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

There are no annotations to aid transparency, so the description carries the full burden. It only restates the action without disclosing whether it is read-only, what data it returns, or any potential side effects. This is a tautological statement that adds no behavioral 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 extremely short, but this is under-specification rather than appropriate conciseness. The single phrase 'Check connection status' simply restates the tool name and does not earn its place by adding valuable 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 tool with no output schema and no annotations, the description should at least clarify what 'connection status' refers to, whether it returns a boolean or detailed diagnostics, and whether any side effects occur. The description is too sparse to be complete even for a simple status check.

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 already covers everything (100% coverage). There is nothing for the description to explain, and the baseline for 0 parameters is 4.

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 'Check' and resource 'connection status', clearly stating the tool's function. However, it does not differentiate from sibling tools like get_sync_status, which might also relate to connection or synchronization.

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. There is no mention of appropriate contexts, prerequisites, or exclusions, leaving the agent to guess when this tool is the right choice.

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 fully disclose behavior. It only says 'get,' implying a read operation, but does not specify what the summary contains, whether it supports a single date or a range, or any response details. This is insufficient for a tool with no other behavioral metadata.

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 short sentence, but it is under-specified rather than concise. It does not earn its place as it fails to provide meaningful information beyond the tool's 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?

Given the lack of annotations, output schema, and parameter descriptions, this description is critically incomplete. The agent cannot infer what data is returned, how to use the date range, or what the response looks like, making this tool essentially unusable without 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?

Schema coverage is 0%, and the description does not clarify any of the three parameters (date, end_date, start_date). There is no indication of their format, validation, or how they interact (e.g., mutually exclusive or range-based), leaving the agent with no guidance.

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 provides a clear verb and resource ('Get daily activity summary'), but the 'daily' wording conflicts with start_date/end_date parameters that suggest a range. It also does not distinguish this tool from sibling query tools (e.g., query_metric_series) that may also return summaries.

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 over alternatives, nor any mention of appropriate scenarios, date ranges, or prerequisites. The description neither explains its context nor excludes any use cases.

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, and the description does not disclose any behavioral traits such as side effects, permissions, data sources, or return behavior. The agent is left completely in the dark about what happens when this tool is invoked.

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, but it is under-specified rather than concise. It omits essential information, so brevity is not a virtue here; the description does not earn its place as a meaningful explanation.

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 minimal parameter schema, the description is the only source of context. It is severely incomplete, failing to explain what 'data coverage' returns, what data_types control, and how this relates to sibling tools.

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

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

The schema has one parameter, data_types, which is an array of strings. However, the description provides zero explanation of what 'data types' means in this context, and schema description coverage is 0%. The description fails to compensate for the undocumented 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 'Get data coverage' simply restates the tool name without elaborating on what data coverage is or what it pertains to. No specific verb or resource beyond the name itself is provided, making it tautological and unhelpful.

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 offers no context about when to use this tool compared to alternatives like sync_data, get_sync_status, or query_* tools. There are no prerequisites, exclusions, or recommended scenarios 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Get user profile information' without revealing what fields are returned, whether it accesses the current user or requires authentication, or any potential side effects. For a simple read operation, this is minimal but insufficiently 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?

The description is a single, straightforward sentence with no filler words. It is front-loaded and efficient, earning a perfect score for conciseness and 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?

With no output schema and no annotations, the description is expected to explain what the tool returns. It merely says 'user profile information' without specifying which fields or the response format. This leaves an AI agent uncertain about the data structure and completeness, making the contextual information inadequate.

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 parameters, so the baseline is 4. The description does not need to explain parameter semantics since there are none. It correctly avoids adding irrelevant parameter information.

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 clear verb ('Get') and resource ('user profile information'), which matches the tool name. While it does not explicitly distinguish from sibling tools, the resource is distinct enough (no other profile-related tool exists among siblings), making the purpose fairly clear.

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. The description simply states what it does without mentioning contexts, prerequisites, or exclusions. Given the presence of many sibling tools, this lack of usage direction 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 provided, so the description carries full burden. It implies a read operation but does not state that it is read-only, whether authentication is needed, or what the returned status looks like. It only restates the tool's purpose without behavioral 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 a single concise phrase with no redundant words. It is front-loaded with the action and resource, 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?

