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

No annotations are provided, so the description carries the full burden. It adds a useful output nuance ('each metric range states how many reported a value'), but it does not explicitly state that the operation is read-only or disclose any other behavioral traits. The comparison is implicitly safe but not stated.

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 a single front-loaded sentence with no filler. It packs the core action, the resource bound, and a key output interpretation detail into minimal space.

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

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

Given the low complexity (one array parameter) and the presence of an output schema, the description covers the essential scope and an important output nuance. The only notable absence is explicit sibling differentiation, which is not critical for this simple tool.

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

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

The schema provides zero description coverage for activity_ids, so the description must compensate. It implies the array-length constraint (2-10) but does not explain what the IDs refer to or any formatting expectations; the meaning relies heavily on the parameter name.

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 concrete operation ('Compare') on a bounded resource (2-10 activities), which is specific enough to distinguish it from sibling get_activity/get_activities tools. The count range adds precision beyond a generic 'compare activities' phrasing.

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

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

Usage context is only implied: the plural comparison semantics suggest choosing this over get_activity/get_activities, but there is no explicit when-to-use or when-not-to-use guidance. An agent must infer the selection criteria from the tool name and siblings.

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

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

With no annotations, the description carries the full behavioral burden. It usefully discloses two real constraints: the range is inclusive and capped at 366 days, and the default window is 14 days. It omits pagination, ordering, and what 'limit' does, so it is only partially 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?

One sentence, front-loaded with the core action and immediately followed by the two constraints that matter. No filler or redundancy.

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

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

An output schema exists, so return values need not be described. Still, for a zero-coverage 3-parameter tool the description leaves 'limit' and date format undocumented, which is a meaningful 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 compensate. It explains the start/end date semantics (inclusive range, 366-day cap) and the default range, which covers two of three parameters, but says nothing about 'limit' or the date string format.

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

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

States a specific verb ('List') and resource ('activities'), so the operation is unambiguous. However, it does not differentiate itself from the near-identically-named siblings get_activity and get_recent_activities, leaving the agent to guess which one applies.

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 when-to-use guidance and never mentions alternatives like get_activity or get_recent_activities. The stated default window (last 14 days) is a behavioral default, not routing guidance, so the agent gets no help choosing among siblings.

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

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

No annotations are provided, so the description carries the behavioral disclosure burden. It clearly implies a read-only operation and notes that HR/power zones are 'available' rather than guaranteed, but it does not mention behaviors like how missing activity IDs are handled, auth requirements, or response edge cases.

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 qualifiers. It front-loads the core action and then enumerates the specific returned data, making it easy to scan.

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 present, the description provides the key information needed to invoke it: the singular scope and the kinds of data returned. It omits usage guidance and edge-case behavior, but those are partially inferable from sibling names and the output schema.

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

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

The schema has 0% description coverage and only defines activity_id as a required integer. The description does not explicitly explain the parameter, but the property name and title 'Activity Id' are self-explanatory for a one-parameter getter, so the gap is minor.

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 uses a specific verb and resource ('Get one activity') and lists concrete output categories (summary, laps, training effect, HR/power zones). The word 'one' distinguishes it from plural siblings like get_activities and get_recent_activities, though it does not explicitly contrast with compare_activities.

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 guidance about when to use this tool versus sibling tools. The singular 'one activity' implies it is for a single activity's detail, but the description does not state to prefer it over get_activities or compare_activities, leaving the selection decision to inference.

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

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

With no annotations, the description carries the burden of disclosing behavior. It clearly states what data is returned, but it does not explain behavior around optional inputs like date nullability or include_timeseries, nor does it mention any side effects or access 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 a single, efficient sentence with no filler. It front-loads the tool's purpose and includes useful output details without becoming verbose.

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 values, but the description lacks guidance on parameter behavior and usage when to use this tool versus siblings. It is adequate for a simple read operation but leaves optional-input semantics and selection context to the agent.

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

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

The input schema has 0% description coverage, so the description must compensate. It vaguely maps to the date parameter through 'for one day', but it says nothing about include_timeseries, date format, or what a null date means. An agent would need to infer most parameter semantics.

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

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

The description uses a specific verb ('Get'), names a clear resource ('Garmin Body Battery'), and specifies scope ('for one day'). It also enumerates the main outputs (charged/drained, start/end/high/low levels), which distinguishes it from sibling tools like get_sleep or get_daily_summary.

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 this is the tool for day-level Body Battery data, but it gives no explicit guidance on when to choose it over alternatives like get_daily_summary. There are no stated conditions, exclusions, or references to sibling tools.

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?

