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

No annotations provided, so description must cover behavior. It states the tool checks status and last sync time, implying a read-only operation. However, it omits details like auth requirements, caching, or call frequency limits, which are acceptable for a simple tool but not fully 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?

Single sentence that is front-loaded and contains all necessary information. No extraneous words.

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

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

Given no output schema, the description still conveys what the tool returns (status and sync time). It sufficiently covers the tool's role among siblings for a simple read-only 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?

No parameters exist, and schema coverage is 100% vacuously. The description adds no param info, but none is needed. Baseline 4 is appropriate for zero-parameter tools.

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

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

The description clearly states the action ('Check') and resource ('connection status to data source and last sync time'), making it distinct from sibling tools like 'sync_data' that perform different operations.

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

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

No explicit when-to-use instructions or mention of alternatives. The description implies usage for verifying connectivity before other operations, but lacks guidance on when not to use or comparison with 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states the basic function and does not disclose traits like read-only nature, data source, or limits. This is a minimal disclosure, but it does not contradict any annotations. A score of 3 reflects adequate but incomplete transparency.

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

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

The description is a single sentence, 10 words, with no fluff. It front-loads the key information. While it is concise, it could benefit from a bit more context (e.g., output hints) without becoming verbose. Thus, a score of 4 for efficiency with room for slight improvement.

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 output schema, the description should hint at what the summary contains (e.g., aggregated metrics). It does not. The input is well-covered by the schema. The sibling tools suggest this is a broad summary, but agents may need to know the return structure to interpret results. A score of 3 reflects adequate but incomplete context for a tool of this 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 input schema covers 100% of parameters with clear descriptions (e.g., 'date', 'start_date', 'end_date', 'timezone' with formats and defaults). The tool description adds no additional parameter information beyond the schema, which is acceptable. Baseline 3 is appropriate as the schema alone is sufficient for understanding 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 action ('Get') and the resource ('daily activity summary') with a scope ('for a date or date range'). It effectively distinguishes from siblings like 'get_connection_status' or 'query_heart_rate', which are more specific or unrelated. However, it could be more specific about what the summary includes (e.g., steps, calories), which is left ambiguous.

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

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

The description implies usage by mentioning a date or date range, but it does not explicitly guide when to use this tool over alternatives. For example, it could state that this tool provides an aggregated summary while specific metrics are handled by 'query_*' tools. Without such guidance, the agent may misuse the tool.

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

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

With no annotations provided, the description bears the full burden. It states the tool returns which dates have data for each type, indicating a read-only operation. However, it does not disclose any potential side effects, rate limits, or authorization requirements, leaving some behavioral ambiguity.

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

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

The description is a single, concise sentence that front-loads the core functionality. Every word is necessary, and it avoids redundancy.

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

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

Given the simplicity of the tool (one optional parameter, no output schema), the description is nearly complete. It explains what the tool does and the output concept. Some minor gaps exist, such as not specifying the return format, but for this context it is sufficient.

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

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

The input schema already describes the single parameter 'data_types' with 100% coverage. The description adds no further semantic information beyond what the schema provides, so it meets the baseline but does not enhance understanding.

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

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

The description clearly states the tool's purpose: 'Get data coverage information - which dates have data for each type'. It specifies the verb 'get' and the resource 'data coverage information', and it is distinct from sibling tools like query_* tools which focus on specific data types.

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

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

The description implies use for checking data availability but provides no explicit guidance on when to use this tool versus alternatives (e.g., other query tools) or any prerequisites. Usage context is implied but not articulated.

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 should disclose behavior, but it only states the basic function. It doesn't mention whether the operation is read-only, what data is included, or any 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 concise sentence, but it lacks structure and could be expanded with context 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?

Given the presence of multiple sibling tools and the simplicity of the schema, the description is too sparse. It fails to specify what 'profile information' includes or how the optional parameter affects the output.

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 100% as the optional parameter 'include_devices' is well-defined in the schema. The description adds no additional meaning beyond the schema, meeting the baseline.

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 user profile information' clearly states the action (get) and resource (user profile), distinguishing it from sibling tools that focus on specific data types like heart rate or sleep. However, it doesn't differentiate from generic profile retrieval.

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 its siblings, such as get_connection_status or query_metric_series. The agent must 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?

With no annotations, the description carries full burden but only states basic purpose. It does not disclose whether data is aggregated, how latest_only works, or if pagination exists. The agent gets minimal behavioral insight beyond 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 extremely concise at one sentence, effectively front-loading the core purpose. However, it sacrifices valuable detail, which prevents a perfect score.

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

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

Given no output schema and four parameters, the description is insufficient. It omits details on metrics selection, latest_only behavior, and return structure, leaving the agent with incomplete information for safe invocation.

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

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

The input schema has 100% description coverage, so each parameter is already documented. The tool description adds no extra semantic value beyond 'for a date range,' which is redundant with the schema. Baseline 3 is appropriate.

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

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

The description explicitly states the verb 'Query' and the resource 'body measurements (weight, body composition)' for a date range, clearly distinguishing from sibling tools like 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?

