conditions, or behavior when an activity has no GPS track. This leaves significant unknown behavioral aspects.

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, well-structured sentence with no filler and the core function front-loaded. It is appropriately concise for a simple one-parameter tool, though it could include a bit more detail without significant length. The structure itself is effective.

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 absence of an output schema, the description should explain what the 'map data' actually contains, such as a sequence of GPS points or a polyline. It also does not note dependencies like the activity requiring GPS recording. While the input is simple, the return value is underspecified, leaving an agent guessing about the response structure.

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 repeats 'activity_id' without explaining how to obtain or validate it. It adds minimal meaning beyond the parameter name and integer type. The description could have mentioned that the ID comes from get_activities or similar, but it does not.

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

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

The description clearly identifies the tool as returning map/GPS track data for a specific activity, using the activity_id parameter. It is specific about the resource (activity map/GPS track) and distinguishable from siblings like get_activity_detail or get_activities. However, it does not explicitly contrast itself with those siblings, so it falls 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?

No guidance is provided on when to use this tool versus alternatives such as get_activity_detail or get_fitness_activities. There is no mention of prerequisites, such as the activity needing recorded GPS data, or when this tool would be inappropriate. The agent must infer usage from the description alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state whether the response includes systolic/diastolic values and units, what happens when no data exists for the requested day, or what the null/default day means. The ambiguity around the optional day parameter is a meaningful gap.

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 with no filler. It communicates the resource, the time scope, and the date format in very few words, which is appropriate for a simple daily-data getter.

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 no output schema, and the description provides the core context an agent needs to make a normal call. However, it is not fully complete because it omits null-day behavior, response shape, and missing-data behavior, and there are no annotations to fill those gaps.

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 provides zero description for the 'day' property, so the description must compensate. It adds the useful date format YYYY-MM-DD and clarifies that the parameter refers to a calendar day, which helps, but it does not explain the null default or what range of dates is valid.

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

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

The description clearly identifies a blood pressure reading for a specific day and includes the date format, so an agent can tell what resource is being accessed. It is distinguishable from the sibling tools because no other sibling covers blood pressure, though it lacks an explicit action verb such as 'Retrieves'.

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 intended use is implied: call this tool when you need a blood pressure reading for a specific date. However, there is no explicit guidance about when not to use it, no mention of alternatives, and no explanation of what happens if the optional day parameter is omitted or null.

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?

There are no annotations, so the description carries the behavioral burden. The wording 'readings for a day' suggests a read-only lookup and the date format is useful, but it does not disclose what happens when the optional day parameter is null, timezone assumptions, or limitations. For a simple getter this is minimally acceptable but not richly transparent.

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?

A single sentence with zero redundancy: it states the resource, the scope, and the date format. The key information is front-loaded and every word 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 single-parameter read tool with an output schema present, the description covers the essential call contract—what to request and the date format. The main omissions, null default behavior and sibling selection guidance, are modest given the tool's low complexity.

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 offers only a title and null default, while the description adds the crucial YYYY-MM-DD format—valuable since schema description coverage is 0%. However, it does not clarify the meaning of the null default or the expected result when day is omitted, leaving a partial but non-trivial contribution.

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

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

The description clearly identifies the resource (Body Battery readings) and the temporal scope (a single day), with an explicit date format. It does not explicitly contrast with sibling tools such as get_body_battery_stress, but the target resource is distinct enough that an agent can infer what the tool returns.

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 a single-day use case but provides no guidance on when to prefer this tool over get_body_battery_stress or get_body_battery_stress_history, and no exclusions or context are given. With many sibling tools, the omission of any selection criteria is a notable gap.

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 present, so the description carries the full burden. It only states the day scope and that it is a summary; it does not disclose default/null-day behavior, timezone handling, read-only nature, or data availability.

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 compact sentence with no filler. The core metric and date format are front-loaded, making it 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?

With no annotations and no output schema, the description is too thin for an agent to confidently invoke the tool. It covers purpose and date format but omits the meaning of the optional/nullable day parameter and when to prefer this tool over closely related 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?

The description adds the YYYY-MM-DD format for the day parameter, which the input schema lacks. However, it does not explain what null or omitted day means, leaving a meaningful ambiguity given the schema's default of null.

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

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

The description clearly identifies the resource (Body Battery + stress) and the scope (a single day, formatted YYYY-MM-DD). The combined metric differentiates it from siblings like get_daily_stress and get_body_battery, though it lacks an explicit verb such as 'Get'.

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 a daily summary use case but gives no explicit guidance on when to select this tool over get_body_battery, get_daily_stress, or get_body_battery_stress_history. No alternatives or exclusions 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?

There are no annotations, so the description carries the behavioral burden. It does disclose that the tool returns combined Body Battery and stress history over a date range, which is meaningful. However, it does not mention default behavior when end is null, timezone handling, or the read-only nature explicitly, though the tool name and 'history' strongly imply a safe read.

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 compact sentence with no filler. It front-loads the resource and action, and the parenthetical 'up to end' directly connects to the end parameter. Slightly terse, but appropriately sized for this 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?

With an output schema present and only two optional parameters, the description covers the core operation and gives some meaning to both parameters. It is incomplete in terms of sibling differentiation and default behavior, but for a simple history-read tool it is 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?

Schema description coverage is 0%, so the description must compensate. It does partially: 'last N days' maps to days, and 'up to end' maps to end, giving the parameters semantic meaning beyond the schema. However, it does not explain the expected string format for end, whether end is inclusive, or what null means in practice.

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 resource (Body Battery + stress), the action (history retrieval), and the time scope (last N days up to end). It is distinguishable from siblings like get_daily_stress by the 'history' framing, though it does not explicitly contrast with get_body_battery_stress.