For a tool with one parameter and no annotations or output schema, this description is too minimal. It lacks information about what status values are possible, how to get sync_id, and what the response contains. A user cannot effectively use the tool without more 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?

Schema description coverage is 0% for the only parameter 'sync_id'. The description does not explain what sync_id refers to, how to obtain it, or its format. It adds no semantic value beyond the schema, which is already empty.

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 verb 'Get' and resource 'background synchronization status' clearly state what the tool does. It distinguishes from siblings like get_connection_status (connection vs sync status) and sync_data (trigger vs retrieve status).

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

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

The description provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, context, or scenarios where this is preferred over get_connection_status or sync_data. Only implied usage.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It indicates a read-only query but does not disclose any behavioral traits such as required permissions, response format, date range handling, or limitations. This is a significant 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, direct sentence with no filler. It is appropriately brief and front-loaded, though it sacrifices valuable detail 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?

Given no annotations and no output schema, the description should provide more context about response structure, parameter constraints, and usage. It falls short, leaving the agent to infer critical details and increasing the risk of incorrect 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?

Schema description coverage is 0% and the description provides no explanation of parameters. The schema lists start_date, end_date, and limit, but the description does not clarify their semantics, formats, or defaults, offering no added value beyond the raw 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 clearly identifies a query operation for a distinct resource ('abnormal heart beat events'), which differentiates it from sibling tools like query_heart_rate and query_metric_series. However, it lacks detail on the nature of 'abnormal' events, so it is not maximally specific.

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 explicit guidance on when to use this tool versus alternatives. The usage is only implied by the name, with no mention of alternatives or exclusions, such as when query_heart_rate 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 full burden of behavioral disclosure. It only states 'Query body measurements' and gives no information about return formats, data granularity, side effects, read-only status, or any other behavioral aspects. The description is essentially non-informative beyond the tool 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?

At four words, the description is under-specified rather than appropriately concise. It lacks even the basic structure needed to convey a clear meaning, sacrificing all substantive content for brevity. The description does not earn its place because it provides zero informational value beyond 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?

Given the tool has four parameters, no output schema, and no annotations, the description is completely inadequate. It does not explain what body measurements are included, how date ranges work, what metrics are available, or what 'latest_only' means. An agent would be left guessing about the tool's full behavior and required inputs.

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 four parameters (metrics, end_date, start_date, latest_only) with zero descriptions. The description adds no meaning to any of these parameters, failing to compensate for the 0% schema description coverage. It does not explain date format, allowed metric values, or the effect of latest_only, leaving all parameter semantics unexplained.

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 'Query body measurements' is a tautology, restating the tool name verbatim without adding any new information about what the tool does, what kind of body measurements it retrieves, or how it differs from sibling tools like query_metric_series or query_heart_rate. It names a verb and resource but provides no distinct purpose clarification.

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 mention of prerequisites, typical use cases, or exclusions. The sibling tools include multiple measurement queries, and this description does nothing to differentiate them, leaving the agent without direction for tool selection.

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

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

With no annotations, the description carries the full burden of behavioral disclosure, but it provides none. It does not mention return format, pagination, filtering behavior, or whether it is read-only. The description simply restates the tool's name and offers no behavioral 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 extremely short, but this is under-specification, not conciseness. A tool with four parameters and no other context requires more than a single phrase to be useful. Every word is wasted because no additional meaning is conveyed.

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

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

Given the tool's complexity (4 parameters, no output schema, no annotations) and the presence of sibling query tools, the description is woefully incomplete. It offers no return value information, parameter semantics, or usage context, making it impossible for an agent to correctly invoke or select the tool.

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

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

Schema description coverage is 0%, so the description must compensate by explaining parameter meanings, but it does not. No parameter such as start_date, end_date, sample_type, or limit is mentioned, leaving the agent completely dependent on the schema's minimal field names.

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

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

The description 'Query heart rate samples' clearly identifies the verb and resource, distinguishing it from related query tools like query_sleep or query_workouts. However, it does not explicitly differentiate itself from potentially overlapping tools like query_metric_series, so it is clear but not fully distinguished.

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. There are no exclusions, alternatives, or contextual hints. The only implied usage is that it queries heart rate data, which is not enough to guide selection among many similar query 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?

No annotations are provided, and the description contains no behavioral details. There is no mention of read-only behavior, side effects, pagination, response format, or any constraints. The description carries the full burden for transparency and completely fails to disclose any behavioral traits beyond the act of querying.

