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

The description omits any details about side effects, such as whether the operation overwrites existing entries, requires prior data, or is idempotent. With no annotations and only a bare action phrase, the agent has no insight into the write behavior or potential consequences.

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

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

The description is concise, consisting of a single action line followed by a parameter list. However, it is not structured as a narrative or front-loaded with a summary; it reads as a bare enumeration, which is efficient but could be more organized.

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 lacks information about the return value or success/failure indications, despite the presence of an output schema. It also does not highlight which parameters are required (date and weight) or any constraints, leaving the agent with incomplete context for invoking the tool correctly.

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

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

The description adds moderate value by listing units for some parameters (e.g., weight in kg, percent_fat as percentage), but it does not provide units for all fields (e.g., basal_met) or clarify expected ranges. Given the schema has 0% coverage, this is helpful but incomplete, earning a middle score.

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 'Add' and the resource 'body composition data', making the tool's purpose unambiguous. It is also distinct from sibling tools like add_weigh_in and get_body_composition, so an agent can easily identify this as the write operation for body composition 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 such as add_weigh_in or get_body_composition. There is no explanation of prerequisites, relationship to other data, or typical use cases, leaving the agent to infer context 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 provided, the description carries the full burden of behavioral disclosure. It only states the high-level association action and does not reveal potential side effects, whether existing gear associations are replaced or appended, error behavior for invalid IDs, or any authorization 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 compact and well-organized, with a clear one-line summary followed by a focused Args section. Every sentence contributes value, and the parameter documentation is front-loaded and easy for an agent to parse quickly.

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

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

For a simple two-parameter tool with an output schema present, the description covers the basics of what the tool does and what the parameters mean. However, it omits important behavioral context such as whether the operation is idempotent, what happens if gear is already associated, and whether the activity must exist, making it adequate but not fully complete.

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

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

The input schema has 0% description coverage, so the description must compensate, and it largely does. The Args block provides semantic meaning for both parameters: activity_id is 'ID of the activity' and gear_uuid is 'UUID of the gear to add (get from get_gear)', adding useful sourcing context beyond the raw schema types.

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

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

The description clearly states a specific verb and resource: 'Associate gear with an activity' and 'Links a specific piece of gear to an activity.' It distinguishes the action from unrelated siblings by defining exactly what is being linked, though it does not explicitly contrast itself with remove_gear_from_activity or get_activity_gear.

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 only usage guidance is the hint that the gear UUID should be obtained from get_gear, which is a helpful prerequisite but not a tool-selection guideline. It does not explain when to choose this tool over remove_gear_from_activity or other gear-related tools, nor does it provide any exclusions or alternative conditions.

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

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

No annotations are provided, so the description carries the full burden. It only states 'Add hydration data' without disclosing any side effects (e.g., idempotency, overwrite behavior, required authentication) beyond the basic action.

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 and free of any unnecessary wording. It includes the essential action and parameter explanations in a compact format.

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

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

The description is adequate for a simple mutation, but lacks broader context such as the purpose of the hydration data, expected response format, or error handling. The parameter explanations are useful, but the overall context is minimal.

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 meaningful details for all parameters: units for value_in_ml and exact formats for cdate and timestamp. This adds value over the bare schema, which only lists parameter names and types.

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

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

The description clearly states the action ('Add hydration data') with a specific verb and object. It distinguished from the sibling 'get_hydration_data' tool, but does not elaborate on the exact resource or context (e.g., logging a new entry).

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

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

No explicit guidance on when to use this tool versus alternatives. The existence of a complementary 'get_hydration_data' tool implies usage for adding, but the description does not state this or mention any conditions.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the mutation intent ('Add') and explains arguments, but says nothing about what timestamp is assigned, whether an existing weigh-in for the same date is overwritten or duplicated, whether a valid weight range applies, or what happens on success. This is a thin behavioral profile for a write operation.

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

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

The description is short and front-loaded with the core action in the first sentence. The Args block is cleanly structured and every line earns its place. It is efficient without being cryptic.

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 flat 2-parameter tool with an output schema, the description covers the basics. The main completeness gap is the ambiguity relative to add_weigh_in_with_timestamps — an agent cannot determine which sibling fits its goal. Also missing is any note on timestamp/duplicate semantics, which matters for a health-data write.

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 partially does: unit_key is usefully explained as 'kg' or 'lb', which the bare schema (no enum) does not provide. However, 'weight: Weight value' is nearly tautological and adds little beyond the property name and type. The description is adequate but not a strong compensation for the missing schema descriptions.

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

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

The description states a specific verb and resource: 'Add a new weight measurement.' This is clear and unambiguous. However, it does not differentiate itself from the closely related sibling add_weigh_in_with_timestamps, which presumably does the same thing plus timestamp handling, so an agent cannot tell them apart from this text alone.

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. With add_weigh_in_with_timestamps, delete_weigh_ins, get_weigh_ins, and get_daily_weigh_ins in the sibling list, the description gives no hint about the distinguishing condition (e.g., when to add with a default/current timestamp vs. specifying timestamps).

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 explaining side effects. It only states 'Add' without disclosing whether this creates a new record, updates an existing one, requires authentication, returns the created entity, or has any other implications. The behavior is implicitly a creation, but no explicit transparency about side effects is provided.

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

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

The description is concise and straightforward, with a clear structure: a one-line summary followed by parameter listings. However, it is minimal to the point of being terse, lacking any additional explanatory content. It is not verbose, but it does not fully exploit the space to add value.

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

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

The description fails to provide broader context. It does not explain what 'specific timestamps' refers to, how they differ from the default behavior, whether both timestamps are required, or what the output of the operation will be. No output schema is described. Given the presence of a similar sibling tool, the lack of differentiation or additional context makes this incomplete for an unfamiliar user.

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 parameter descriptions are purely redundant: 'Weight value', 'Unit of weight', 'Local timestamp', 'GMT timestamp'. They add no meaning beyond the parameter names themselves. The schema already provides names and types, and the description fails to clarify units, formats, constraints, or relationships between parameters. Schema coverage is 0% and the description compensates nothing.

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 operation: 'Add a new weight measurement with specific timestamps'. It specifies the verb (add), the resource (weight measurement), and the distinguishing feature (timestamps). This distinguishes it from the sibling 'add_weigh_in' which presumably lacks timestamp support.

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

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

No guidance is given about when to use this tool versus the alternative 'add_weigh_in'. The description does not mention scenarios, prerequisites, or conditions that would make this tool preferable. The usage context is entirely absent.

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. It accurately portrays a read-only operation via 'Get' and 'Returns', and does not claim any side effects. However, it does not explicitly disclose that it does not modify data or mention error conditions, though these are largely implied by the verb.

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 exceptionally concise, consisting of two short sentences that convey the purpose and output without any redundant or extraneous information. The structure is clean 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?