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 is given about when to use this tool versus alternatives such as get_body_battery_stress, get_daily_stress, or get_weekly_stress. The phrase 'for the last N days' implies historical usage, but no direct routing or exclusion guidance 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?

With no annotations, the description carries the full burden of behavioral disclosure. It does not explicitly state that this is a read-only operation, nor does it explain what happens when 'day' is omitted or null, what timezone applies, or how missing data is represented. The listed metrics provide some context but not sufficient behavioral detail.

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 with no filler. It efficiently conveys the core resource and a few key output metrics. It could be slightly clearer with an explicit verb, but it is appropriately concise for a simple getter.

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

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

There is no output schema and no annotations, so the description should provide a fuller picture. It partially describes the return values (grams, BMI, body fat) but leaves 'etc.' undefined and fails to clarify behavior when 'day' is absent. For a tool with a single optional parameter, this is a notable gap that could lead an agent to call it incorrectly.

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 provides no descriptions, so the description must compensate. It does add the crucial YYYY-MM-DD format for the 'day' parameter, which is meaningful. However, it does not explain the semantics of the default null value or whether omitting the parameter returns the latest available weight, leaving part of the parameter's meaning undocumented.

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 identifies the resource (body weight) and scope (a single day with YYYY-MM-DD format), and lists key returned data (grams, BMI, body fat). While it lacks an explicit verb like 'Gets', the tool name and context make the action clear, and the single-day scope distinguishes it from the sibling get_weight_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?

No guidance is provided on when to use this tool versus alternatives such as get_weight_history or get_weight_goal. The 'for a day' phrasing implies single-day usage, but there is no explicit when/when-not statement or mention of the alternatives, leaving the agent to infer the routing.

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

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

With no annotations, the description carries the burden. 'List' clearly implies a read-only operation, but the description does not disclose any additional behavior such as whether only currently paired devices are returned or whether ordering is meaningful. This is adequate but minimal for a simple list 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?

One short, front-loaded sentence with no filler. Every word contributes meaning: 'List', 'all', 'connected', and 'Garmin devices'.

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

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

For a zero-parameter list tool with an output schema, the description is nearly complete. The only real gap is the exact meaning of 'connected' and how this relates to get_device_info, but that is minor given the trivial call signature.

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

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

The tool has zero parameters, so parameter documentation is inherently unnecessary. The description's phrase 'all connected Garmin devices' communicates the implicit scope of the operation.

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

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

The description states a specific resource ('all connected Garmin devices') and a clear list/retrieve action. The plural 'devices' and qualifier 'connected' help differentiate it from singular or profile-oriented sibling tools like 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?

There is no guidance on when to use this tool versus get_device_info or other sibling tools. It does not mention whether this is a prerequisite for device-specific calls or how 'connected' is scoped.

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 burden of behavioral disclosure. It discloses the returned fields (max, min, resting) but does not mention what happens when the optional 'day' parameter is null, whether the data is read-only, or how missing data is handled.

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 compact sentence with no filler or redundancy. It front-loads the most important details: date format and the returned metrics.

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?

This is a simple one-parameter read tool, and the description covers the resource and expected output fields. However, it leaves the default null behavior ambiguous and does not guide selection among the many heart-rate siblings, so an agent may not fully understand invocation edge cases.

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

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

The schema has 0% description coverage, and the description adds the important YYYY-MM-DD format for the 'day' parameter. However, it does not explain the meaning of the default null value or what day is used when the parameter is omitted.

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

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

The description clearly identifies the resource (daily heart rate) and the returned metrics (max, min, resting), and includes the expected date format. It relies on the tool name for the verb 'get' but still distinguishes this from siblings like get_resting_heart_rate by listing all three values.

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 about when to choose this tool over alternatives such as get_resting_heart_rate or get_hrv. The description only restates the tool's purpose and offers no exclusions or 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?

No annotations are provided, so the description must cover behavioral implications. It does disclose that the response includes the daily goal, which is somewhat useful, but it does not explain units, timezone handling, the meaning of null day, or whether this is a safe read-only call. This leaves meaningful uncertainty for an agent.

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 compact sentence with no filler. It front-loads the core concept ('fluid intake') and adds only the essential scoping detail about date format.

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 one-parameter getter, the description conveys the main return content and the expected argument format. Yet with no output schema and no annotations, it leaves gaps around default behavior, units, and exact response structure, making it adequate but not fully complete.

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

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

Schema coverage is 0%, so the description must compensate. It adds the expected format (YYYY-MM-DD) and ties the parameter to a single day, which is helpful. However, it does not explain the behavior when day is null or omitted, even though the schema marks the parameter as optional with a null default.

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

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

The description clearly identifies the resource as daily fluid intake and specifies that it includes the daily goal, scoped to a single day with YYYY-MM-DD format. This distinguishes it from the sibling get_hydration_history, though the description does not explicitly name or contrast that alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'for a day (YYYY-MM-DD)' implies this tool is for retrieving a single day's hydration data rather than a history or range. However, it provides no explicit guidance about when to prefer this over get_hydration_history or what happens when the optional day parameter is omitted.

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 of behavioral disclosure. It does disclose the lookup window ('period=1, up to end') and expected date format (YYYY-MM-DD), which adds meaningful context. It stops short of addressing edge cases like null end, data availability, or timezone handling.

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 compact sentence with the most important information ('step count') front-loaded. The parenthetical packs the necessary qualifiers without any wasted 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?

For a one-optional-parameter read tool with an output schema, the description is nearly sufficient: it states the resource, the period, and the date format. The main gaps are the ambiguity of 'last day' and the absence of a statement about the behavior when 'end' 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?