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 only three words, which is extremely concise, but the brevity is a symptom of under-specification rather than efficiency. It does not earn its place since it merely parrots the tool name without contributing semantic value. A concise description should still convey purpose and 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?

This tool has 5 parameters, 3 enums, no output schema, and no annotations. The description only says 'Query metric series', which is far from sufficient. It does not explain what a metric series is, how to specify it, what the returned data looks like, or any constraints. Essential context for successful invocation is entirely missing.

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

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

Schema description coverage is 0%, meaning the schema itself provides no explanations for parameters. The description adds zero information about metric, date ranges, aggregation, or granularity. It does not help the agent understand parameter purposes or relationships, such as how start_date and end_date define the series interval.

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 'Query metric series' directly restates the tool name (query_metric_series) without adding specificity. It identifies the verb and general resource but fails to indicate which metrics are involved, how the series is defined, or how it differs from sibling query tools like query_heart_rate or query_sleep. This is tautological and uninformative.

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. The sibling tools include many query_* variants, yet the description provides no context, use cases, or exclusions. An agent is left to guess which tool fits a given metric query.

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 'Query sleep sessions' only implies a read-only operation. It does not mention whether naps are included, how sessions are defined, what output is returned, or any side effects. This is insufficient for a tool with three parameters and no output schema.

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 short sentence, but it is under-specified rather than concise in a helpful way. It lacks essential detail, making it closer to a placeholder than an efficient explanation.

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 has three parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain how the tool behaves, what inputs are required, or what results to expect, making it inadequate for reliable tool selection and 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?

Schema description coverage is 0%, so the description must compensate by explaining the parameters. It provides no information about start_date, end_date, or include_naps, leaving the agent with no semantic meaning beyond raw schema names.

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

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

The description clearly identifies the resource ('sleep sessions') and differentiates from sibling tools that query other metrics like heart rate or workouts. However, it lacks scope details (e.g., date range vs. all sessions, or whether it returns summaries or raw sessions), making it slightly less specific than an ideal purpose statement.

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. The name implies sleep-related queries, but there is no explicit context, prerequisites, or exclusions, leaving the agent to infer usage 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.

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

No annotations are provided, and the description only says 'query', which implies a read-only operation without explicit confirmation. It does not disclose behaviors like return format, pagination, rate limits, or side effects.

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, concise and front-loaded. It earns its place by clarifying the resource, though it is sparse on details, which is a separate issue from 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 description is too minimal for a tool with no output schema and no annotations. It does not explain what 'samples' means, how date filtering works, or what the response contains, making it incomplete for effective use.

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 provides no information about the parameters (start_date, end_date, limit). With schema description coverage at 0%, the description was expected to compensate but does not, leaving parameter meaning entirely to the schema.

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

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

The description clearly states the tool queries blood oxygen saturation samples, using a specific verb and resource. It distinguishes from siblings by naming the unique resource (SpO2), though it does not explicitly contrast with other query 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?

No guidance is provided on when to use this tool versus alternatives, such as query_metric_series or other query tools. The description only states the function without any context or 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?

The description discloses no behavioral traits. It does not state whether the operation is read-only, what the response format looks like, whether pagination is supported, or any side effects. With no annotations, the description carries the full burden and fails entirely here.

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?

At only three words, the description is under-specified rather than appropriately concise. It lacks any sentence structure that conveys necessary context for a tool with four parameters, so brevity comes at the cost of usefulness.

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 completely inadequate given the tool's complexity: no annotations, no output schema, four parameters, and two required fields. A bare phrase like 'Query stress samples' leaves the agent without essential information about tool capabilities, constraints, or expected results.

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%, yet the description adds no explanation of the parameters (start_date, end_date, level, limit). The tool requires two date parameters and has a level enum, but the description does not clarify their meaning or usage, so it does not compensate for the lack of schema documentation.

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 specific verb 'Query' and identifies the resource as 'stress samples', which distinguishes it from sibling tools that query other data types (e.g., heart rate, sleep). However, it is not fully explicit about what constitutes a 'sample' or the exact scope, 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?

The description provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, intended use cases, or exclusions, leaving the agent without context for tool selection.

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

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

No annotations exist, so the description must disclose behavior. It only uses the generic verb 'query', which adds no insight into date-range requirements, output format, pagination, or read-only semantics.