Given the tool's simplicity (no parameters, no annotations, no explicit output schema), the description fully explains what the tool does and what it returns. Agents can invoke it correctly without needing additional 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 tool has no parameters, so schema coverage is effectively 100%. The description adds no parameter-specific information, but none is needed. The baseline score of 3 applies because the schema fully covers the (empty) parameter space.

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 with a specific verb ('Get') and resource ('total count of activities'), and implicitly distinguishes it from get_activities by focusing on the count instead of the list. The two sentences are concise and unambiguous.

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

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

The description implies the primary use case (obtaining a count) but does not explicitly state when to prefer this over get_activities or mention any alternative. No guidance on when not to use it is provided, leaving the decision to the agent.

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

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

No annotations are provided, so the description carries the full burden. It discloses the success response (foodId and servingId) and the 204 fallback, but does not mention potential errors, authentication, or other side effects beyond creation. This is adequate 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?

The description is well-structured with an intro, behavioral notes, and an Args list. It is slightly long but every sentence adds value, including the fallback and unit conversion reminders. No redundant or filler content.

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 schema covers all parameters and an output schema exists (per context), the description adds necessary context about the response and fallback. It tells the agent what to do with the output (use IDs for logging) and how to handle a 204. Missing minor details like uniqueness constraints, but overall complete.

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

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

The schema has no descriptions, but the Args section in the description adds meaningful detail to every parameter, including units (mg, g, mcg) and clarifications like 'NOT %DV' for micronutrients. It also specifies allowed examples for serving_unit and defaults. This fully compensates for the schema's lack of descriptions.

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 specific verb 'Create' and the resource 'custom food in the user's Garmin nutrition library'. It also differentiates from siblings by noting that the returned foodId and servingId are needed for log_custom_food, making the purpose unambiguous.

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

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

The description provides actionable guidance: it explains the fallback to get_custom_foods when a 204 is returned, and instructs converting %DV values to absolute units. While it does not explicitly say when to use this vs update or delete, the purpose is clear and these guidelines are helpful.

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 only says 'Log' and lists input constraints; it does not mention side effects, permissions, reversibility, validation failures, or whether it overwrites anything. For a write operation 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 front-loaded with the purpose, followed by a useful type_key note and a compact Args list. It repeats a few defaults already in the schema, but the extra format details earn their place. No filler or fluff.

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 7-parameter write tool with no annotations, the description covers the parameter space well and directs agents to the right reference for valid type_key values. It avoids explaining return values because an output schema exists. Missing error-handling details, but the essentials are present.

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

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

Schema description coverage is 0%, but the description compensates thoroughly: it documents every parameter with formats (YYYY-MM-DD, HH:MM), defaults (09:00, UTC, 0.0, default to type_key), and a meaningful controlled vocabulary for type_key, including a pointer to get_activity_types. This adds exactly the meaning the schema lacks.

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 and resource: 'Log a manual activity in Garmin Connect'. The phrase 'manual activity' and 'without a watch' distinguishes it from workout-creation and upload tools like create_strength_workout or upload_workout. Clear intent, no ambiguity.

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?

Explicitly gives the primary use case ('useful for activities done without a watch') and instructs the agent to use get_activity_types for valid type_key values. It does not explicitly name alternatives or exclusions, but the context is sufficient for tool routing.

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

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

With no annotations, the description carries the full burden of transparency. It discloses the primary side effect (uploading to Garmin Connect) and the behavior of heart rate targeting with both named zones and custom ranges. It does not mention failure modes or reversibility, but for a creation operation this level of transparency is reasonably complete.

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 well-structured with a headline, an explanatory paragraph, and a parameter list. The heart rate zone example is detailed and valuable but adds a bit of length; overall, it is concise and every sentence serves a purpose without fluff.

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 and the existing output schema (though not displayed), the description adequately covers the input semantics and the primary action. It does not discuss return values, but since an output schema is indicated, that is acceptable. No prerequisites or error conditions are mentioned, but they are not essential for this creation operation.

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

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

The description explicitly explains every parameter in a bulleted list, including the nuanced behavior of hr_min and hr_max (must be given together, overrides hr_zone) and the default value of hr_zone. This adds substantial meaning beyond the raw schema, which only lists types and defaults, ensuring the agent understands exactly how to supply each argument.

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 creates a continuous run workout and uploads it to Garmin Connect, with a detailed explanation of a single uninterrupted run interval. It does not explicitly contrast with sibling workout creation tools like create_walk_run_workout or create_strength_workout, but the 'continuous run' phrasing and the example parameter values make the purpose unambiguous.

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

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

The description provides clear guidance on when to use hr_zone versus hr_min/hr_max, explaining the pitfall of named zones and the requirement to pass both min and max together. However, it does not explicitly state when to choose this tool over alternative workout creation sibling tools, leaving some ambiguity about the broader selection criteria.

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

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

With no annotations, the description carries the full behavioral disclosure burden. It covers the create+upload side effect, the conversion of exercises to reps-based steps, how exerciseName is only retained when it matches Garmin's keys, and that invalid categories cause a 400 rejection. It also links to the authoritative category list, which is a strong transparency signal.

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 purpose is front-loaded in the first sentence, followed by concise behavioral details and an Args block. Every sentence adds necessary information, and the long allowed-category list is linked rather than inlined. The length is justified by the number of constraints the agent must handle.

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 2-parameter tool with no annotations and a sparse schema, the description is the only guide to correct invocation. It fully specifies the payload shape, category validation, and Garmin's exerciseName behavior. The presence of an output schema means return values need no description, and nothing critical appears 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 coverage is 0% and the schema only defines 'name' and an opaque 'exercises' array. The description compensates fully by specifying the required dict keys (name, sets, reps, rest_seconds, optional category), explaining category omission and allowed values, and documenting the failure mode. This adds essential meaning 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 states a specific verb and resource ('Create a strength workout') and immediately adds the distinctive behavior 'upload it to Garmin Connect' plus 'Each exercise becomes a reps-based step.' This clearly differentiates it from siblings like create_run_workout or create_walk_run_workout, even without naming them.

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

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

The description provides detailed parameter constraints but never tells an agent when to prefer this tool over closely related siblings such as create_run_workout, create_walk_run_workout, or upload_workout. No alternatives or exclusions are mentioned, so an agent must infer tool selection entirely from the 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?

No annotations are provided, so the description carries the full burden of disclosing behavior. It clearly states that the tool uploads to Garmin Connect and returns a new workout ID, which are the primary side effects and return value. It does not mention potential failure modes or authorization requirements, but the main behavioral traits are 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 concise, consisting of two sentences that convey the purpose and key outputs, followed by a parameter list that adds necessary semantics. No redundant or filler content is present. The structure is clear and 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?

Given the tool's moderate complexity (7 parameters) and the existence of a return value (workout ID), the description covers the essential purpose and parameters. It does not describe the output schema, but the returned ID is sufficient for many use cases. It lacks details on error handling or prerequisites, but within the context of sibling tools, it is reasonably complete.