Schema coverage is 0%, but the description partially compensates by indicating that 'end' is a date in YYYY-MM-DD format and that the result runs 'up to' that date. It does not explain what a null end means or clarify the 'period=1' notion, since no period parameter appears in the input 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 specifies a concrete resource ('step count') and a temporal scope ('last day', period=1), which clearly differentiates it from weekly step tools at a glance. However, it does not explicitly name or contrast any sibling tool, so it falls short of full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no indication of when to choose this tool over alternatives such as get_weekly_steps or get_daily_summary. There is no explicit use case, prerequisite, or exclusion, leaving the agent to infer from the name and 'period=1' rather than from concrete 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 provided, the description carries the burden. It discloses the basic behavior: a historical stress lookup bounded by N days and an end date format. However, it does not mention how missing/null end is handled, whether the day count is inclusive, or any quirks around data availability.

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 compact sentence with no filler. It front-loads the core purpose and packs the two parameter semantics into a short parenthetical. Every element 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 simple read-only history tool with an output schema, the description covers the main call pattern. However, it does not position this tool relative to siblings like get_weekly_stress or get_body_battery_stress_history, which matters given the large sibling list. Output schema covers return shape, so that omission is less critical.

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 maps 'N days' to the days parameter and 'up to end, YYYY-MM-DD' to the end parameter, adding practical meaning beyond the bare schema. It stops short of explaining the default/null behavior fully, but it is still helpful.

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

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

The description clearly identifies the resource ('stress history') and the time scope ('last N days'), and the phrase 'period=days' reinforces that this is the daily variant. It is distinguishable from get_weekly_stress, though it does not explicitly contrast with other stress-related siblings like get_body_battery_stress_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?

The description gives no explicit guidance on when to choose this tool over alternatives. It does not mention get_weekly_stress or other stress/history endpoints, nor does it state exclusions or conditions. The intended usage is only implied by the name and 'period=days'.

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 at all, the description carries the full burden of behavioral disclosure. It reveals only the output fields, not whether this is a safe read-only operation, how missing or null day values are handled, timezone assumptions, or any failure behavior. For a health-data retrieval tool this missing context is notable.

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?

One compact sentence delivers the core purpose, the date format, and the main output contents with no wasted words. The most important information is placed first and the structure is easily scannable.

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 very simple one-parameter tool, the description names the resource, the parameter format, and key output fields. But with no output schema and no annotations, it should also clarify the optional/null-day behavior and perhaps the units or structure of the returned summary to be fully complete.

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

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

Schema description coverage is 0%, so the description must compensate for the lone optional day parameter. It does add the expected YYYY-MM-DD format, which is genuinely useful. However, it does not explain that day is optional, what happens when it is null, or what range of dates is valid.

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

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

The description clearly identifies the resource (daily summary), the date scope, and the three data fields included: steps, calories, and heart rate. It is specific enough to distinguish this aggregate tool from the many sibling per-metric tools like get_daily_steps and get_daily_heart_rate, though it lacks an explicit verb like 'retrieves'.

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 when-to-use or when-not-to-use guidance is provided. The description does not contrast this with get_daily_summary_history or the individual metric tools, leaving the agent to infer which sibling is appropriate for a given need. The only implicit context is that it is for a single day.

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 burden of explaining behavior. It discloses the core behavior: returning daily summary history over a trailing window of N days ending at a specified date. However, it does not clarify edge cases such as whether the end date is inclusive, what happens when end is null, or if there is a maximum N, leaving some behavioral ambiguity.

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 entire description is one efficient sentence that front-loads the core purpose and includes the key date format detail. There is no filler or repetition, and it is appropriately sized for a simple read-only history 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 has an output schema and only two optional, self-explanatory parameters with defaults, so the description is nearly sufficient. However, it lacks explicit guidance on how to choose this over get_daily_summary and does not specify the exact semantics of 'up to end', leaving some room for misreading the range inclusiveness.

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 maps 'N days' to the days parameter and gives the end parameter's expected format as YYYY-MM-DD, which is useful. However, it does not elaborate on the meaning or constraints of either parameter beyond what their names already suggest.

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

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

The description clearly identifies the resource as 'daily summary history' and scopes it to 'the last N days (up to end, YYYY-MM-DD)', which distinguishes it from the singular get_daily_summary. It lacks an explicit verb like 'retrieves' or 'returns', but the meaning is unambiguous for an agent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'for the last N days (up to end, YYYY-MM-DD)' implies this is used for historical daily summary data, but it never explicitly states when to use this tool versus get_daily_summary or other history tools. No alternatives or exclusions are named, so usage guidance is only implied.

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

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

No annotations are provided, so the description carries the burden. It reveals that the tool returns the active device's type, name, and battery level, and the 'get' prefix implies a non-mutating read. However, it does not disclose behavior when no active device exists, possible null returns, or whether battery level is a percentage.

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 with no filler. The resource and key output fields are front-loaded, and every word contributes meaning.

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

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

For a zero-parameter read-only tool, the description gives the essential information: what it operates on and what it returns. It could be slightly more complete by noting edge cases like no active device or exact battery format, but it is adequate for basic invocation.

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

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

The tool has zero parameters, and the schema reflects this with an empty properties object. In the absence of inputs, the description does not need to explain parameter semantics, making the baseline 4 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 clearly states the tool returns information about the active Garmin device, specifying the fields type, name, and battery level. It is distinct from most siblings like get_body_weight or get_sleep, though it does not explicitly contrast with get_connected_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?

There is no guidance on when to use this tool versus alternatives such as get_connected_devices or get_user_profile. The description implies a device-information use case but provides no exclusions or decision 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?

No annotations are provided, so the description carries the full burden of revealing behavior. It adds a time-window hint but does not disclose whether results are daily aggregates, what 'up to end' means when end is null, or whether workout activities are excluded from 'fitness activities'.