Without annotations, the description carries the behavioral burden. It adds transparency about the maximum date range and data source, but it does not disclose default behavior when dates are omitted, date format expectations, or how the endpoint handles over-range requests.

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; the verb, resource, and key constraint all appear before any secondary details.

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

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

With an output schema and only two optional simple parameters, the missing pieces are small, but the lack of default-date behavior and usage routing leaves an agent to infer how to call it without arguments.

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 adds the meaningful constraint that start/end dates span at most 366 days, but it does not document date syntax or what null defaults mean for each 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?

States a specific verb ('Get'), resource ('weight and Garmin-provided body composition'), and a concrete boundary (at most 366 days). This clearly differentiates it from sibling health-data tools by naming the body-composition 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?

The resource name implies use when body composition or weight data is needed, and the 366-day cap is a useful constraint. However, it does not explicitly state when to prefer this tool over siblings or give exclusions.

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 adds useful context by noting the output is normalized and excludes notes, symptoms, and raw day logs, but it does not explain what 'normalized' means, how date selection affects results, or any data-availability caveats.

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. Every word contributes to the core semantics of what is returned and what is excluded.

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

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

The tool is simple with one optional parameter and an existing output schema, so return-value documentation is not required. However, the missing date semantics and lack of usage guidance leave some ambiguity about how to invoke it correctly, especially when a specific date is needed.

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

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

The single optional 'date' parameter has 0% schema description coverage and the description does not mention date at all. The agent is given no guidance about accepted formats, default behavior, or what null means, so the description fails to compensate for the missing schema detail.

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 uses the verb 'Get' with a specific resource, 'normalized cycle phase/timing', and explicitly states what is omitted ('without notes, symptoms, or raw day logs'). This identifies the tool's function clearly, though it does not directly differentiate from the listed siblings since none target cycle data.

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 statement of when to use this tool versus alternatives. The exclusions imply a summary use case, but no sibling or alternative tool is named and no contextual conditions are 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get' implies a read operation, but the description does not clarify date behavior, defaults, authentication requirements, or any other operational constraints. It only lists returned fields rather than explaining how the tool behaves.

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 a front-loaded verb and a useful list of metrics. There is no filler or repetition, though it sacrifices necessary parameter information for brevity.

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 tool with one optional parameter and an output schema, the description is too thin. It omits any mention of the date parameter and provides no usage or behavior context, leaving the agent to infer too much from the tool name and schema alone.

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, 'date', is completely absent from the description, while schema description coverage is 0%. The schema only provides a type and default, so the agent receives no guidance on date format, accepted values, or what omitting the date means.

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 clear verb and resource: 'Get activity time/goals, HR, stress, respiration, SpO2, Body Battery, steps/calories.' It enumerates the data points returned, making the tool's purpose obvious. It does not explicitly contrast with sibling tools such as get_stress or get_body_battery, but the 'daily summary' framing implies an aggregate view.

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 the many sibling tools that cover individual metrics. It does not mention alternatives, exclusions, or scenarios where a different tool would be more 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 provided, the description carries the behavioral disclosure burden. It adds a useful, non-obvious limitation: optional readings are capped at 48 points. The read-only nature is implied by 'Get', though not explicitly stated, so there is still some room for more 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?

One sentence with no filler. The main purpose is front-loaded, and the limiting behavior is appended clearly. 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 description is adequate for a simple getter, especially since an output schema exists to document return fields. However, it fails to explain the semantics of the date parameter and offers no usage guidance relative to siblings, leaving moderate gaps for an agent to resolve.

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 two parameters. It indirectly references timeseries readings, which maps to include_timeseries, but it never explains the date parameter, its default behavior, or what the returned values represent. This is insufficient for full parameter clarity.

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 gives a specific verb and resource: retrieving Garmin HRV status and nightly values. This is immediately distinguishable from sibling tools focused on sleep, stress, recovery, or body composition, so an agent can tell what domain this tool belongs to.

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 choose this tool over siblings, nor whether it should be used for current status versus historical HRV data. The 'optional readings' note hints at timeseries usage, but the description never states when to use it or what the date parameter should represent.

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

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

With no annotations, the description carries the full behavioral burden. It does disclose the meaningful constraints that stay within a 1-90 day window and that type matching is case-insensitive, but it says nothing about result capping or truncation behavior despite a default limit of 20, nor about read-only safety. Useful context, but not complete for a zero-annotation tool.

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

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

One compact sentence with no padding, front-loading the verb, resource, and time bound. It is arguably too terse for a three-parameter tool, but there is zero wasted language.