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

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

The schema provides only titles and types with zero descriptions, so the parameter explanations in the description are essential. Each parameter is given a brief semantic definition (e.g., 'Duration of each run interval in seconds', 'Target heart-rate zone (Z1-Z5, default Z3)'), covering all seven parameters. It lacks constraints like minimum values or exact allowed enum values for hr_zone, but the core meaning is clear.

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 'Create' and the resource 'walk/run interval workout', and specifies that it uploads to Garmin Connect. The mention of 'walk/run interval' distinguishes it from sibling tools like create_run_workout and create_z2_walk_workout, making the purpose unambiguous.

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

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

The description does not provide any explicit guidance on when to use this tool versus the alternative creation tools (e.g., create_run_workout, create_z2_walk_workout) or upload tools. There is no mention of 'use this when...' or 'not for...', leaving the selection criteria implicit.

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, and it does disclose the key external side effect: upload to Garmin Connect. It also clarifies that hr_min and hr_max are used only for the description rather than setting the target, which prevents an incorrect assumption. However, it does not address duplicate names, overwrite behavior, or required permissions.

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

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

The description is two compact sections: a front-loaded purpose statement followed by a terse argument list. Every sentence contributes information, with no filler or repetition of the schema titles.

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 covers the operation, all required parameters, and the key side effect, and an output schema exists so return values need not be specified. It is only slightly incomplete in not addressing when to prefer this over sibling workout-creation or upload tools and in not documenting edge cases such as duplicate workout names.

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 parameter semantics fall entirely on the description, and the description documents all four required arguments with units and purpose. It usefully explains that hr_min and hr_max are descriptive only while the target is Z2, adding meaning the schema does not provide.

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

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

The description states a specific verb and resource: create a steady Z2 walking workout and upload it to Garmin Connect. The Z2 walking scope differentiates it from sibling tools like create_run_workout, create_strength_workout, and the more generic create_walk_run_workout.

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 use case (steady Z2 walking workout plus upload) is implied by the first sentence, but there is no explicit when-to-use guidance or exclusions. An agent is not told when to choose this tool over upload_workout, create_walk_run_workout, or create_run_workout.

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 carries the full behavioral burden because no annotations are provided. It identifies the action as destructive, but does not disclose whether the deletion is permanent or irreversible, what dependent data may be affected, whether authorization is required, or how invalid IDs are handled. For a destructive tool with zero annotation coverage, 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 very compact and well-structured: the first sentence states the operation, and the second line defines the sole parameter and how to source it. Every sentence earns its place; 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?

For a single-parameter destructive tool with an output schema present, the description supplies the essential call information: what to delete and how to get a valid ID. It lacks explicit irreversibility or edge-case caveats, but the overall operation is simple and the output schema covers return shape.

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

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

Schema description coverage is 0%, and the description meaningfully compensates by explaining that `course_id` is the ID of the course to delete and by directing the agent to `get_courses` as the reliable source of valid IDs. This adds real value beyond the bare integer field.

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

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

The description opens with a specific verb-resource pair ('Delete a course') and identifies the exact domain ('Garmin Connect'), making the intended tool unambiguous even among siblings like `delete_workout`, `delete_weigh_ins`, and `upload_course`. No other plausible interpretation exists.

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?

It gives a genuine usage hint by telling the agent to obtain course IDs from `get_courses`, which is a useful prerequisite. However, it does not explicitly say when to use this tool versus alternatives or state any exclusions. The usage context remains mostly implied rather than explicitly spelled out.

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 present, the description carries the burden. It discloses the permanent nature of the deletion and the requirement that the food not be in active use, which are important behavioral traits. It does not cover error handling or side effects, but the essential behaviors are clearly 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 concise, starting with the purpose, then a brief note on constraints, and finally a clear Args section. No redundant information or filler; every sentence contributes to understanding the tool's use.

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

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

Given the output schema exists, the description need not explain return values. It includes the essential context: action, resource, ID sourcing, and a critical precondition. It lacks explicit error scenarios but remains sufficient for correct 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 single parameter food_id is fully described: it identifies the custom food to delete, is a 32-char hex string, and can be obtained from get_custom_foods or create_custom_food. This adds substantial meaning beyond the schema's bare type definition.

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

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

Clearly states it deletes a custom food from the user's Garmin nutrition library, using the verb 'delete' and specifying the resource (custom food). It also adds the key detail that deletion is permanent, fully covering the action's intent.

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

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

Provides explicit guidance to use get_custom_foods to find the foodId, and mentions the precondition that the food must not be actively referenced in a logged meal. This gives clear context on when and how to use the tool, though it doesn't mention alternative tools for non-deletion operations.

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 explicitly says 'Permanently removes', disclosing the destructive and irreversible nature. It also clarifies that it works for both QUICK_ADD and REGULAR_LOG entry types. Since no annotations are provided, the description carries the full burden and does it well.

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?

Three concise sentences plus a compact Args list. The description is free of fluff and delivers the essential information in a well-organized structure, making it easy for an agent 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?

Covers the core action, parameter sourcing, and format. It doesn't mention error handling or return values, but for a delete operation the description provides enough context for an agent to invoke it correctly. The absence of an output schema in the prompt reduces the need for return details.

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 no descriptions (0% coverage). The tool description compensates by explaining log_id as the entry ID from get_nutrition_daily_food_log, and meal_date in YYYY-MM-DD format. It also specifies log_id is a 32-char hex UUID. This adds meaningful detail 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?

States exactly what it does: delete a food log entry. The verb 'Delete' and resource 'food log entry' are specific, and it distinguishes from siblings like delete_weigh_ins or delete_course by targeting the nutrition log.

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

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

Provides a clear prerequisite: 'Use get_nutrition_daily_food_log to find the logId and date.' This tells the agent how to obtain the required parameters. It doesn't explicitly say when not to use this tool, but the guidance is actionable and sufficient for a delete operation.

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 burden. It states the destructive action, but does not disclose whether deletion is permanent, what happens if delete_all is false, or any return/error 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?

Short, direct, front-loaded with the action and argument list; no unnecessary 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?

The tool lacks output description and leaves delete_all false ambiguous; for a destructive operation, more context is needed to be 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?

It adds date format and describes delete_all as controlling whether all measurements for the day are deleted. It does not explain the false behavior or default, and there are no property-level descriptions in 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?

Clearly identifies the action (delete), the target (weight measurements), and the scope (specific date). It is distinct from sibling add/get weigh-in 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 purpose statement implies the use case: call this when deleting weight measurements for a date. It does not explicitly mention alternatives 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?

No annotations are provided, so the description carries the full burden. It explicitly discloses that deletion is permanent, which is the critical behavioral warning for a destructive operation. It does not mention side effects on scheduled workouts, but the permanence statement is valuable and non-obvious.

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

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

The description is compact and front-loaded: the main action, the permanent effect, and the only parameter are stated in three short sections. There is no filler or redundant 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 single-parameter tool, the description is mostly adequate for invoking it correctly. However, it omits important context about the sibling delete_workouts, whether deleting also unschedules workouts, and any authorization requirements. The output schema presence makes missing return-value details acceptable.

