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 describes the basic function and date handling but does not cover important traits like whether this is a read-only operation (implied by 'Get'), potential rate limits, authentication needs, error handling, or the format of the returned schedule data. For a tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that front-loads the core purpose ('Get MLB schedule for a specific date') and includes essential details (date format, default behavior) without any waste. Every part earns its place, making it appropriately sized and well-structured.

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 low complexity (one optional parameter) and no annotations or output schema, the description is minimally adequate. It covers the purpose and parameter semantics but lacks details on behavioral traits like response format, error cases, or usage constraints. Without an output schema, it should ideally explain return values, but it does not, leaving gaps in completeness for a tool that might return complex schedule data.

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 one parameter with 0% description coverage, so the description must compensate. It adds meaning by explaining that 'date_str' is for a specific date in YYYY-MM-DD format or defaults to today if not specified, which clarifies the parameter's purpose and default behavior. This effectively documents the single parameter beyond the schema, earning a high 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 tool's purpose: 'Get MLB schedule for a specific date' with a verb ('Get') and resource ('MLB schedule'). It specifies the date format (YYYY-MM-DD) and default behavior (today if not specified). However, it does not explicitly distinguish this from sibling tools like 'get_game_summary' or 'get_standings', which might also involve schedule-related data, so it lacks sibling differentiation.

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

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

The description implies usage by stating when to use it: for retrieving the MLB schedule on a specific date or today. It mentions the default behavior if no date is specified. However, it does not provide explicit guidance on when not to use it or name alternatives among the sibling tools, such as 'get_game_summary' for detailed game info or 'get_standings' for standings data, leaving usage context somewhat implied.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states a read operation ('Get') but doesn't describe response format, error conditions, rate limits, or authentication needs. For a tool with zero annotation coverage, this is a significant gap in transparency about how it behaves.

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

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

The description is a single, efficient sentence with zero waste—every word contributes to the purpose. It's appropriately sized for a simple tool and front-loaded with the key action and resource.

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

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

Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It covers the basic purpose but lacks details on behavior, parameters, and return values, which are critical for a tool with one required parameter and unknown output structure.

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

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

Schema description coverage is 0%, so the description must compensate. It mentions 'for a specific year,' which aligns with the 'year' parameter in the schema, adding basic semantic context. However, it doesn't specify format (e.g., integer year like 2023), valid ranges, or examples, leaving gaps in parameter understanding.

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

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

The description clearly states the verb ('Get') and resource ('MLB draft summary') with specific scope ('for a specific year'), making the purpose immediately understandable. It distinguishes from siblings like get_player_profile or get_standings by focusing on draft data, though it doesn't explicitly differentiate from non-existent draft-related siblings.

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

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, constraints, or sibling tools that might overlap (e.g., if draft data is also available elsewhere). This leaves the agent without context for tool selection beyond the basic purpose.

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 states the action but doesn't describe what 'detailed boxscore' includes, whether it's a read-only operation, error handling, or response format. This is inadequate for a tool with no annotation coverage.

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

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

The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy 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?

Given no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain what a 'boxscore' entails, how to interpret results, or any behavioral traits, making it insufficient for effective tool use in this 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 schema description coverage is 0%, but the description adds some meaning by implying 'game_id' is required to specify the MLB game. However, it doesn't explain the format or constraints of 'game_id', leaving significant gaps. Baseline is 3 due to the single parameter, but it doesn't fully compensate for the coverage gap.

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

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

The description clearly states the verb 'Get' and the resource 'detailed boxscore for a specific MLB game', making the purpose explicit. It distinguishes from siblings like 'get_game_summary' or 'get_game_play_by_play' by specifying 'boxscore', but doesn't explicitly contrast them, so it's not a perfect 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'get_game_summary' or 'get_game_play_by_play', nor does it specify prerequisites or exclusions, leaving usage context unclear.

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 tool retrieves data, implying a read-only operation, but does not disclose any behavioral traits such as rate limits, authentication needs, error handling, or what happens if the game_id is invalid. This leaves significant gaps for an agent to understand how to use it effectively.