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

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

An output schema exists, so return-value details are not required. Still, an agent calling this needs to know the default day window and that 'limit' caps results; those gaps are not covered by schema descriptions or annotations, leaving the definition only minimally viable.

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 document the valid range for 'days' (1-90) and the case-insensitive behavior of 'activity_type', but omits the 'limit' parameter entirely and never states the default window of 14 days. Partial compensation for three undocumented parameters.

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

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

States a specific verb ('List') and resource ('activities') with a bounded scope ('last 1-90 days'), which is more precise than a bare name restatement. However, it never distinguishes itself from the closely named sibling get_activities, leaving the agent to guess which list endpoint is appropriate.

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 when-to-use guidance, no mention of alternatives among the many sibling list tools (get_activities, get_activity, compare_activities), and no exclusions. The recency window is implied by the name but never framed as the selection criterion.

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 disclosure burden, and it succeeds by revealing that the tool explicitly reports missing data with reasons. This is valuable behavioral context beyond a plain metric fetch. It does not mention authentication, rate limits, or data source freshness, but the presence of an output schema reduces the need to describe return structure.

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, dense sentence that names the resource, the operation, the involved metrics, and the absence-handling behavior. It has zero filler and front-loads the core aggregation purpose, making it highly scannable for an agent.

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 output schema exists to document return values, the description covers the essential selection context: what data is aggregated and how missing data is handled. The only minor gap is date format/semantics, but with a single optional parameter and default null, the tool remains fully invocable. This is slightly better than the minimum viable definition.

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 single 'date' parameter. While the description doesn't explicitly mention the parameter, the tool's name and action make it clear that an optional date selects the recovery window. With only one optional parameter and a clear default of null, the semantics are reasonably inferable.

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 ('Combine') and resource ('Garmin sleep, HRV, Body Battery, stress, RHR, readiness'), making the tool's purpose clear. It does not explicitly differentiate it from sibling tools like get_daily_summary or get_training_readiness, but the aggregation framing sets it apart from the individual metric tools.

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

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

The phrase 'states why any is absent' implies this tool is a comprehensive recovery aggregator, useful when a consolidated view is wanted instead of querying each metric separately. It doesn't explicitly list exclusions or alternatives, but the 'combine' wording gives enough context for an agent to select it over getting single-metric siblings.

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

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that output is aggregated over a 7/14/28-day window, which is useful, but says nothing about permissions, whether values are smoothed/baselined, rate limits, or how the trend is computed.

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; the metrics list and the time window are both immediately visible. Nothing is wasted.

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

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

An output schema exists so return values need not be explained, and the trend window is covered. However, for a tool surrounded by many similar recovery/health siblings, the absence of any routing or scoping guidance leaves the definition only minimally 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% and the single 'days' parameter is undocumented in the schema. The description hints at acceptable values ('7/14/28 days') but never names the parameter, states its default of 7, or clarifies whether other integer values are honored.

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

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

States a specific verb ('Trend') and enumerates the concrete resources trended (sleep HR/temp, HRV, RHR, readiness, Body Battery) plus the window. The multi-metric trend framing does implicitly separate it from single-metric siblings like get_hrv or get_recovery, but it never explicitly names or contrasts those siblings.

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

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

There is no when-to-use guidance. With near-identical siblings such as get_recovery, get_hrv, get_sleep and get_daily_summary, the agent is left to infer that this tool is for multi-metric trend analysis over a window rather than point-in-time reads. No exclusions or alternatives are stated.

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

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

No annotations are provided, so the description carries the burden of revealing behavior. It clearly indicates a read operation and describes the retrieved data, which is useful. However, it doesn't disclose what happens if days is outside the 1-90 range, how end_date interacts with days, or any response-format caveats that the output schema may not cover.

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, repetition, or redundant phrasing. Every word adds meaningful detail and the key information is front-loaded.

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

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

Given the tool's simplicity, an output schema exists, and the description covers core what-it-returns and the time range, the definition is serviceable. But it lacks usage guidance versus sibling tools and doesn't explain end_date interpretation, leaving a moderately informed agent to guess about 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?

With 0% schema description coverage, the description must compensate for undocumented parameters. It does provide a range ('1-90 days') for the days parameter, which adds some meaning, but it says nothing about end_date beyond its name. The description leaves the relationship between days and end_date unclear, and doesn't cover format or validation 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 uses a specific verb ('Get') and clearly identifies the resource (running tolerance) and the data fields returned (Garmin running distance, impact load, tolerance, feedback). It also specifies a time range (1-90 days), making the tool's scope unambiguous. It doesn't explicitly differentiate from siblings like get_training_status or get_daily_summary, but the metric list is distinctive enough.