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 with no filler; the parentheticals and trailing 'up to end' add useful signal without bloat. Slightly terse, but every word 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?

The output schema covers return shape, so that is not a gap. However, with no annotations and many overlapping sibling tools, the description lacks usage-selection cues and sufficient parameter semantics to make fully informed invocation decisions. It is minimally adequate but incomplete.

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 relates 'days' to 'N' and 'end' to the endpoint, but does not explain accepted date formats, null semantics, the default behavior, or the parameter relationship, leaving key semantics under-specified.

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 the resource ('fitness activities'), the specific data covered ('steps/calories'), and the time window ('last N days'), making the core purpose clear. It does not explicitly differentiate it from sibling tools like get_activities or get_daily_steps, but the parenthetical disambiguates the metric type.

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 use this tool versus alternatives, no exclusions, and no mention of how it differs from get_daily_steps, get_weekly_steps, or get_activities. Given the large sibling list, the agent is left to infer usage 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?

With no annotations, the description carries the burden of explaining behavior. It does disclose the scope (one day) and the contained metrics, but it does not state what happens when the optional day is null, whether the numbers have units, or how the response is shaped. The core read behavior is clear, but edge behavior is left implicit.

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?

A single, well-structured sentence with no filler. The resource, scope, and returned metrics are front-loaded in a way an agent can parse quickly.

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 one-parameter read tool, the description covers the main purpose and output fields, but it lacks a statement about the null default, lacks units, and gives no differentiation from overlapping sibling tools. The absence of annotations and output schema raises the burden, so the description is only minimally 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?

Schema coverage is 0%, so the description must compensate. It adds the critical YYYY-MM-DD format for day, which the schema does not specify. However, it never explains that the parameter is optional/defaults to null, nor what null means, leaving part of the parameter semantics undocumented.

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

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

The description names a specific verb-resource pair (get Garmin fitness scores) and scopes it to a single day. It enumerates the returned metrics (Vo2Max, Endurance, Power), which distinguishes it from the many sibling health/training getters that do not mention these fields.

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 choose this tool over alternatives such as get_training_status_daily or get_daily_summary. The only implied usage context is the date parameter, which is common to nearly all sibling tools, so it does not help an agent decide.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does explain the date-range semantics ('period=days, up to end, YYYY-MM-DD'), which goes beyond the raw schema. However, it does not state that this is a read-only operation, what the response contains, or how the default end/days behave at runtime, leaving notable 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 a single front-loaded sentence that states the core purpose first and keeps all content relevant. The parenthetical is compact and information-dense, though slightly cryptic. No words are wasted, but the cryptic phrasing prevents a top score.

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 low complexity (2 optional params, output schema present), the description covers the basic purpose and some parameter meaning. However, it lacks explicit usage guidance and fully transparent parameter behavior (e.g., defaults, null end). It is minimally viable but has clear gaps for an agent needing to select and invoke it confidently.

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

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

Schema description coverage is 0%, so the description must compensate for undeclared parameters. It partially does by mapping 'days' to 'period' and 'end' to 'up to end, YYYY-MM-DD'. But the phrasing 'period=days' is ambiguous because 'period' is not a schema parameter, and it does not clarify that both parameters are optional or their default behaviors, so compensation is incomplete.

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 the resource ('HRV history') and the time scope ('last N days'), which clearly identifies what the tool returns. It is distinguishable from sibling tools like get_resting_heart_rate or get_body_battery because HRV is a specific metric. However, it does not elaborate on whether the history is daily averages, raw values, or another form, so it is not fully explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus siblings such as get_daily_heart_rate or get_body_battery. There is no mention of alternatives, exclusions, or conditions that would select this tool. The only implicit cue is the name and 'HRV history,' which is insufficient explicit 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 behavioral transparency burden. It explains that the range is expressed in days and the upper bound is an end date in YYYY-MM-DD, but it does not disclose what a null end means, whether the end date is inclusive, or the fluid units returned. These are moderate gaps for a read-only history endpoint.

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 compact sentence with no filler. Each clause carries information: the resource, the period unit, the endpoint, and the date format. It is concise without sacrificing key semantics.

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, low-complexity read tool with an output schema and only two optional parameters, the description is largely complete: the agent knows what data is returned and how to bound the query. It is not fully complete because the null/default behavior of end is left implied, but this is a minor gap.

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

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

Schema description coverage is 0%, so the description must add meaning. It does add semantics for both parameters: 'period=days' defines the days parameter as a length in days, and 'end, YYYY-MM-DD' defines the end parameter as a date-formatted upper bound. It omits default/null behavior, but the core meaning of each parameter is present.

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

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

The description clearly identifies the resource as fluid intake history and specifies the time window (last N days), which is enough to distinguish it from the sibling get_daily_hydration. It lacks an explicit 'returns' verb, but the phrase 'Fluid intake history for...' makes the purpose evident.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'history for the last N days' implies this tool is for multi-day historical queries, but it never names the alternative or states when to prefer get_daily_hydration or another sibling. There is implied context but no explicit exclusion or 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 burden of behavioral disclosure. It adds the alias relationship and date format, but it does not state read-only behavior, what the returned value represents, or how null/omitted day is handled. It partially compensates by pointing to get_training_readiness.

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?

A single sentence that front-loads the tool's purpose and alias with no filler. Every word 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 simple one-optional-parameter read tool with no output schema, the alias and date format provide enough context for selection and most invocation needs. The main missing piece is explicit null/omission behavior, but complexity is low enough that this is not a critical gap.