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

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

The schema only defines workout_id as an integer with 0% description coverage. The description compensates by explaining the parameter's role and pointing to get_workouts as the source of valid IDs, which is actionable guidance beyond the schema field 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?

Clearly identifies the action as deleting a single workout from Garmin Connect and emphasizes that the removal is permanent. It does not explicitly contrast with the sibling delete_workouts, but the singular wording and single workout_id make the scope reasonably 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?

Provides a useful prerequisite by directing the agent to get IDs from get_workouts. However, it does not mention when to prefer this tool over delete_workouts or unschedule_workout, nor does it explain scenarios where deletion may be inappropriate.

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 clearly labels the operation as permanent removal, which is essential for a destructive tool, and notes the batch nature of the call. It does not discuss failure behavior or permissions, but the core destructive consequence is disclosed.

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 front-loaded with the key purpose, then adds the permanence warning and a compact Args explanation. No extraneous content.

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 deletion tool, the description plus schema covers the action, the permanent effect, and the ID source. An output schema exists, so return-value details are not required. It could still mention the singular delete_workout alternative or what happens with invalid IDs, but nothing critical is 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 coverage is 0%, so the description compensates by explaining that workout_ids is a list of workout IDs and pointing to get_workouts as the source. This is sufficient for the only 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 states a specific action and resource: deleting multiple workouts from Garmin Connect and permanently removing them from the workout library. The word 'multiple' and 'single call' distinguish it from the sibling delete_workout, which appears to handle a single workout.

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 makes clear this is for deleting multiple workout IDs at once and tells the agent to obtain IDs from get_workouts. It does not explicitly mention when to use the singular delete_workout instead, so there is a small exclusion 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, but the description fully discloses behavioral details: it saves a file to disk, overwrites existing files, supports a one-off output directory override that is not persisted, and returns a needs_setup status when no directory is configured.

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 well-structured and front-loaded, but the directory resolution and needs_setup behavior are described twice in nearly identical terms, adding minor 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 covers the key operational context and user prompting flow, but it does not describe the actual return value on success or the response schema, leaving some ambiguity about what the caller receives.

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?

Although the schema description coverage is 0%, the prose explains all three parameters: activity_id is the Garmin activity ID, format has default 'fit' and supported values, and output_dir is an optional non-persisted override.

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 downloads an activity and saves it to disk as a file. It identifies the resource (activity), the action (download/save), and the output (file), which differentiates it from related tools like download_course_gpx and download_workout.

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 explicit guidance on when to use the tool: it explains supported formats (fit, gpx, tcx, csv), the directory resolution precedence, and the fallback needs_setup behavior with instructions to ask the user and call set_fit_download_dir.

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

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

With no annotations, the description carries the burden of explaining behavior. It discloses that binary data is not returned directly but confirms availability, which is a meaningful behavioral trait. However, it does not mention permissions, side effects, 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 concise and front-loaded with the primary purpose. It uses a clear first line followed by a brief elaboration and an explicit Args section, making it easy to scan and understand.

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

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

The tool is simple, and the description covers the core action and an important limitation. While it does not specify the exact return value, the statement 'confirms the workout is available' implies a confirmation response, which is sufficient 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 only the parameter name and type (integer) with no description. The description adds the explanation 'ID of the workout to download', which clarifies the parameter's purpose but provides no additional detail about constraints, format, or default behavior.

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

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

The description clearly states the tool downloads a workout as a FIT file, naming the resource (workout) and action (download). It is distinct from sibling tools like download_course_gpx and download_activity_file, which target different resources.

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

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

The description does not indicate when to use this tool versus alternatives such as download_activity_file or upload_workout. It mentions a limitation (binary data cannot be returned) but offers no explicit guidance on selection criteria or preconditions.

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?

Because no annotations are provided, the description carries the full burden, and it delivers: pagination behavior, newest-first ordering, event_type semantics, common values, and the important caveat about 'uncategorized' activities and Peloton imports. This goes well beyond the minimal 'retrieves a list' statement.

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 well-structured and front-loaded, with purposeful paragraphs for purpose, usage, and parameter details. It is slightly redundant because the opening sentence and the second sentence both convey pagination support, but the overall length is justified by the valuable event_type guidance.

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, the description doesn't need to spell out return fields—it covers the important contextual points: pagination defaults, ordering, event_type filtering, and relationship to the date-filtered sibling. An agent has everything needed to call this 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 0%, but the description fully compensates with an Args section: start is the starting index with default 0, limit is max activities with default20 and max100. This is exactly the meaning an agent needs beyond the bare integer types.

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

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

The description names a specific verb and resource ('Get activities'), and adds critical distinguishing detail: paginated list, ordered newest-first. It also explicitly contrasts itself with get_activities_by_date, so an agent can select it without opening schemas.

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?

It tells the agent exactly when to use the tool: 'when you do not need to filter by date range' or as a complement to get_activities_by_date. It also gives concrete filtering guidance for event_type, which is rare and highly actionable.

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 behavioral burden. It clearly discloses newest-first ordering, the pagination contract, the total_count API limitation, and nuanced event_type semantics including the absent-field edge case.

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 substantial but every paragraph adds necessary operational detail: pagination behavior, API constraints, event_type filtering guidance, and parameter formats. It is front-loaded with a clear purpose before caveats.

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 5-parameter tool with no annotations, the description covers invocation details, pagination mechanics, filtering semantics, and known API limitations. The output schema handles return-value documentation, so nothing essential is 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%, and the description fully compensates. It documents date format for start_date/end_date, examples for activity_type, zero-based indexing for page, and the max/default for page_size. Every parameter receives actionable meaning.

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

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

Description states a specific operation: 'Get activities between specified dates,' with pagination support. The verb, resource, and date-range scope are clear, distinguishing it from sibling tools like get_activity or count_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?

Provides strong practical guidance: explains when pagination is needed, how to walk pages with has_more/next_page, and how to interpret event_type for filtering. However, it never explicitly contrasts this tool with sibling alternatives or states when to prefer another 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the operation is a read ('Get') but does not describe the return shape, pagination, date inclusivity, or any other runtime behavior. This is a minimal disclosure for a tool with zero annotation support.

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

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

The description is short, front-loaded with the core purpose, and includes a clean Args block for the parameter. Every element earns its place without redundancy.

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

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

For a simple one-parameter getter with an output schema present, the description provides enough to invoke the tool correctly: the operation, the resource, and the date format. It lacks sibling differentiation and behavioral detail, but the low complexity and output schema reduce the burden.

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

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

Schema description coverage is 0%, but the description compensates by specifying the exact date format (YYYY-MM-DD), which is the key semantic information for the single required parameter. It adds meaning beyond the schema's bare 'Date' title.

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 ('Get') and resource ('activities') scoped to a date. However, it does not differentiate from the sibling tool get_activities_by_date, which appears to serve a nearly identical purpose.