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 guidance on when to use this tool versus alternatives; it doesn't mention any sibling tools, prerequisites, or conditions that would select this tool over others. The '1-90 days' phrase is a parameter constraint, not usage 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?

No annotations are present, so the description carries the full burden of behavioral disclosure. The verb 'Get' implies a read-only operation, but the description does not explain date semantics (e.g., what passing null means), timezone behavior, or how missing sleep data is handled. It only lists metric categories.

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

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

The description is a single, front-loaded sentence that efficiently lists the tool's key outputs with no filler. It is appropriately compact, though the brevity contributes to the omission of parameter and usage context captured in other dimensions.

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

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

An output schema exists, so the return shape is covered, but the date parameter's format and behavior are undocumented, no sibling differentiation or usage conditions are given, and there are no annotations to fill gaps. These omissions make confident invocation harder than necessary for a tool with one critical parameter.

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

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

The description does not mention the sole 'date' parameter, which has 0% schema description coverage. The input schema only indicates a string/null with a default of null, leaving the expected date format and meaning of null undocumented; the description fails to compensate for this 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 uses a specific verb ('Get') and names the resource ('sleep') while enumerating the returned metrics: sleep score/need, stages, HR/stress, respiration, SpO2, and skin-temp deviation. This makes the tool's function clear, though it does not explicitly differentiate it from overlapping siblings like get_recovery, get_hrv, and get_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?

There is no explicit statement about when to use this tool versus alternatives. The name and metric list imply it is for sleep-related data, but no exclusions or alternate tool mentions are provided, leaving the selection to inference.

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

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It explicitly notes the series is capped at 48 points, a meaningful limitation, and indicates daily aggregation. However, it does not address auth, permissions, or other side effects, though the cap is a key disclosed behavior.

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 12-word sentence that front-loads the primary action and result before stating the limitation. Every word earns its place with 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?

The description is adequate for a simple tool but leaves notable gaps: parameter semantics are thin, and 'per-band durations' is not defined. The presence of an output schema covers return types, but usage and parameter details would need to be inferred from parameter names and sibling context.

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 0% description coverage, so the description must compensate for the two parameters. It indirectly relates to `date` via 'daily' and to `include_timeseries` via 'series capped', but never explains accepted date formats or how the timeseries flag alters the response, leaving the agent to infer.

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 begins with a specific verb and resource ('Get Garmin daily average/max stress') and clearly specifies output contents ('per-band durations'), making it distinct from sibling tools focused on other metrics like sleep, HRV, or body battery.

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

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

The description implies usage context through the metric name 'stress' but does not explicitly state when to use this tool over siblings or mention any exclusions. No alternatives are named, leaving the agent to infer from the resource 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 provided, the description carries the full burden. It does disclose a behavioral trait beyond a plain fetch — 'transparent comparisons' signals that the tool performs analysis and surfaces the underlying values — and 'anchored to date' clarifies filtering behavior. However, it omits operational details such as what happens when the date parameter is null and how 'preceding training' is bounded (how far back, how many sessions).

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 12-word sentence with the primary content ('recovery and preceding training') front-loaded before the qualifiers. Every word earns its place, there is no filler, and it is not a tautological restatement of the tool name.

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 and the tool is a simple one-parameter read operation, which lowers the bar. Yet with no annotations, the null-date behavior, the comparison baseline, and routing among a crowded sibling set remain unstated, so an agent would still need to make assumptions before invoking it.

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

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

Schema description coverage is 0%, so the description must compensate, and it does tie the only parameter 'date' to the core behavior via 'anchored to date.' It fails to state expected date format, timezone handling, or the semantics of null even though the schema defaults date to null, so an agent must infer what an omitted date yields.

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

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

The description names a specific verb and resource: get 'recovery and preceding training anchored to date,' which is a composite scope that differentiates it from single-domain siblings like get_recovery or get_activities. However, 'with transparent comparisons' is vague about what is being compared against what, leaving some ambiguity about the tool's exact function.

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 composite scope ('recovery AND preceding training') implies a comparison-oriented use case, which offers situational context. But the description never states when not to use this tool or names alternatives such as get_recovery for recovery-only needs, leaving sibling routing to inference.

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

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

There are no annotations, so the description must bear the full behavioral disclosure burden. It only lists returned metric categories and gives a 'Get' verb; it does not explain date handling, what happens when date is omitted, units, or any other behavioral details.

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, so it is concise. However, the structure is a long slash-separated list of jargon ('acute/chronic', 'ratio/status', 'focus/targets') that is cryptic and harder to parse than necessary.