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 that efficiently conveys the core purpose without any fluff or redundancy. It is appropriately sized and front-loaded, 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?

Given the complexity of retrieving game-specific pitch metrics, the lack of annotations and output schema means the description must compensate more. It fails to provide details on return values, data structure, or any behavioral context, leaving the agent with insufficient information to handle the tool robustly in a broader context.

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

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

The input schema has one parameter ('game_id') with 0% schema description coverage, meaning the schema provides no details about the parameter. The description adds no semantic information beyond implying it's for a specific MLB game, without explaining the format or constraints of 'game_id'. This partially compensates but does not fully address the coverage gap, aligning with the baseline for minimal param info.

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

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

The description clearly states the action ('Get') and the resource ('pitch-level metrics and Statcast data for a specific MLB game'), making the purpose evident. However, it does not explicitly differentiate from siblings like 'get_game_boxscore' or 'get_game_play_by_play', which might also provide game-specific data but for different aspects, so it lacks sibling differentiation.

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

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

The description provides minimal guidance by specifying 'for a specific MLB game', implying usage when pitch-level metrics are needed for a particular game. However, it offers no explicit advice on when to use this tool versus alternatives (e.g., 'get_seasonal_pitch_metrics' for aggregated data or 'get_game_summary' for broader game info), and no exclusions or prerequisites are mentioned.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'detailed play-by-play data' but does not specify what that includes, whether it's read-only, if there are rate limits, authentication needs, or error handling. This is a significant gap for a tool with no annotation coverage.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for the complexity, earning full marks for conciseness.

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

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

Given no annotations, no output schema, and low schema description coverage, the description is incomplete. It lacks details on behavior, parameter usage, output format, and differentiation from siblings, making it inadequate for a tool that likely returns complex data like play-by-play 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 schema description coverage is 0%, with one parameter 'game_id' undocumented in the schema. The description adds no semantic details about the parameter, such as format or examples, but since there is only one parameter, the baseline is 4. However, the lack of any parameter guidance in the description reduces it to 3, as it fails to compensate for the low coverage.

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

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

The description clearly states the action ('Get') and the resource ('detailed play-by-play data for a specific MLB game'), making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'get_game_summary' or 'get_game_boxscore', which might offer overlapping or related data, so it misses the highest score.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as 'get_game_summary' or 'get_game_boxscore', nor does it mention any prerequisites or exclusions. It only states what the tool does, leaving usage context implied but not specified.

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 tool retrieves 'summary information' but doesn't specify what that includes (e.g., scores, teams, date), whether it's a read-only operation, potential rate limits, or error handling for invalid game IDs. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 a single, direct sentence that efficiently conveys the core purpose without any fluff or redundancy. It's appropriately sized for a simple tool and front-loaded with the essential information, making it easy for an agent to parse quickly. Every word earns its place.

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

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

Given the tool's low complexity (one parameter, no nested objects) but lack of annotations and output schema, the description is incomplete. It doesn't explain what 'summary information' entails, how to handle errors, or provide any behavioral context. For a tool with no structured support, the description should do more to guide the agent, such as hinting at the return format or common use cases.

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

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

The input schema has one parameter ('game_id') with 0% description coverage, meaning the schema provides no details on its format or meaning. The description adds minimal value by implying it's for a 'specific MLB game,' but doesn't clarify the expected format (e.g., numeric ID, string code) or where to obtain it. Since there's only one parameter, the baseline is higher, but the description doesn't fully compensate for the lack of schema details.

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

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

The description clearly states the action ('Get summary information') and the resource ('for a specific MLB game'), making the purpose immediately understandable. It distinguishes this from siblings like 'get_game_boxscore' or 'get_game_play_by_play' by specifying 'summary' rather than detailed metrics or play-by-play data. However, it doesn't explicitly differentiate from 'get_daily_schedule' or 'get_team_profile', which might also provide game-related info, keeping it from a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing a valid game ID, or compare it to siblings like 'get_game_boxscore' for detailed stats or 'get_daily_schedule' for broader game listings. Without any context on usage scenarios or exclusions, the agent must infer based on tool names alone.