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

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

The description adds the YYYY-MM-DD format for the day parameter, which the schema does not specify. However, schema coverage is 0%, and the description does not clarify whether an omitted day returns null or defaults to today, leaving a gap in invocation 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 identifies this tool as an alias for get_training_readiness and scopes it to a specific day with a YYYY-MM-DD format. This distinguishes it from the many other get_* siblings and makes its purpose 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 alias statement implies interchangeable use with get_training_readiness, giving some usage context. However, there is no explicit guidance on when to prefer this tool over the canonical sibling or any conditions for use.

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 behavioral burden; it does disclose the returned data categories and the date-based scope. However, it does not explain what happens when the optional day is null/omitted, whether the tool defaults to today, or how invalid dates are handled.

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 focused sentence with no filler. The key scope ('for a day'), format, and returned content are all front-loaded in an easily parseable structure.

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

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

For a one-parameter getter this is reasonably complete, especially given the content list and date format. The main missing piece is the semantics of the optional null/default day, and with no output schema an agent still has to infer the exact response shape.

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 is the only source of meaning for the 'day' parameter. It usefully adds the YYYY-MM-DD format and the 'for a day' semantics, but it fails to explain the schema's default null value, leaving ambiguity about omitting 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 identifies a specific resource (nutrition log), a required date scope (a day, YYYY-MM-DD), and the returned content (calories, macros, meals). It is clear but does not explicitly state a verb or differentiate itself from the sibling get_nutrition_status, so it falls 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?

There is no guidance about when to use this tool versus alternatives such as get_nutrition_status, nor any mention of prerequisites, default-day behavior, or situations where another tool would be more appropriate. The intended use is only implied by the name and the day parameter.

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 bears the full burden of explaining behavior. It discloses that the tool returns current calorie goals and consumption, which is useful, but it does not state whether this is a read-only snapshot, how 'current' is determined, or what happens if nutrition data is unavailable.

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 very short and front-loaded, but the opening phrase 'Nutrition status:' is somewhat redundant with the tool name. The rest is efficient and contains 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 no-parameter read-only status tool, the description adequately covers the core return content. However, with no output schema and no annotations, it could add a bit more context about temporal scope or what 'consumption' refers to. Overall it is sufficient for a simple status query.

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

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

The tool has zero parameters, so the schema is trivially complete. Baseline 4 applies because there is no parameter complexity for the description to clarify.

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 resource (nutrition status) and the specific content returned (current calorie goals and consumption). It does not explicitly distinguish it from the sibling get_nutrition_log, but 'status' versus 'log' and the mention of goals/consumption provides enough differentiation for most agents.

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 use this tool versus its many siblings such as get_nutrition_log, get_daily_summary, or get_daily_hydration. The description gives no context about suitable scenarios, prerequisites, or exclusions, so an agent must infer usage from the name alone.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It implies reading all personal records via the word 'all', but it does not explicitly state read-only behavior, data scope, ordering, pagination, or any limitations. This is a minimal gesture toward behavior, similar to a bare 'get' semantics inferred from the name.

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 definition is extremely short, but brevity comes at the cost of substance. 'All personal records.' is a fragment that leaves out necessary context, so this is under-specification rather than disciplined conciseness.

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 has no parameters and an output schema, which reduces complexity, but the description still fails to explain what 'personal records' means, what the returned data looks like, or how this tool fits with sibling tools. An agent would struggle to confidently select this tool for a task without additional external knowledge.

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 the schema is trivially complete and there is nothing for the description to explain. The baseline of 4 for zero-parameter tools applies; the description adds no parameter detail, but none is needed.

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 'All personal records' is essentially a restatement of the tool's name, providing a noun phrase rather than a clear verb-resource statement. It names a resource ('personal records') but gives no detail about what these records are or how they differ from siblings like 'get_personal_record_types'.

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 about when to use this tool versus alternatives. No mention of prerequisites, scenarios, or exclusionary conditions relative to the many sibling tools, such as 'get_personal_record_types' or 'get_activities'.

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 of behavioral disclosure, but it only says the record types are 'available', implying a read operation. It does not state whether this is safe/read-only, what triggers an empty list, or any side effects or restrictions. Minimal behavioral signal, but not completely missing.

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 with no filler words, which is appropriate for a zero-parameter tool. However, it is structured as a fragment rather than a clear imperative sentence, slightly reducing its clarity. It earns a high score for brevity but not perfection.

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?

Despite the zero-parameter schema and output schema, the description does not explain what 'record types' means in this domain, how they relate to get_personal_records, or when an agent should call this tool. The presence of many sibling tools makes the lack of context more significant, leaving the agent to guess.

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 zero properties and required parameters, so there are no parameter semantics to explain. The baseline for zero-parameter tools is 4, and the description adds no confusing parameter information. No penalty is warranted.

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 'Available record types.' is a noun phrase with no clear verb, essentially restating the tool name without explaining what action it performs. It names the resource but does not differentiate itself from the sibling get_personal_records, which could easily be confused with it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives such as get_personal_records or how the returned types should be used. The description gives no context about prerequisites, intended workflow, or scenarios where this call is appropriate.

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 disclosure burden. It does reveal that the tool returns historical data over a time range and specifies the end-date format, but it omits details like optionality of end, default behavior, inclusivity of endpoints, or timezone handling. These are lower-stakes omissions for a read-only get tool, but still leave 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 a single compact sentence with no filler or redundant restatement of the tool name. It front-loads the resource and immediately communicates the time-window semantics, so every part 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?

The tool is simple—two optional parameters, no nesting, and an output schema—so the description covers the essential selection logic. However, the lack of explicit routing guidance matters in a large sibling family of health-metric tools, and the description does not fully compensate for the absent annotations.

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 explain the parameters, and it does: 'N' maps to days and 'end' is identified as a YYYY-MM-DD date. This adds real meaning beyond the bare schema types, though it does not explain null/default behavior.