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?

Although an output schema exists, the description lacks enough context for correct invocation. It does not explain the optional date's role or differentiate this tool from the sibling readiness, recovery, and activity tools, leaving important selection and call-time behavior unclear.

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 one optional date parameter with 0% description coverage, and the tool description does not mention date at all. The parameter name 'date' and its default of null provide a minimal hint, but the description adds no meaning about format, default behavior, or how date filters the load metrics.

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 uses the verb 'Get' and names a resource ('training load') followed by a list of metric categories, so the general purpose is recognizable. However, it is an indiscriminate enumeration ('acute/chronic load, ratio/status, focus/targets, VO2 max, scores, acclimation') that does not distinguish this tool from closely related siblings like get_training_readiness or get_recovery.

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 usage guidance is provided. The description does not say when to use get_training_load versus alternatives, nor does it state any exclusions or conditions. An agent is left to guess which of the many overlapping health-metric tools 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?

There are no annotations, so the description carries the full burden of behavioral disclosure. It only states that the tool gets readiness data; it does not reveal whether the date is required, what happens when no date is given, whether it returns data for multiple days, or any side effects. 'Get' implies read-only, but the description does not explicitly confirm this.

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, efficient sentence that names the resource and key output components with no fluff. It loses a point because the extreme brevity omits necessary context about the date parameter, but the existing text is well-structured and front-loaded.

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

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

For a tool with one optional parameter and an output schema, the description provides a minimal but acceptable overview of the return value. However, it is incomplete for correct invocation: it does not explain the role of the date parameter or how this tool fits among the many similarly named readiness/recovery 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 schema has 0% description coverage for the only parameter, 'date'. The description does not mention the date parameter at all, so the agent must infer formatting, meaning, and default behavior from the schema's title and default value alone. The description fails to compensate for the low schema coverage.

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

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

The description clearly states a specific verb and resource ('Get Garmin training readiness') and adds detail about the expected response contents ('component percentages, and factor feedback'). This distinguishes it from generic sibling tools like get_sleep or get_activities, though it does not explicitly contrast with get_recovery or get_body_battery.

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 instead of siblings like get_recovery, get_body_battery, or get_daily_summary. The description does not mention whether it supports a specific date, how it relates to other readiness metrics, or what inputs should be 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?

There are no annotations, so the description carries the full behavioral burden. It discloses a non-obvious reporting trait: each total states the count of activities that reported the metric, protecting against misinterpretation of incomplete aggregates. It also pins down the week boundary (Mon-Sun).

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 no filler; the purpose is front-loaded and the reliability caveat is appended in a second clause. 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 one-optional-parameter tool with an output schema, the description covers the aggregation window and a metric caveat. The main gap is the undocumented default/null-date behavior, which the schema leaves unresolved. That gap is minor given the 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?

Schema coverage is 0%, and the description never mentions the single 'date' parameter, its format, or the meaning of null (default). The parameter name is self-explanatory, but the description does not compensate for the schema's lack of documentation. An agent must guess how to format the date and what a null value does.

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

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

States a specific verb ('Summarize') and resource ('a Mon-Sun week'), making the function's scope immediately clear. It contrasts implicitly with get_daily_summary by defining the weekly aggregation granularity, though it does not explicitly name any sibling.

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 'Mon-Sun' qualifier conveys that a provided date is interpreted within its calendar week, which is useful routing context. It implies this tool is for weekly rather than daily or single-metric summaries, but gives no explicit exclusions and names no 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?

No annotations are present, so the description carries the disclosure burden. It signals a non-mutating retrieval operation ('Get') and clarifies that the data source is the user's configured thresholds. It does not mention output shape or edge cases, but the output schema covers return structure, making this a minimally sufficient disclosure.

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 tight sentence with no filler, and the specific resource ('Garmin HR-zone and cycling power-zone floor thresholds') is front-loaded. 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 zero-parameter, read-only tool, the description covers what is returned and where the data comes from. The output schema covers return details, and sibling names help disambiguate intent. The only notable gap is usage guidance, which is minor 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 tool takes zero parameters, so there are no argument semantics to document. With no parameters, the baseline of 4 applies and the description does not need to compensate for schema gaps.

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 verb 'Get' and a specific resource: 'configured Garmin HR-zone and cycling power-zone floor thresholds.' Unlike sibling tools, which return measured metrics like sleep or readiness, this targets stored configuration thresholds, making it readily distinguishable.

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 siblings such as get_training_context or get_training_load. The description neither states use cases nor exclusions, leaving the agent to infer intent from the tool name alone.

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