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

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

No annotations are provided, so the description carries the full burden. It states 'Get current MLB injury report' but doesn't disclose behavioral traits such as data freshness, rate limits, authentication needs, or what 'current' means (e.g., real-time, daily updates). This leaves significant gaps in understanding how the tool behaves.

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

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

The description is a single, efficient sentence with no wasted words. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.

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 (0 parameters, no annotations, no output schema), the description is minimally adequate but incomplete. It lacks details on output format, data scope, or behavioral context, which are needed for full understanding despite 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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds no parameter information, which is acceptable here as there are no parameters to explain, aligning with the baseline for zero 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 verb 'Get' and the resource 'current MLB injury report', making the purpose specific and understandable. However, it doesn't explicitly differentiate from siblings like get_player_profile or get_team_roster, which might also contain injury information, so it misses full sibling differentiation.

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

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like get_player_profile that might include injury data, there's no indication of when this specialized injury report is preferred, leaving usage context unclear.

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 what the tool does but lacks details on permissions, rate limits, data freshness, pagination, or error handling. For a read operation with no annotations, this is a significant gap, as agents need more context to use it effectively.

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

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

The description is a single, efficient sentence that front-loads the core purpose with no wasted words. Every part ('Get MLB league leaders for a specific year and category') contributes directly to understanding the tool's function, making it appropriately sized and well-structured.

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

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

Given no annotations, 0% schema coverage, no output schema, and 2 parameters, the description is incomplete. It covers the basic purpose but lacks behavioral traits, detailed parameter semantics, and output expectations. For a tool with this complexity and minimal structured data, it should provide more context to be fully helpful.

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

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

Schema description coverage is 0%, so the description must compensate. It adds meaning by specifying that parameters are for 'year' and 'category (hitting/pitching)', which clarifies beyond the schema's generic titles. However, it doesn't detail valid year ranges, category options beyond examples, or default behaviors, leaving gaps in parameter understanding.

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

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

The description clearly states the verb ('Get') and resource ('MLB league leaders') with specific scoping parameters ('for a specific year and category'). It distinguishes from siblings like get_standings or get_player_seasonal_stats by focusing on league leaders rather than standings or individual player stats. However, it doesn't explicitly differentiate from get_statcast_leaders, which might overlap in purpose.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, when not to use it, or compare to siblings like get_statcast_leaders for advanced metrics or get_seasonal_statistics for broader data. Usage is implied only by the parameters (year and category), with no explicit context or exclusions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only operation ('Get') but does not specify aspects like rate limits, authentication needs, error handling, or the format of the returned profile information. This leaves significant gaps in understanding how the tool behaves beyond its basic function.

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

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

The description is a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for quick understanding.

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

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

Given the lack of annotations and output schema, the description is incomplete for a tool that presumably returns detailed profile information. It does not explain what 'detailed' entails, the structure of the output, or any behavioral constraints. For a read operation with no structured support, more context is needed to fully guide 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?

The input schema has 0% description coverage, with only one parameter 'player_id' documented structurally. The description does not add any semantic details about this parameter, such as what constitutes a valid player ID or where to obtain it. However, with a single parameter and no complex schema, the baseline score of 3 is appropriate as the schema minimally defines the 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 clearly states the verb ('Get') and resource ('detailed profile information for a specific MLB player'), making the purpose evident. However, it does not explicitly differentiate this tool from potential siblings like 'get_player_seasonal_stats' or 'get_team_roster', which might also provide player-related data, so it falls short of a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as 'get_player_seasonal_stats' for stats or 'get_team_roster' for roster details. It lacks any context about prerequisites, exclusions, or specific use cases, offering only a basic statement of purpose.

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-only operation but does not specify data format, pagination, rate limits, authentication needs, or error handling. This is a significant gap for a tool with two parameters and no output schema.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy 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?

Given the complexity (2 parameters, no annotations, no output schema), the description is incomplete. It does not cover return values, error cases, or behavioral details, leaving the agent with insufficient information to use the tool effectively beyond basic invocation.