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

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

The phrase 'for a specific date' implies this tool is for date-scoped activity retrieval, but there is no explicit guidance on when to choose this over get_activities, get_activities_by_date, or count_activities. Usage context is implied rather than 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?

With no annotations, the description carries the behavioral disclosure burden. It goes beyond a simple 'get' by explaining the returned fields and the event_type behavior, including that the field is omitted for old activities. It does not cover errors, permissions, or rate limits, but for a read-only single-resource tool it provides meaningful 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 compact and well-structured, front-loading the purpose and then adding return details and the argument definition. There is slight redundancy between 'Get detailed information' and 'Returns a comprehensive summary,' but no filler or unnecessary content.

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

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

Given the simple single-parameter schema and the presence of an output schema, the description is largely complete for invoking the tool correctly. It covers the core return fields and a notable edge case (old activities lacking event_type). Explicit guidance on when to use this over sibling activity tools would make it 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%, but the description compensates by explicitly documenting activity_id as 'ID of the activity to retrieve.' This adds meaning beyond the schema's bare type/title, though it could clarify accepted ID formats or whether integer/string forms are interchangeable.

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 opens with 'Get detailed information for a single activity,' naming a specific verb, resource, and singular scope. This clearly distinguishes it from sibling list tools like get_activities and activity-specific tools like get_activity_splits.

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 'single activity' implies use when you have an activity_id and need one activity's details, but no explicit guidance is given about when to choose this over alternatives like get_activities or get_activity_splits. Usage context is implied rather than 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?

With no annotations, the description carries the burden of behavioral disclosure. 'Get' implies a read-only operation, which is appropriate, but it does not specify what happens for non-strength activities, whether an empty result is possible, or any error 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?

The description is concise and front-loaded with the main purpose. The Args section is slightly redundant with the schema, but it is not bloated or confusing.

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

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

For a one-parameter getter with an output schema, the basics are covered: what the tool retrieves and which parameter to pass. However, it lacks any context about activity type expectations, empty results, or relationship to similar tools, leaving some ambiguity 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 0%, so the description must compensate. It does explain that activity_id is the ID of the activity to retrieve sets for, but this adds only modest meaning beyond the parameter name and schema type.

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

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

The description clearly states a specific verb and resource: 'Get exercise sets for strength training activities.' It does not explicitly compare against siblings, but the resource is distinct enough that an agent can infer what this tool does.

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

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

The phrase 'for strength training activities' implies the intended use case, but the description gives no explicit guidance on when to choose this over related activity data tools like get_activity_splits or get_activity_fit_data, and no exclusions 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?

With no annotations provided, the description carries the full burden of transparency. It discloses a side effect—'Warning: adds significant data volume for long rides'—and hardware dependencies that affect success. It does not explicitly state that the operation is read-only or non-destructive, but given the lack of annotations and the 'download and parse' wording, this is a reasonable transparency level.

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?

Despite being lengthy, the description is well-organized with bullet points and sections (shift quality, notes, args). It packs substantive information without redundancy or filler. Each sentence contributes to understanding the tool's capabilities, prerequisites, or parameters, making the length appropriate for the complexity of the data returned.

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 comprehensive for an agent: it details the output categories (DI2 events, cycling dynamics, climb detection, etc.), defines shift quality terms, lists hardware requirements, and explains arguments. No output schema is provided, but the enumerated data types give sufficient context for expected results. The inclusion of a dedicated note about include_records ensures the agent understands the trade-off. Overall, nothing essential is 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?

The schema has zero descriptions for its properties, so the description fully compensates. It explicitly explains activity_id as 'Garmin activity ID' and include_records as 'Include full per-second time series (default False)' with a data volume warning. This covers both parameters completely, leaving no ambiguity about their meanings or defaults.

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 clear verb+resource: 'Download and parse FIT file for an activity to expose advanced cycling data.' It distinguishes itself from the standard REST API by stating it returns data 'not available through the standard REST API,' and enumerates specific advanced metrics such as DI2 shifting, cycling dynamics, and power curves. This makes the tool's unique purpose obvious relative to the many sibling 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 description provides useful usage guidance by noting hardware prerequisites ('DI2 data requires Shimano Di2 / SRAM eTap') and a warning about include_records adding significant data volume. It also states that it returns data not available through the standard REST API, which tells the agent when to prefer this tool. However, it does not explicitly name alternative sibling tools or give conditional 'use this vs. that' instructions, so it falls short of fully explicit when/when-not 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?

The name and description imply a read-only operation, but no explicit statement about side effects or lack thereof is made. Since annotations are absent, the description carries the full burden; it does not clarify whether the returned gear data includes all fields or just summaries, nor does it mention any rate limits or authentication requirements.

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

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

The description is extremely concise, consisting of one clear sentence plus the parameter explanation. No unnecessary words or redundant information is present.

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

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

For a simple retrieval tool, the description is adequate. It does not cover return value details or error conditions, but since an output schema exists (as indicated by context), the lack of return-value explanation is acceptable. The description covers the essential purpose and 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 explicitly explains the sole parameter: 'ID of the activity to retrieve gear data for'. This provides clear meaning for activity_id. However, it does not specify whether the ID is numeric or string-based, which could cause minor ambiguity given the anyOf type in 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 action: 'Get gear data used for an activity' and identifies the specific resource (gear for an activity). This verb+resource combination is unambiguous and distinct from sibling tools like get_gear or add_gear_to_activity.

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

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

No guidance is provided on when to use this tool versus alternatives such as get_gear (list all gear) or add/remove gear tools. The description does not mention any conditions, prerequisites, or scenarios that would make this tool the preferred 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?

No annotations are provided, so the description carries the full behavioral burden. It only restates the get operation and data scope; it does not clarify read-only behavior, timezone conversion semantics, whether data is available for all time zones, or any permissions or rate limits. The output schema may describe the return shape, but the description itself adds little behavioral transparency 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?

The description is compact and front-loaded: the core purpose appears in the first sentence, followed by a short Args block. There is no fluff or repetition of schema details, so every part of the description 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?

Complexity is low with one required parameter, and an output schema exists, so the description does not need to explain return values. However, with no annotations and no usage guidance, the description leaves timezone semantics and when-to-use questions unanswered. It is minimally complete for a simple getter but not richly contextual.

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 add some semantic value with 'activity_id: ID of the activity to retrieve heart rate time zone data for,' which explains the parameter's role. However, it does not clarify accepted formats beyond the schema's anyOf, how to find or interpret the ID, or behavior when the activity does not exist, so the compensation is minimal though adequate for a single obvious 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 names the specific operation: 'Get heart rate data in different time zones for an activity.' This gives a clear verb, resource, and scope. It distinguishes the tool from the closely named sibling get_activity_power_in_timezones by specifying heart-rate data rather than power 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 guidance about when to use this tool versus alternatives such as get_heart_rates, get_activity_splits, or get_activity_power_in_timezones. The only contextual clue is 'for an activity,' which implies an activity_id is needed but does not explain when this endpoint 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, the description carries full burden. It discloses output details (time spent, watt thresholds, duration) and prerequisites (power meter, FTP). It does not state side effects, but the read-only nature is implicit from the name and description, and there is no contradiction.