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 short but under-specified. This is not effective conciseness; it omits all useful information while taking up almost no 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 five parameters, no output schema, and a sibling tool likely covering workout dynamics, the description is completely inadequate for correct selection or invocation. It provides no context about required date range or optional filters.

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 offers no explanation of the five parameters. The agent gets only names and types for start_date, end_date, min_duration, activity_types, and min_distance_km, with no units or format 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 'Query workouts' is a tautology that restates the tool name. It provides no detail about scope, filtering, or what distinguishes this from sibling tools like 'workout_series'.

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 workout_series or query_metric_series. There is no mention of required inputs or typical use cases.

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 fully disclose behavioral traits. It only says 'synchronize' without explaining side effects, such as whether it overwrites existing data, is asynchronous, requires authentication, or has rate limits. The tool appears to be a mutation/action, but none of these critical behaviors are disclosed, leaving the agent completely uninformed.

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 short sentence, which is efficient in length, but it is under-specified. It lacks any structural elements like usage examples, parameter summaries, or behavioral notes that would justify its brevity. The information provided is too minimal to be considered adequately concise; it is simply incomplete.

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

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

Given the tool's complexity (5 parameters, no annotations, no output schema, no schema coverage), the description is severely incomplete. It doesn't explain return values, sync behavior, or how to use the parameters, and it fails to provide any relationship to sibling tools. This is inadequate for an agent to select and invoke the tool effectively.

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 5 parameters and 0% schema description coverage, the description was expected to compensate for the lack of parameter documentation. It does not mention start_date, end_date, data_types, background, or force_full_sync, nor does it provide any hints about their meanings or formats. The agent cannot infer what each parameter does from the description alone.

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 'Synchronize Mi Fitness data' clearly states the action (synchronize) and the resource (Mi Fitness data). It distinguishes from sibling tools, which are mostly query/get operations for specific data types or connection status. However, it doesn't clarify the direction of sync (e.g., pulling from Mi Fitness or pushing to it) or the exact scope, so it's specific but not fully elaborated.

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. It doesn't mention that this is for triggering a sync while get_sync_status should be used for checking status, or that query tools should be used for reading data. The description offers no context about typical use cases or prerequisites, providing no 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses auto-downsampling, the hard limit on returned points ('never returns more than max_points points'), the reporting of downsampled/source_points/returned_points/method plus summary stats, and numeric t offsets in seconds. It also explains the normalization behavior and the effect of reference_max_hr, providing rich context beyond a simple API call.

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

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

The description is three sentences long, front-loaded with the primary purpose, and every sentence carries essential information. There is no redundancy or filler. It covers behavior, constraints, and the key usage caveat about reference_max_hr 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 tool's moderate complexity, lack of output schema, and 5 parameters, the description is remarkably complete. It explains the return format (points with t offsets, summary stats), the downsampling behavior, the max_points constraint, and the cross-activity normalization caveat. No significant gaps are evident for an agent to select and invoke the tool correctly.

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

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

Schema description coverage is 60%, and the description adds meaningful semantics for key parameters: reference_max_hr ('used to normalize time_in_zone... pass a consistent value when comparing zone distributions'), max_points ('Hard cap on returned points (server-enforced)' is in schema, but description reinforces 'never returns more than max_points'), and resolution ('increased automatically when needed to stay within max_points' is in schema, but description adds 'auto-downsampled'). It does not elaborate on workout_id or metric beyond schema, but those are straightforward. The description adds value beyond the schema for the most nuanced 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?

The description clearly states the tool's purpose: 'Get an agent-safe, auto-downsampled time series for a workout metric.' It identifies a specific verb (get), resource (time series for workout metric), and unique differentiators (agent-safe, auto-downsampled, contract version). It also distinguishes from sibling tools by focusing on the downsampling behavior and cross-activity normalization, which is not mentioned for query_heart_rate or query_metric_series.

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 clear context for when to use the tool, especially regarding reference_max_hr: 'For cross-activity comparison of time_in_zone, pass reference_max_hr... otherwise each activity is normalized to its own max and zone distributions are not comparable across activities.' It implies usage for workout metric time series, but does not explicitly name alternatives or state when not to use the tool. This is a clear context without explicit exclusions, aligning with a score of 4.

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