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

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

Schema description coverage is 0%, so the description must compensate. It mentions 'specific player' and 'seasonal statistics,' which hints at the 'player_id' and 'year' parameters, but does not explain their semantics, formats, or constraints (e.g., what constitutes a valid player_id or year range). This adds minimal value beyond 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 verb 'Get' and the resource 'seasonal statistics for a specific player,' making the purpose understandable. However, it does not differentiate from sibling tools like 'get_seasonal_statistics' or 'get_seasonal_splits,' which might have overlapping functionality, so it lacks explicit distinction.

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 prerequisites, context, or compare to siblings such as 'get_player_profile' or 'get_seasonal_statistics,' leaving the agent to infer usage 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 provided, so the description carries the full burden of behavioral disclosure. It states it 'gets' data, implying a read-only operation, but doesn't cover aspects like rate limits, authentication needs, data format, or whether it returns aggregated or raw metrics. For a tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a simple data retrieval tool, making it easy 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?

Given the complexity (2 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'Statcast pitch metrics' include, how data is returned, or handle edge cases like invalid years. Without annotations or output schema, more detail is needed to fully inform 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%, meaning parameters are undocumented in the schema. The description mentions 'player's season', which hints at the 'player_id' and 'year' parameters, but doesn't explain what 'player_id' format to use (e.g., MLB ID) or that 'year' is optional with a default. It adds minimal semantic value beyond the schema's basic structure.

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 'Get' and the resource 'detailed Statcast pitch metrics for a player's season', which is specific and distinguishes it from siblings like 'get_game_pitch_metrics' (game-level) and 'get_player_seasonal_stats' (general stats). However, it doesn't explicitly differentiate from 'get_seasonal_splits' or 'get_seasonal_statistics', which might overlap in scope, keeping it from a perfect 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose it over 'get_game_pitch_metrics' for game-level data or 'get_player_seasonal_stats' for broader seasonal stats, nor does it specify prerequisites or exclusions. This lack of context leaves usage unclear.

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

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

No annotations are provided, so the description carries full burden. It mentions what data is retrieved but lacks behavioral details like whether this is a read-only operation, any rate limits, authentication needs, or what the return format looks like. For a 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 a single, efficient sentence that front-loads the purpose with no wasted words. It is appropriately sized for the tool's complexity.

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 complexity (2 parameters, no annotations, no output schema), the description is incomplete. It lacks details on parameter usage, behavioral traits, and return values, making it inadequate for effective tool invocation.

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

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

Schema description coverage is 0%, so the description must compensate. It does not explain the parameters player_id or year, their formats, or semantics. The description adds no value beyond what the schema provides, failing to address the coverage gap.

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

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

The description clearly states the verb 'Get' and resource 'seasonal splits for a player', specifying the type of splits (home/away, vs lefty/righty, etc.). It distinguishes from siblings like get_player_seasonal_stats by focusing on splits rather than overall statistics, though it doesn't explicitly name alternatives.

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_player_seasonal_stats or get_seasonal_statistics. The description implies usage for split data but lacks explicit context, prerequisites, or exclusions.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic action ('Get') without detailing traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like (e.g., statistical categories returned). This leaves significant gaps for a tool that likely returns complex data.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a basic tool description, though this conciseness comes at the cost of missing contextual details.

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

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

Given the complexity of retrieving seasonal statistics (likely involving multiple data points), no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't provide enough information for an agent to understand what statistics are returned, how to interpret parameters, or behavioral constraints, making it inadequate for effective tool use.

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

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

Schema description coverage is 0%, meaning parameters are undocumented in the schema. The description adds no information about parameters beyond implying a 'team_id' is needed. It doesn't explain the meaning of 'year' (e.g., if null defaults to current season) or 'season_type' (e.g., what 'REG' stands for or other possible values), failing to compensate for the low schema coverage.