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

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

The description is concise and well-structured: a one-sentence summary, output details, prerequisites, and parameter explanation. No redundant or vague wording.

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

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

Provides essential context: what it returns, prerequisites, and parameter meaning. It does not mention error cases or what happens when no power data exists, but these are minor gaps given the tool's simplicity and the presence of related siblings with similar patterns.

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

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

The single parameter activity_id is clearly explained in the Args section as 'ID of the activity to retrieve power zone data for'. Although the schema lacks description, the description fully compensates, making the parameter's meaning unambiguous.

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 action ('Get power distribution across training zones') for a specific resource ('an activity'). This distinguishes it from sibling tools like get_activity_hr_in_timezones or get_activity_splits.

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

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

Provides condition 'Requires a power meter' and explains FTP basis, which tells the agent when this tool is appropriate. It does not explicitly mention when to choose an alternative, but the unique purpose is clear enough.

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 only states the action and parameter, giving no information about side effects, permissions, rate limits, or whether the operation is read-only. The verb 'get' implies a read, but this is not explicit, and there is no mention of error conditions or return behavior. This is a minimal disclosure that does not go beyond the literal action.

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 and front-loaded, with the core purpose stated in the first sentence. The parameter explanation is redundant with the schema but does not add fluff. It is well-structured as a docstring, though the brevity limits the information conveyed. For a one-parameter tool, this length is appropriate, but it could be more informative without losing efficiency.

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 incomplete in the context of the tool ecosystem. It does not clarify what type of splits are returned (e.g., lap splits, typed splits, summaries), nor does it address the existence of sibling tools that might be more appropriate for specific use cases. The presence of an output schema mitigates the need to describe return values, but the tool's role among the many split-related tools is ambiguous. An agent cannot confidently choose this tool over its siblings without additional information.

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 says 'ID of the activity to retrieve splits for', which adds only slightly to the schema's 'Activity Id' field. It explains the parameter's role but provides no additional context about format, constraints, or typical usage. With 0% schema description coverage, the description should compensate with richer semantics, but it essentially repeats what the parameter name already conveys. This is insufficient.

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-resource pairing: 'Get splits for an activity'. It identifies the resource (activity splits) and the action (get). However, it does not differentiate from closely related siblings like get_activity_typed_splits or get_activity_split_summaries, which likely also retrieve split data. This is a clear purpose but lacks the specificity to distinguish among similar 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 description provides no guidance on when to use this tool versus alternatives. It does not mention any conditions, prerequisites, or exclusions, nor does it reference sibling tools. An agent must infer the appropriate usage, which is risky given the number of split-related tools available in the sibling list.

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

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

There are no annotations provided, so the description carries the full burden of behavior disclosure. It only says 'get' without mentioning return format, volume, pagination, error cases, or any read-only cautions, leaving the agent to infer from the 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 appropriately short and front-loaded with the purpose, but the Args block largely duplicates the input schema, adding no real value. Both sentences together are concise, but not every line strongly 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?

This is a simple one-parameter read tool, so the minimum is present, but the description does not clarify the meaning or format of 'split summaries' relative to sibling functions like get_activity_splits. Since an output schema exists, return documentation is not strictly needed, yet more context about what the summaries represent would make the description 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?

With schema_description_coverage at 0%, the description should compensate for missing parameter documentation. It does say 'activity_id: ID of the activity to retrieve split summaries for', which adds a little semantic context over the schema name. However, it does not explain the accepted types or where the activity_id comes from.

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 split summaries for an activity', so the agent knows what the tool does at a basic level. However, it does not distinguish this from the closely related siblings get_activity_splits and get_activity_typed_splits, leaving a subtle terminology gap.

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 contains no guidance on when to use this tool instead of get_activity_splits or get_activity_typed_splits. It only repeats the activity_id parameter in the Args block, which is not a usage guideline.

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 provides no information about side effects, read-only status, data scope, or any behavioral characteristics. With no annotations present, the description itself should disclose such details, but it is entirely silent.

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 extraneous words. It is concise and well-structured, conveying the essential information without padding.

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 GET operation with one parameter, the description is adequately complete. The lack of output schema or annotations lowers the burden, and the description covers the core functionality. A brief mention of return type would be beneficial but is not strictly necessary 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?

The single parameter activity_id is clearly described as 'ID of the activity to retrieve typed splits for'. The meaning and purpose are unambiguous, fully satisfying the parameter explanation requirement.

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 a specific resource ('typed splits'), making the primary purpose clear. However, it does not explicitly differentiate from sibling tools like get_activity_splits or get_activity_split_summaries, so some ambiguity remains about what 'typed' adds.

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

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

No guidance is provided on when to use this tool versus alternatives such as get_activity_splits or get_activity_split_summaries. The description offers no context for selecting this tool over others.

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 carry the behavioral disclosure. It does indicate a read-only retrieval ('Get', 'Returns a list') and the data scope ('supported by Garmin Connect'). However, it leaves out details such as whether the list includes custom or localized activity types, which could matter depending on the agent's task.

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 two sentences: the first is a direct, front-loaded statement of the tool's function, and the second adds a relevant use case. Every word earns its place with no filler or repetition.

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

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

Given the tool has no parameters and an output schema is available, the description adequately covers what the tool returns and why it is useful. No critical information needed for correct invocation is 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?

The tool has zero parameters, and schema description coverage is 100%. The description correctly adds no parameter-specific information because none is needed, matching the baseline for parameterless 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 states a specific action and resource: 'Get all available activity types' and clarifies it returns 'a list of all activity types supported by Garmin Connect'. This clearly distinguishes it from sibling tools that set activity types or retrieve activity records.

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

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

The description explicitly identifies a practical context—'useful for filtering activities by type'—which gives the agent a clear cue for when to invoke it. It does not mention exclusions or alternatives, but the intended use case is sufficiently clear.

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

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

With no annotations provided, the description carries the full burden, and it does so thoroughly. It explains that the raw endpoint returns Fahrenheit without a unit indicator, that this tool converts temperatures to the account's display unit, and that wind speed is passed through unconverted with its own unit label. This gives the agent essential behavioral context 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?

The description opens with a clear one-sentence purpose and then uses short, organized paragraphs for unit-conversion behavior, followed by an Args section. Every sentence adds useful information, and the structure makes the content 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?

Given the tool has only one required parameter and an output schema is present, the description covers all essential context: what the tool does, what the activity_id means, and the key behavioral quirk around unit conversion. Nothing critical is missing for an agent to invoke it correctly.

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

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

The input schema has no parameter descriptions, so the description must compensate. The Args section says 'activity_id: ID of the activity to retrieve weather data for,' which clarifies which activity the ID refers to beyond the schema title 'Activity Id.' For a single, self-explanatory identifier parameter, this is sufficient semantic 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 opening sentence states a specific verb and resource: 'Get weather data for an activity.' This clearly distinguishes the tool from the many activity-related siblings, none of which are about weather. The resource and scope are exactly what an agent needs to select it.