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 identifies a specific resource ('Resting heart rate history') and a clear time-window scope ('last N days'), which helps distinguish it from sibling tools like get_daily_heart_rate and get_hrv. It lacks an explicit verb but the tool name and noun phrase convey the intended retrieval clearly.

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 a use case—retrieving resting heart rate history over a trailing window—but it does not explicitly state when to prefer this tool over related alternatives. No exclusions or alternative tool references are provided, leaving some routing inference to the agent.

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 for behavioral disclosure. It only states what data is included, but does not describe the response shape, timezone handling, behavior when no sleep data exists, or whether a null day defaults to today. These are meaningful gaps for a data-retrieval 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 a single compact sentence that leads with the resource and immediately gives the date format. Every word contributes value and there is 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?

For a one-parameter getter this is minimally viable: the agent knows the date format and the kind of data returned. However, there is no output schema, so the response shape is unclear, and the existence of sleep-related sibling tools makes the lack of distinguishing context a notable gap.

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

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

The only parameter, 'day', is explained by the description's 'YYYY-MM-DD' format, which adds meaning beyond the schema's generic string/null type. The null/default behavior is not explained, but the essential format requirement is clearly stated.

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 resource ('Sleep data for a day') and the date format, and it adds content detail by mentioning 'sleep stage time blocks.' However, it does not explicitly distinguish this from the sibling tools get_sleep_detail and get_sleep_summary, so it stops short of full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance about when to use get_sleep versus get_sleep_detail or get_sleep_summary. The description gives no context, exclusions, or alternative routing, so an agent must rely on the tool name and guesswork.

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 burden of behavioral disclosure. It makes clear this is a read-style retrieval and that it returns daily data for a specific day, but it does not address null/default behavior, timezone handling, or the exact shape of the returned sleep detail data.

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

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

The description is one short sentence with the operation, resource, and date format front-loaded. There is a minor redundancy between 'daily data' and 'for a day', but every other 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?

For a simple one-parameter read-only tool, this is minimally viable: the purpose and date format are clear, and no output schema exists to explain return values. However, the many sibling sleep tools create ambiguity, and the description does not say how get_sleep_detail differs from get_sleep or get_sleep_summary.

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 only defines 'day' as an optional string or null with no description, so 0% schema description coverage. The tool description compensates by stating the expected YYYY-MM-DD format and clarifying that the day is the target of the daily data lookup. It does not explain what null or default means, but the sole parameter is otherwise well-specified.

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 retrieves sleep details for a single day and specifies the date format. It does not differentiate itself from siblings like get_sleep or get_sleep_summary, so it loses the top score.

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 given about when to use this tool instead of alternatives such as get_sleep, get_sleep_summary, or get_daily_summary. The phrase 'daily data' implies a single-day scope, but there is no explicit or implicit routing based on the user's needs.

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 burden of behavioral disclosure. It usefully states the conditional return behavior ('sleep-related fields if available, otherwise the full dict'), but it does not clarify what happens when 'day' is null, what 'full dict' entails, or any other side-effect/authorization context.

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

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

The description is two concise sentences, front-loads the core purpose, and adds a valuable behavioral detail without wasted 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?

For a single-parameter read tool with no output schema, the description covers the basic mechanics but leaves ambiguity around a null 'day' value and the exact composition of the 'full dict'. An agent could still call it, but may not fully understand the response without additional inference.

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

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

The schema has no parameter descriptions (0% coverage), so the description must compensate. It provides the date format YYYY-MM-DD for the 'day' parameter, which is helpful. However, it omits the meaning of the default null value and does not explain how the parameter controls the summary.

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 resource (daily summary) and the behavior (returns sleep-related fields or falls back to the full dict), which distinguishes it from siblings like get_sleep_detail. It does not explicitly name alternatives, so it misses the top score.

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 about when to use this tool versus alternatives such as get_sleep, get_sleep_detail, or get_daily_summary. The only clue is the phrase 'sleep summary', but no explicit when-to-use or when-not-to-use instructions.

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 phrase 'device + user + sync status' hints that the response includes or depends on these elements, which is useful given no output schema. However, it is ambiguous—it could mean the return shape, data scoping, or freshness caveats. With no annotations, the description carries the burden but only partially fulfills it.

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 and front-loads the main purpose and date format. The trailing 'device + user + sync status' is cryptic and not clearly earned, which keeps it from a 5, but there is no fluff or repetition.

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

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

With no annotations and no output schema, the description is the only source of behavior and parameter context. It omits what null means, what the response structure is beyond vague hints, and how device/user/sync status factor into the result. An agent would likely need to probe or guess to invoke this reliably.

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 provides a 'day' parameter with zero documentation and 0% coverage, so the description must compensate. It does add the important YYYY-MM-DD format. Yet it does not explain the default null behavior or whether null means 'today', leaving a meaningful 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?

The description states a specific verb and resource: retrieving the steps goal for a given day. The YYYY-MM-DD format clarifies the scope. However, it does not explicitly contrast with sibling tools like get_daily_steps or get_weight_goal, though the word 'goal' implies a distinct resource.

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 given on when to use this tool versus alternatives. The description does not mention get_daily_steps for actual steps or get_weight_goal for a different goal type. The intended context must be inferred entirely from the tool name and sibling list.

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 present, so the description carries the full burden of behavioral disclosure. It only restates the metric and date format, without explaining what happens when day is null, what the output shape is, or whether this is purely a read 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?

The description is a single terse phrase with no filler or repetition, and the date format is front-loaded. It is appropriately concise for a simple getter, though it reads more like a label than a complete sentence.

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 single-optional-parameter read tool, the description conveys the essential metric and date format, which may be enough for basic invocation. But with no annotations and no output schema, the lack of return-value details and default-behavior information keeps it at a minimally viable level.

