sports

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 return fields (event name, date, teams, scores, league) but omits critical behavioral details such as error handling, rate limits, authentication requirements, data freshness, or whether results are paginated. For a read operation with zero annotation coverage, this leaves significant 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 a single, efficient sentence that front-loads the core purpose and includes essential return details. Every word earns its place with zero redundancy, making it highly concise and well-structured for quick comprehension.

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 output schema, no annotations), the description is minimally adequate. It covers the basic purpose and return fields, but lacks completeness in behavioral context (e.g., error cases, limits) and usage guidelines. Without annotations or output schema, the description should do more to compensate, but it meets a bare-minimum threshold.

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

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

Schema description coverage is 100%, so the input schema fully documents the single required parameter (team_id). The description adds no additional parameter semantics beyond what the schema provides—it doesn't explain format constraints, provide examples beyond the schema's example, or clarify parameter interactions. Baseline 3 is appropriate when the schema handles parameter documentation.

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

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

The description clearly states the specific action ('Get the last 15 events/matches'), resource ('played by a team'), and scope ('last 15'), distinguishing it from siblings like get_next_events (future events) and get_league_table (standings). It precisely defines what the tool does without being vague or tautological.

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 for retrieving recent match history for a team, but provides no explicit guidance on when to use this tool versus alternatives like search_teams or get_next_events. It lacks any mention of prerequisites, exclusions, or comparative context with sibling tools.

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

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

No annotations are provided, so the description carries the full burden. It mentions the return data structure but lacks behavioral details such as whether this is a read-only operation, potential rate limits, authentication requirements, or error handling. The description provides basic output info but misses key operational context.

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

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

The description is a single, efficient sentence that front-loads the purpose and details the return values without unnecessary words. Every part earns its place, 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 no annotations and no output schema, the description provides the purpose and return structure but lacks completeness for a read operation. It does not cover error cases, data freshness, or pagination, leaving gaps in operational context that could aid an AI agent.

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

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

Schema description coverage is 100%, so the schema already documents both parameters (league_id and season) with examples. The description adds no additional parameter semantics beyond what the schema provides, such as format constraints or usage tips, meeting the baseline for high 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 verb ('Get') and resource ('current standings/table for a league and season'), specifying the exact data returned (team, played, wins, etc.). It distinguishes itself from siblings like get_last_events or search_players by focusing on league standings rather than events or player/team searches.

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 for retrieving league standings, but does not explicitly state when to use this tool versus alternatives like get_last_events or search_teams. No exclusions or specific contexts are provided, leaving usage inferred rather than guided.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool returns specific data fields and limits results to 'next 15' events, which is useful context. However, it doesn't mention error handling, rate limits, authentication needs, or whether this is a read-only operation (though implied by 'Get').

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, well-structured sentence that efficiently conveys purpose, scope, and return data without unnecessary words. Every element earns its place.

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

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

For a simple read operation with one parameter and no output schema, the description adequately covers the core functionality. However, without annotations or output schema, it lacks details on error cases, pagination (implied by 'next 15'), or full behavioral context, making it minimally complete.

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

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

Schema description coverage is 100%, so the schema already documents the single 'team_id' parameter with its format example. The description doesn't add any parameter-specific information beyond what's in the schema, but with high coverage, the baseline is 3.

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'), the resource ('next 15 upcoming events/matches for a team'), and the return data ('event name, date, home team, away team, and league'). It distinguishes from 'get_last_events' by specifying 'upcoming' vs. past events, but doesn't explicitly differentiate from other siblings like 'get_league_table' beyond the resource type.

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 for retrieving upcoming team events, but doesn't explicitly state when to use this tool versus alternatives like 'get_last_events' for past events or 'search_teams' for team information. No guidance on exclusions or prerequisites is provided.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions the return fields (name, team, nationality, etc.), which is helpful, but lacks critical behavioral details: it doesn't specify whether this is a read-only operation, how results are sorted/limited, error conditions, or authentication requirements. For a search tool with zero annotation coverage, 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 appropriately concise with two sentences: the first states the purpose, and the second lists return fields. It's front-loaded with the core functionality, and every sentence adds value (the return fields info is useful since there's no output schema). However, it could be slightly more structured by separating usage notes from output 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 tool's moderate complexity (search function with one parameter) and lack of annotations/output schema, the description is minimally adequate. It covers the basic purpose and return fields, but misses behavioral aspects like result limits, error handling, or performance characteristics. For a search tool, this leaves the agent with incomplete context to 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?

Schema description coverage is 100%, with the single parameter 'query' documented as 'Player name or partial name to search for.' The description adds minimal value beyond this, only restating 'by name' without providing additional context like search sensitivity, format expectations, or examples. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Search for players by name' specifies the verb (search) and resource (players). It distinguishes from sibling tools like 'search_teams' by focusing on players rather than teams, though it doesn't explicitly contrast with other player-related tools (none exist in the sibling list). The description is specific but could be more precise about scope limitations.

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

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

The description implies usage context through 'Search for players by name,' suggesting this tool is for finding players when you have partial name information. However, it provides no explicit guidance on when to use this versus alternatives like 'search_teams' or other sibling tools, nor does it mention any prerequisites or exclusions. Usage is implied but not clearly articulated.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the return fields (team name, sport, league, etc.), which is helpful, but doesn't describe critical behaviors like pagination, rate limits, error conditions, or whether this is a read-only operation. For a search tool with zero annotation coverage, 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 appropriately concise with two sentences that efficiently convey the tool's purpose and return format. It's front-loaded with the core functionality. However, the second sentence listing return fields could be slightly more structured (e.g., using a bulleted format in the actual implementation), though this is minor.

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 (search operation with 1 parameter) and no output schema, the description provides basic completeness by stating purpose and return fields. However, it lacks important context about search behavior (fuzzy matching, case sensitivity), result limits, and error handling. With no annotations and no output schema, the description should do more to compensate.

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

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

Schema description coverage is 100%, so the schema already fully documents the single 'query' parameter. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

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 specific verb ('Search for') and resource ('sports teams'), and specifies the search criteria ('by name'). It distinguishes from siblings like 'search_players' by focusing on teams rather than players. However, it doesn't explicitly differentiate from other team-related tools that might exist in a broader context.

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 use 'search_teams' versus 'get_league_table' or 'search_players', nor does it provide any context about prerequisites, limitations, or typical use cases. The agent must infer usage from the tool name alone.

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