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

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

The description makes the usage context clear: use this when weather data for a particular activity is needed. It does not name exclusions or alternative tools, but the purpose is specific enough that an agent can identify this as the weather-specific activity getter among the 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?

With no annotations provided, the description carries the full burden. It states that the tool 'returns' challenges, indicating a read operation, but does not disclose potential errors, rate limits, or any additional behavior beyond the basic retrieval. The differentiation from badge challenges adds some context but lacks thorough behavioral 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 concise, consisting of two sentences that front-load the purpose and then list the parameters. There is no fluff or redundancy; every sentence adds value.

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

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

The tool is positioned within the context of challenges by explicitly contrasting with official badge challenges, and the parameters are fully explained. However, the description does not mention the response structure or any related usage notes, leaving a minor gap in completeness for an agent encountering this tool for the first time.

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 meaningful semantics for both parameters: 'start' is the starting index for pagination, and 'limit' is the maximum number to return (with a max of 100). This goes beyond the bare schema types and defaults, giving the agent clear guidance on how to use the 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 that the tool retrieves user-created social/group challenges, distinguishing them from official Garmin badge challenges. The verb 'Get' and specific resource type make the purpose unambiguous.

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

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

The description explicitly notes that these challenges are different from official badge challenges, which implies a contrast with sibling tools like get_badge_challenges. However, it does not explicitly state 'use this when you need user-created challenges, use the other for official ones,' leaving some inference to the agent.

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

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

There are no annotations, and the description does not disclose any behavioral traits such as read-only nature, data source, or potential side effects. Since nothing is disclosed beyond the basic action, the description fails to inform the agent about the tool's 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?

The description is extremely concise and to the point, containing only the essential information about the parameter format. There is no redundancy or irrelevant detail, making it efficient for the agent 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?

The description lacks essential context about what 'wellness events' actually represents, what the response structure will be, or how this data is used. Without output schema details or examples, the agent cannot fully anticipate the tool's behavior or 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?

The description provides the date format 'YYYY-MM-DD' in the Args section, which adds meaning beyond the schema's bare type 'string'. This helps the agent correctly format the parameter, but it is the only parameter and the description is otherwise minimal.

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 verb 'Get' and a resource 'daily wellness events data', but the term 'wellness events' is ambiguous and could refer to various types of data (e.g., stress, body battery, all-day stress). It does not clearly differentiate from sibling tools like get_all_day_stress or get_body_battery_events.

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 over alternatives. The description gives no conditions, examples, or hints about appropriate usage scenarios, leaving the agent to guess based on the name alone.

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

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

No annotations are present, so the description carries the full burden. It states only the action 'Get' without clarifying whether it is read-only, if there are side effects, or how it behaves on errors or missing data. The name implies a read operation but this is not explicit.

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, consisting of one sentence and a parameter format line. No unnecessary information is included, and every word adds value.

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

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

The description is complete for a simple getter in terms of its action and parameter, but it does not describe the output format, data structure, or possible error conditions. Given the simplicity, this is acceptable but leaves some gaps.

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

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

The input schema has a single required parameter 'date' with no description. The description adds the format 'YYYY-MM-DD' but does not explain the semantic meaning (e.g., the specific day for which stress is requested). This is minimal but adequate for a straightforward date 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 all-day stress data' clearly states the action (get) and the resource (all-day stress data). It is specific enough to distinguish from generic stress queries, though it does not explicitly differentiate from sibling tools like get_stress_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?

No guidance is provided on when to use this tool versus alternative stress-related tools such as get_stress_data, get_stress_summary, or get_weekly_stress. The description does not mention conditions, fallbacks, or selection criteria.

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

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

The description is a simple retrieval operation with no side effects, but it does not explicitly state that it is read-only or mention any permissions, rate limits, or error conditions. Since annotations are absent, the description carries the burden and provides basic transparency but lacks depth.

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

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

The description is concise, with a clear one-sentence purpose, a brief explanation of returns, and a simple 'Args:' section. No unnecessary words or redundant 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?

Since the tool has an output schema (as indicated by 'Has output schema: true'), the description need not enumerate output fields. However, it could briefly mention that the result is a paginated list of challenges, but the pagination parameters already imply that. Overall, the description is sufficient given the 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?

Both parameters are explained in the description: 'start' is the pagination index starting at 1, and 'limit' is the maximum number of results with a default of 20 and a max of 100. This adds meaningful detail that the schema does not provide (the schema only includes type and default).

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

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

The description clearly states it retrieves official Garmin badge challenges that are available to join, and distinguishes them from earned badges, ad-hoc challenges, and non-completed challenges by explicitly mentioning 'available to join' and 'monthly/seasonal'.

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

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

No explicit guidance is given about when to use this tool versus other badge-related tools like get_badge_challenges or get_earned_badges. The description implies its use case but does not state conditions or alternatives, leaving the agent to infer.

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 explaining behavior. It clearly indicates the scope (user's joined challenges) and the return content, but it does not explicitly state that the operation is read-only or mention any side effects, authentication requirements, or rate limits. However, the verb 'Get' makes the read-only nature implicit.

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

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

The description is concise and well-structured: a single sentence for the main purpose, one for the return details, and a clear breakdown of parameters. There is no extraneous information, making it easy for an agent to parse quickly.

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

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

The description provides enough context for an agent to know exactly what the tool does and what parameters mean. Since an output schema is indicated as existing, the description does not need to enumerate the return structure. It covers the essential information for correct 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 schema only provides types and defaults for 'start' and 'limit', but the description adds meaningful semantics: 'start' is the starting index (1-based) and 'limit' is the maximum number to return with a default of 20 and max of 100. This fully explains the parameters 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 states the tool retrieves all badge challenges the user has joined, including both completed and in-progress ones. It also lists the specific data returned (progress, completion status, earned dates), making the purpose unambiguous and distinct from sibling tools like get_earned_badges or get_available_badge_challenges.

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 when to use this tool—when you need the user's full history of joined badge challenges—but it does not explicitly contrast it with alternatives such as get_non_completed_badge_challenges or get_available_badge_challenges. The guidance is inferred rather than 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 must carry the behavioral disclosure burden. It only says 'Get blood pressure data' and lists parameter formats; it does not disclose read-only behavior, date-range inclusivity, timezone handling, or response shape. The agent cannot infer side effects or edge-case 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?

The description is short and free of irrelevant content. The core purpose is front-loaded and the argument details are listed cleanly. It could use a sentence or two more of behavioral context, but as written it is economical.

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 only two required date parameters and an output schema present, the tool does not need an explanation of return fields. Yet the complete lack of usage guidance and behavioral transparency leaves gaps: the agent is not told how to interpret the date range, whether results are aggregated or raw, or whether there are any constraints. This is a minimal viable description, not a complete one.