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

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

The description clearly states the action ('Get') and resource ('seasonal statistics for a specific team'), making the purpose understandable. However, it doesn't distinguish this tool from similar siblings like 'get_player_seasonal_stats' or 'get_seasonal_pitch_metrics', which also retrieve seasonal data but for different entities or 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. With siblings like 'get_player_seasonal_stats' and 'get_seasonal_pitch_metrics' that handle related seasonal data, the description lacks any indication of context, prerequisites, or exclusions, leaving the agent to infer usage based on tool names alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves standings but doesn't describe behavioral traits such as data format (e.g., JSON structure), potential rate limits, error handling (e.g., invalid year/league inputs), or whether it's a read-only operation (implied by 'Get' but not explicit). This leaves gaps in understanding how the tool behaves beyond its basic purpose.

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

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

The description is a single, efficient sentence that front-loads the core purpose ('Get MLB standings') and succinctly covers key usage aspects (year/league or current season). There is no wasted verbiage, and every part of the sentence contributes directly to understanding the tool's function and scope.

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 (2 parameters, no annotations, no output schema), the description is adequate but incomplete. It covers the basic purpose and parameter usage but lacks details on behavioral traits (e.g., response format, error cases) and doesn't leverage sibling tool context to clarify differentiation. Without an output schema, it should ideally hint at what the standings data includes, but it doesn't, leaving some contextual 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 description adds some meaning beyond the input schema by specifying that 'year' and 'league' parameters can be used for historical data or omitted for the current season, and it clarifies that 'league' accepts 'AL/NL'. However, with 0% schema description coverage and 2 parameters, it doesn't fully compensate by detailing parameter formats (e.g., year range, league codes beyond AL/NL) or default behaviors when parameters are null. This meets the baseline for minimal viability but lacks depth.

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

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

The description clearly states the tool's purpose: 'Get MLB standings for a specific year and league (AL/NL) or current season.' It specifies the verb ('Get'), resource ('MLB standings'), and scope (year/league or current season). However, it doesn't explicitly differentiate from sibling tools like 'get_league_leaders' or 'get_seasonal_statistics', which might also involve standings-related 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?

The description implies usage context by mentioning 'specific year and league (AL/NL) or current season,' suggesting when to use it for historical vs. current data. However, it doesn't provide explicit guidance on when to choose this tool over alternatives like 'get_league_leaders' for standings-related queries or 'get_team_profile' for team-specific info, nor does it mention any exclusions or prerequisites.

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

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

No annotations are provided, so the description carries full burden. It states the tool retrieves leaderboards but doesn't disclose behavioral traits such as data format, pagination, rate limits, authentication needs, or whether it's read-only. 'Get' implies a safe read operation, but this isn't explicitly confirmed.

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

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

The description is a single, efficient sentence that front-loads the purpose with specific examples. There is no wasted verbiage, making it easy to scan and understand 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?

Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on parameters, return values, and behavioral context needed for a tool with two parameters and statistical data retrieval.

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 mentions categories like exit_velocity but doesn't explain the 'year' or 'category' parameters beyond what's in the schema titles. No details on valid values, defaults, or constraints are provided.

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 'Get' and resource 'Statcast leaderboards' with specific examples (exit_velocity, launch_angle, barrel_rate). It distinguishes from most siblings by focusing on Statcast metrics rather than games, players, or teams, though it doesn't explicitly differentiate from 'get_league_leaders' which might overlap.

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

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

No guidance on when to use this tool versus alternatives like 'get_league_leaders' or other statistical tools. The description implies usage for Statcast metrics but lacks explicit context, prerequisites, or exclusions.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it 'gets' data, implying a read operation, but doesn't specify if it's real-time, cached, requires authentication, has rate limits, or what the output format might be. This leaves significant gaps in understanding 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 a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It is front-loaded and appropriately sized, making it easy to parse and understand 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?

Given the complexity of a tool that retrieves hierarchical data (leagues and divisions), the description is incomplete. There are no annotations, no output schema, and it doesn't explain what the returned data structure looks like or any behavioral traits. This makes it inadequate for an agent to fully understand how to use the tool effectively.

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

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

The tool has 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline of 4 is applied as it handles the lack of parameters correctly without unnecessary details.

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

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

The description clearly states the action ('Get') and resource ('complete MLB team hierarchy with divisions and leagues'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_team_profile' or 'get_standings', which might also provide team-related information, so it doesn't reach the highest score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any context, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name alone without explicit direction.