No guidance is provided on when to use this tool versus alternatives (e.g., query_metric_series). The description lacks any when-to-use or when-not-to-use instructions, forcing the agent to infer context.

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

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

With no annotations provided, the description carries full burden for behavioral transparency. It only states the action and scope, omitting critical details like read-only nature, pagination, error handling, or data retention limits. The description does not disclose any behavioral traits beyond the basic query.

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 of 8 words, very concise and front-loaded. However, it may be too terse, missing important context like return format. It is efficient but not optimally informative.

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

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

Given 4 parameters and no output schema, the description is incomplete. It does not explain the response structure, pagination, or any side effects. Compared to sibling tools like get_daily_summary, which provide more context, this description leaves many gaps.

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

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

Schema coverage is 100% with clear parameter descriptions. The description adds no additional meaning beyond what the schema provides, such as format constraints or dependencies between parameters. Baseline of 3 is appropriate since schema does the heavy lifting.

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

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

The description clearly states the verb 'query' and the resource 'heart rate samples' with a scope 'for a date range'. Among siblings like query_body_measurements and query_sleep, this tool is specific to heart rate, providing good differentiation.

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

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

The description provides no guidance on when to use this tool vs alternatives such as query_metric_series or query_body_measurements. It implicitly says to use for date ranges but lacks explicit comparisons, exclusions, or prerequisites.

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

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

With no annotations provided, the description must disclose behavioral traits. It only states 'Query', implying read-only, but lacks details on rate limits, data freshness, authentication needs, or any side effects. The description is insufficient for behavioral transparency.

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

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

The description is a single concise sentence that is front-loaded with the core action and resource. However, it could include a bit more structure, such as listing key parameters or constraints, 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?

Given the tool has 5 parameters, 3 enums, and no output schema or annotations, the description is too minimal. It does not explain return format, pagination, or behavior for overlapping dates. The schema covers parameters but contextual completeness is lacking.

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 100%, so the schema already provides adequate information for each parameter. The description adds no extra meaning beyond 'time series data', which is already implied. Baseline 3 is appropriate.

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

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

The description clearly states the action 'Query' and the resource 'time series data for a specific metric', providing a specific verb and resource. However, it does not differentiate from sibling tools like query_heart_rate or query_sleep, which also query time series data for different domains.

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, exclusions, or context that would help the agent select it over other 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?

With no annotations, the description alone must convey behavioral traits. It only states 'Query sleep sessions', implying a read operation, but omits details about return structure, data freshness, pagination, or whether it supports historical queries beyond the date range. This is insufficient for an agent to anticipate side effects or output.

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 instantly conveys the tool's purpose. Every word is necessary, and there is no redundancy or filler.

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

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

Given the lack of output schema, annotations, and the presence of 4 parameters, the description is too terse. It fails to specify return format, data granularity, or behavioral details like rate limits or data coverage, making the tool under-specified for an agent.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond 'for a date range', which is already obvious from the required start_date and end_date. It does not explain the role of optional parameters like include_naps or include_stages.

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

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

The description clearly states it queries sleep sessions within a date range, specifying the resource (sleep sessions) and scope (date range). It distinguishes from sibling tools like query_heart_rate and query_workouts, which target different health metrics.

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 does not mention prerequisites, when-not-to-use, or reference sibling tools like get_daily_summary or query_workouts, leaving the agent to infer usage context.

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

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

No annotations provided, and the description does not disclose behavioral traits such as read-only nature, side effects, authorization requirements, or pagination. 'Query' implies read-only but is not explicitly 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 description is a single clear sentence with no unnecessary words. It efficiently conveys the tool's purpose.

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

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

Despite having 5 parameters and no output schema, the description provides no details about the return format, scope of results (e.g., multiple workouts per day?), or any behavior beyond the date range. This is incomplete given the tool's 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 description coverage is 100%, with each parameter already described in the schema. The tool description adds no additional meaning or context beyond the schema, which is adequate but not extra.

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 'Query workouts for a date range', specifying the verb (query), resource (workouts), and time scope. It distinguishes from sibling tools like query_heart_rate and query_sleep by focusing on workouts.

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

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

No guidance on when to use this tool over alternatives like query_metric_series or get_daily_summary. The description does not mention use cases, prerequisites, or when not to use it.

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

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

Without annotations, the description bears full responsibility for disclosing behavioral traits. It only states the general operation, failing to mention that this is a write/mutation tool, potential side effects on local cache, or any authorization or rate limit considerations.

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

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

The description is extremely concise (one sentence), which is efficient but sacrifices important details that an agent might need. It is front-loaded but overly brief.

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 four parameters and no output schema or annotations, the description fails to provide essential context about sync behavior (e.g., incremental vs full, overwrite policy, impact on existing data). The tool's complexity demands a more complete description.

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 100%, so baseline is 3. The description does not add value beyond what the schema already provides for parameters. No additional information about format, constraints, or usage is given.

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 clear verb ('synchronize') and specifies the resource ('data from source to local cache'). It distinguishes from sibling query tools by implying a write/update operation. However, it could be more specific about what 'source' refers 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?

No guidance is provided on when to use this tool versus alternatives like query tools. There is no mention of prerequisites or situations where syncing might be inappropriate.

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