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 gives zero description coverage, so the description adds meaningful value by specifying the expected YYYY-MM-DD format for day. However, it does not explain the meaning of null or the default value, leaving an important part of the parameter semantics undocumented.

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 identifies the specific metric (Morning Training Readiness) and clearly scopes it to a day with a YYYY-MM-DD format. It reads as a noun phrase rather than a full verb statement, and it does not distinguish this tool from the sibling get_morning_readiness, which appears to overlap in purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use guidance, exclusions, or mention of alternatives. The only implied usage context is that this tool provides readiness for a single day, which is thin but understandable given the simple one-parameter interface.

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 of behavioral disclosure. It only states the resource and date format; it does not explain what training status data is returned, whether the operation is read-only, how null/omitted day values behave, or any error conditions. This is a significant gap for a tool with zero annotation coverage.

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 with no filler or repetition. Every word earns its place by identifying the resource and the required input format.

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 one-parameter getter with an output schema, the description is minimally adequate, especially since sibling names help disambiguate daily versus weekly versus monthly. But it omits the meaning of the optional/null day value and provides no usage context, so an agent cannot fully determine correct invocation without looking at external documentation or guessing.

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 documents a single 'day' parameter with no schema-level description, so the YYYY-MM-DD format in the description adds meaningful value. However, the description does not clarify that the parameter is optional, has a null default, or what a null value means semantically, leaving part of the parameter behavior to be inferred.

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

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

The description clearly identifies the resource as 'Training status for a day' and specifies the expected date format (YYYY-MM-DD), which distinguishes it from the weekly and monthly sibling tools. However, it lacks an explicit verb like 'get' or 'retrieve', so it is clear but not maximally precise.

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 daily usage by saying 'for a day', but it provides no explicit guidance about when to choose this over get_training_status_weekly or get_training_status_monthly. There are no stated exclusions, prerequisites, or alternative routing, so an agent must infer usage primarily from the tool name.

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

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

With no annotations, the description carries the burden of explaining behavior. It states that the tool returns training status for the last month and hints at an end-date boundary with format 'YYYY-MM-DD'. It does not disclose what happens when the optional 'end' parameter is null, or whether the month is a calendar month versus a rolling 30-day window.

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 with no filler, and the key scoping ('last month') appears first. The parenthetical 'up to end, YYYY-MM-DD' is somewhat awkward but still compact and informative.

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 one-parameter getter with an output schema available, the description covers the basic call intent and date format. It leaves two gaps: the exact meaning of 'last month' and the behavior when 'end' is omitted or null. These are notable but not severe for a low-complexity read tool.

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

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

The schema provides no description for the 'end' parameter, so the description's mention of 'YYYY-MM-DD' and 'up to end' adds meaningful format and boundary semantics. However, it does not explain the parameter's default/null behavior or whether the end date is inclusive, leaving part of the semantic burden unaddressed.

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

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

The description clearly identifies the resource ('training status') and the temporal scope ('last month'), and the tool name plus 'monthly' distinguishes it from get_training_status_daily and get_training_status_weekly. It does not explain what 'training status' contains, but the core 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?

The phrase 'last month' gives an implied usage context for when this tool is relevant, and the sibling names signal daily/weekly/monthly options. However, the description never explicitly says when to prefer this over get_training_status_daily or get_training_status_weekly, nor does it mention any exclusions or 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?

With no annotations at all, the description carries the full burden for behavioral disclosure, but it only restates the time window and the end parameter format. It does not explain how the weekly value is aggregated, what happens when end is null, whether the range is inclusive, or any read/access characteristics.

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 compact sentence with the core scope front-loaded and no filler. Every word contributes 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 one-optional-parameter tool with an output schema, the description is minimally adequate: it gives the time window and date format. It is not complete because it lacks explicit alternative routing and default behavior, but the low complexity prevents this from being a severe gap.

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

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

The schema has no description coverage, but the 'up to end, YYYY-MM-DD' note does add format and semantic meaning for the single optional parameter. It still fails to explain the null default and the behavior when no end is provided, so compensation is partial.

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 identifies the resource (training status) and the temporal scope (last week), which is enough to distinguish it from get_training_status_daily and get_training_status_monthly. It lacks an explicit verb in the description itself, relying on the tool name's 'get', so it is clear but not maximally explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The time window 'last week' implies this tool should be used when weekly granularity is needed, particularly against get_training_status_daily and get_training_status_monthly. However, it never explicitly states when to choose this tool over those alternatives or what to do if no end date is supplied.

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 of disclosing behavior. It only lists output fields and provides no explicit statement about read-only nature, authentication requirements, data source, or lack of side effects. This is minimal transparency beyond the obvious.

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 phrase that front-loads the resource and lists the key fields. It avoids wasted words, but it is a fragment rather than a complete sentence, which slightly reduces structure quality.

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

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

For a zero-parameter tool with no output schema, the description's field list partially compensates, but it lacks explicit context about whether this is the current authenticated user's profile and how it differs from get_user_settings. The description is minimally serviceable but not complete.

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

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

The tool has zero parameters and the schema is empty, so the description has no parameter semantics to add. Per the rubric, 0 params earns a baseline of 4; the description adequately avoids inventing parameter-related 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 identifies the resource (Garmin user profile) and enumerates the fields it returns (name, email, age, sex, height, location), so an agent can understand what the tool provides. However, it is a noun phrase rather than a verb-phrase like 'Gets the...', and it does not explicitly distinguish itself from the sibling get_user_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?

There is no guidance about when to use this tool versus alternatives such as get_user_settings or other profile-adjacent tools. The description implies retrieval of basic profile data, but it never states a condition, exclusion, or preferred alternative.