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 states it 'gets' information, implying a read-only operation, but doesn't specify aspects like rate limits, authentication needs, error handling, or what 'detailed profile information' entails. This leaves significant gaps in understanding 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 a single, clear sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and efficiently conveys the core function, making it easy 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?

Given the complexity of a tool with one parameter but no schema descriptions, annotations, or output schema, the description is insufficient. It doesn't explain what 'detailed profile information' includes, how to interpret the team_id, or the response format, leaving the agent with incomplete context for effective use.

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

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

The input schema has 0% description coverage, with one parameter 'team_id' documented only by its title. The description adds no semantic information about this parameter, such as format examples (e.g., team abbreviations, numeric IDs), valid values, or where to find team IDs. This fails to compensate for the schema's lack of detail.

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

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

The description clearly states the action ('Get') and resource ('detailed profile information for a specific MLB team'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_team_hierarchy' or 'get_team_roster', which might also provide team-related information, so it doesn't reach the highest score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage based on the name alone. This lack of explicit guidance reduces effectiveness in tool selection.

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

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

No annotations are provided, so the description carries full burden. It states 'Get' which implies a read operation, but doesn't disclose behavioral traits like whether it requires authentication, rate limits, what format the roster returns (e.g., list of players with details), or if it's real-time vs. cached data. For a tool with zero annotation coverage, this is insufficient.

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

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

The description is a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a simple tool and front-loaded with the core purpose.

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

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

Given the tool's moderate complexity (retrieving a roster), lack of annotations, no output schema, and low parameter coverage, the description is incomplete. It doesn't explain what the output contains (e.g., player names, positions, stats) or address potential issues like invalid team IDs, making it inadequate for reliable agent use.

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

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

The input schema has 1 parameter (team_id) with 0% description coverage in the schema. The description adds no specific meaning about the parameter, such as what team_id format to use (e.g., team abbreviations, numeric IDs) or where to find valid values. With low schema coverage, the description doesn't compensate, but since there's only one parameter, the baseline is slightly higher than 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 clearly states the verb ('Get') and resource ('current roster for a specific MLB team'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like get_team_profile or get_team_hierarchy, which might also provide team-related information but with different scopes.

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 doesn't mention prerequisites, exclusions, or compare it to sibling tools like get_team_profile (which might include roster info) or get_player_profile (for individual details), leaving the agent to infer usage context.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but doesn't disclose critical traits like whether it requires authentication, rate limits, pagination, error handling, or the format of returned data (e.g., list of transactions with details). For a data-fetching tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is highly concise and front-loaded: a single sentence that directly states the tool's function without unnecessary words. Every part of the sentence ('Get MLB transactions for a specific date or recent transactions') contributes essential information, making it efficient and easy to parse for an AI agent.

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

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

Given the tool's complexity (data retrieval with one parameter), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain return values (e.g., transaction types, fields), error cases, or behavioral nuances like how 'recent' is defined. For a tool that likely returns structured data, more context is needed to ensure the agent can use it effectively.

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

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

The input schema has one parameter ('date_str') with 0% description coverage, and the description adds minimal semantic context: it mentions 'specific date or recent transactions,' hinting that 'date_str' is optional for recent data. However, it doesn't specify the date format (e.g., YYYY-MM-DD), what 'recent' means (e.g., last 7 days), or default behavior when null. With low schema coverage, the description fails to adequately compensate, leaving key parameter details unclear.

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

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

The description clearly states the tool's purpose: 'Get MLB transactions for a specific date or recent transactions.' It specifies the verb ('Get'), resource ('MLB transactions'), and scope ('specific date or recent'), which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'get_injuries' or 'get_team_roster', which might also involve transaction-related data, so it lacks sibling differentiation.

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

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

The description provides minimal guidance: it implies usage for retrieving transactions by date or recent ones, but offers no explicit when-to-use rules, exclusions, or alternatives. For example, it doesn't specify if this is for daily updates vs. historical lookups or how it compares to other tools like 'get_player_profile' for player movements. This leaves the agent with little context for optimal tool selection.

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