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 only parameter names and string types, so the description adds the YYYY-MM-DD format for both date arguments. This is helpful but minimal: it still omits whether the date range is inclusive, what time of day applies, or how invalid dates are handled. For a tool with 0% schema coverage, the compensation is partial.

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

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

The description states a specific verb and resource ('Get blood pressure data'), and the resource name distinguishes it from sibling tools like set_blood_pressure. However, it does not go beyond the tool name to describe what the returned blood pressure data contains or how it is scoped, so it is clear but minimally informative.

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, nor any exclusions or prerequisites. Sibling tools include several health-data getters and set_blood_pressure, but the description does not help the agent choose this one over those or clarify whether it is the only blood-pressure read 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 provided, the description carries the full burden of behavioral disclosure. It implies a read operation but does not explain event semantics, data availability, date-range behavior, or any other runtime characteristics beyond taking two dates.

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 short and well-structured, front-loading the tool's purpose and then cleanly listing arguments. It avoids filler, though the argument section mostly restates schema property names.

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 two-parameter read tool with an output schema present, this is minimally viable. The description is incomplete in that it never differentiates from get_body_battery_events, and the meaning of 'events' is unexplained, creating a real selection risk.

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 add meaning by exposing the YYYY-MM-DD format and naming start/end as a date range, but it stops short of clarifying inclusivity, timezone handling, or max range limits.

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 action and resource: 'Get body battery data with events'. However, the phrase 'with events' is ambiguous, and the close sibling get_body_battery_events exists, so the description does not clearly distinguish this tool from that one.

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

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

No guidance is given for when to use this tool versus get_body_battery_events or other health-data getters. The description only lists arguments, leaving the agent to infer the appropriate use case.

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 gives no information about side effects, read-only nature, return format, or any behavioral details. Since annotations are absent, the description bears full responsibility and fails to disclose anything beyond the action name.

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

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

The description is extremely concise, with no redundant words or fluff. It directly states the purpose and parameter format, making it highly efficient.

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 many similar tools (e.g., get_body_battery, get_body_composition), the description lacks context about what 'events' specifically means, what the output looks like, or how it differs from siblings. No output schema is provided, leaving the user without a complete picture.

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

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

The single parameter 'date' is explained with a format specification 'YYYY-MM-DD' in the docstring, which is sufficient for usage. However, no further semantic details (e.g., timezone handling) are provided, but the format note meets the basic need.

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 'Get' action on 'body battery events data', identifying the resource and verb. However, it does not differentiate from the sibling tool 'get_body_battery', so purpose is clear but not fully distinct.

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 'get_body_battery' or which conditions apply. The description just restates the function name without any context for selection.

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

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

With no annotations, the description alone must convey behavior, but it only states that data is retrieved. It does not disclose read-only status, potential errors, or any side effects, leaving the agent without information about consequences of invoking the tool.

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

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

The description is brief and direct, leading with the purpose and followed by parameter details. It avoids redundant information and is 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?

The description covers the tool's function and all parameters, and since an output schema exists, it need not describe return values. However, it lacks any examples or edge-case notes, which could be useful but are not essential.

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 fully explains both parameters: start_date is required and can be a single date or the start of a range, and end_date is optional and completes the range. It also specifies the YYYY-MM-DD format, which is not present in 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 action ('Get') and resource ('body composition data') in the first sentence, making the tool's purpose unambiguous. It also specifies the date-based scope, which distinguishes it from other data retrieval 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 description implies when to use this tool (when body composition data is needed) but does not explicitly compare it to alternatives like get_weigh_ins or get_stats_and_body. No conditions or exclusions are provided, so guidance is minimal.

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

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

No annotations are present, so the description carries the full burden. It indicates a read-only operation returning a curated list of fields, which is transparent about the result. It does not mention error handling or rate limits, but the behavior is clear enough for a simple list tool.

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

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

The description is concise, using two sentences to convey purpose and output fields. It is well-structured and free of unnecessary detail.

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 names the specific fields returned, which covers the output structure. However, it does not mention pagination or limits, which could be relevant for a list endpoint. Still, for a simple listing tool, it is reasonably 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?

There are no parameters, so schema coverage is 100% (empty). Per the rubric, the baseline is 3 since the description does not need to elaborate on absent 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: to list all courses saved on Garmin Connect. It also specifies the returned fields, distinguishing it from related tools like get_course_details or delete_course.

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

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

The description does not explicitly mention when to use this tool versus alternatives. It implies a simple 'list all' operation, but lacks guidance on scenarios like needing a specific course or filtering options, so usage guidance is minimal.

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 responsibility. It clearly indicates this is a read-only lookup and mentions returned fields, but it does not explicitly state that no data is modified or describe pagination edge 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?

The description is succinct and well-structured, leading with the main purpose, followed by usage guidance and parameter details. It avoids unnecessary fluff.

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 list/search tool with an output schema, the description provides sufficient context: it identifies user-specific custom foods, explains the purpose of returned IDs, and directs users to the correct sibling tool for branded foods. No essential information is 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?

The schema has no parameter descriptions, but the Args section explains all three parameters: search filters by name, start is the pagination index, and limit is the maximum result count. Defaults are also included.

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: search or list the user's custom foods. It also distinguishes this tool from search_foods, which handles branded catalog foods.

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?

It explicitly instructs to use the search parameter before creating duplicates and notes that the response includes foodId and servingId for log_custom_food. It also names search_foods as the alternative for branded foods, so usage guidance is concrete.

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 carry behavioral disclosure. It correctly states the tool returns a list of valid units, implying a read-only, side-effect-free operation. However, it does not detail pagination, auth requirements, or whether the list is exhaustive, although for a simple lookups these are minor gaps.

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

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

The description is compact and front-loaded with the main statement, followed by a clarifying detail with examples. The opening sentence closely mirrors the tool name, causing slight redundancy, but the rest 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?

This is a simple, parameterless lookup with an output schema present, so the description is nearly complete. It conveys the return concept and its use case, which is enough for an agent to call it correctly; nothing important is missing for this level of 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 has zero parameters, and the schema coverage trivially covers them. The description adds value by explaining what the returned units are used for, even though no parameter semantics are needed. Baseline 4 for 0 params 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 states a specific verb ('Get') and resource ('available serving units for custom foods'), and clarifies with examples (G, ML, OZ). It is clearly distinct from sibling tools like get_custom_foods, so an agent can tell the difference without opening schemas.

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

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

The description explicitly frames the tool as a lookup to be used 'when creating custom foods,' giving clear context for when to call it. It does not name alternative tools or exclusion conditions, but no obvious alternative exists for this resource, so the guidance is sufficient.

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 clearly indicates a read-only, no-argument operation returning the latest cycling FTP estimate from Garmin, which is sufficient for a simple getter; it does not detail edge cases like missing data or sync delay, but the output schema covers 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 very short and front-loaded, but the first sentence and second sentence partly restate the same idea ('Get the latest' vs. 'Returns the most recent'). Still, it is compact and 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?