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 of behavioral disclosure. It only lists settings categories and never explicitly states that the operation is read-only, what the response shape will be, or what units or formats the values use. The 'get' in the tool name implies retrieval, but the description itself adds little behavioral 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?

The description is extremely compact with no filler words and the resource is front-loaded. It is slightly fragmentary as a colon-list rather than a complete sentence, but it is appropriately concise for a zero-parameter settings getter.

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

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

For a zero-parameter tool with no output schema and no annotations, the description names four concrete setting domains, which gives an agent a reasonable idea of what to expect. However, it does not define the exact return structure, units, or how this differs from overlapping sibling tools, so completeness is only partial.

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

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

The tool has zero parameters, so the baseline for this dimension is 4 regardless of the description. The description does not need to explain parameter semantics, and the content list adds minor context about what the returned settings cover.

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

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

The description clearly identifies the resource as 'user settings' and enumerates the key content areas: VO2Max, thresholds, measurement system, and sleep times. It is not a tautology, but it does not use a full verb and does not distinguish itself from overlapping sibling tools like get_garmin_scores or get_user_profile.

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 about when to use this tool versus the many sibling getter tools. The description never mentions alternatives, exclusions, or a decision rule such as 'use get_user_profile for user identity information'.

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 disclosure burden. It reveals the rolling window and date format but does not explain how a null or omitted 'end' behaves, whether the end date is inclusive, or timezone handling. For a read tool this is lightly transparent but incomplete.

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?

One compact sentence with all content front-loaded; the parenthetical adds period and date format without waste. No redundant restatement of the tool name or schema.

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 single-parameter, low-complexity read with an output schema, the description is close to sufficient. Remaining gaps around null default semantics and exact inclusion of the end date prevent it from being fully self-contained.

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 supplies the key meaning for the single parameter: 'end' is the upper bound in YYYY-MM-DD format with a 7-day period. It does not clarify the meaning of the default null or whether the end date is included, so the compensation is partial.

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 identifies the resource ('step count') and the exact time window ('last 7 days'), which separates it from get_daily_steps and get_steps_goal. It does not use an explicit verb like 'returns' or name a sibling tool, so it falls just short of a perfect score.

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 usage is implied: use this tool when you need 7-day step data anchored at the provided end date. It does not state when to prefer alternatives like get_daily_steps or get_steps_goal, nor does it mention 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the time range and the end date format, but omits details such as whether the end date is inclusive, what timezone applies, whether the result is a daily breakdown or aggregate, and whether this is a read-only operation. This is minimal and leaves key behaviors unspecified.

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 with no filler. It front-loads the core fact (stress history) and then the scope ('last 7 days') and parameter format. Every word earns its place, and it is appropriately sized for a tool with one optional 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?

The tool is simple and has an output schema, so return values are covered elsewhere. But among many sibling tools that deal with stress or body battery, the description does not explain how this tool differs, nor does it clarify the default behavior of 'end'. For a one-parameter tool, the description is close to adequate but still leaves the null case and sibling boundary unresolved.

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. It does add meaning by explaining that 'end' is a YYYY-MM-DD date and that the history runs 'up to' that date. However, it does not clarify what happens when 'end' is null (the schema default), nor does it describe whether the period includes the end date or excludes it. The description partially compensates but leaves a notable gap.

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

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

The description clearly states the tool returns stress history for a weekly window. The name and 'last 7 days' distinguish it from daily stress tools. However, no explicit verb like 'get' or 'retrieve' is present, and it does not differentiate from the similarly named get_body_battery_stress_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?

No explicit guidance is given on when to use this tool versus alternatives. The description implies a weekly time range, but it never mentions get_daily_stress, get_body_battery_stress_history, or when this tool is the right choice. An agent must infer usage from the name alone.

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

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

There are no annotations, so the description carries the full behavioral burden. It only describes the returned content and not behavior such as whether the operation is read-only, what happens when day is null/defaulted, or possible failure conditions.

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?

A single, front-loaded sentence with no filler. Every phrase carries information: resource, date format, and returned data.

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

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

The tool is simple, but there is no output schema and no annotations, so the description must explain return shape and default behavior. It only partially does so with 'target + target ranges' and does not clarify how the optional day parameter behaves.

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 compensates partially by documenting the date format (YYYY-MM-DD). It does not explain the null/default behavior or whether the date is relative to a particular timezone.

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 resource ('weight goal'), a time scope ('for a day'), and the expected contents ('target + target ranges'). It is distinguishable from siblings like get_body_weight and get_weight_history, though it does not explicitly contrast them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The date scope implies it is for retrieving a single day's goal rather than history or measured body weight. However, it does not explicitly state when to choose this tool over get_weight_history, get_body_weight, or get_steps_goal, and it does not explain what omitting the day argument means.

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 of behavioral disclosure. It only states the temporal range and date format, omitting read-only expectations, behavior when 'end' is null, timezone/inclusivity, or any side effects. This is minimal for a tool with no annotation support.

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?

A single, front-loaded sentence with no filler words. It conveys the core purpose and parameter hints efficiently.

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 simple tool and existence of an output schema, the description is nearly sufficient for calling it, but it omits default/null behavior and provides no guidance distinguishing it from sibling weight tools. These gaps prevent complete self-sufficiency.

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 description coverage is 0%, but the description does add meaning by mapping 'days' to 'N' and explaining the 'end' parameter format as YYYY-MM-DD. However, it does not explain the defaults (days=7, end=null) or what a null end date means, leaving a gap.

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

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

The description clearly identifies a weight-history retrieval tool with a specific temporal scope ('last N days') and a date format for the endpoint. It does not explicitly contrast itself with siblings like get_body_weight or get_weight_goal, so it stops short of full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives such as get_body_weight, nor any mention of when not to use it. The usage context is only implied by the word 'history', not stated explicitly.

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