NBA MCP Server

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose targeting specific resources (league standings, live games, players, teams, scoreboard) with no overlap. The descriptions clearly differentiate between standings, boxscores, play-by-play, awards, stats, logs, details, and scoreboard data, making misselection unlikely.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with 'get_' prefix, followed by the resource type (e.g., league_team_standings, player_awards, team_details). The naming is uniform throughout, using snake_case consistently without any deviations or mixed conventions.
Tool Count5/5
With 10 tools, the count is well-scoped for an NBA data server, covering core areas like standings, live games, players, teams, and scoreboard. Each tool earns its place by providing distinct data retrieval functions without being overly sparse or bloated.
Completeness4/5
The toolset provides comprehensive coverage for retrieving NBA data, including CRUD-like operations for players and teams (e.g., stats, logs, details) and live game information. A minor gap exists in the lack of tools for creating or updating data (e.g., posting comments or simulations), but this is reasonable for a read-only data server focused on retrieval.
Average 3.3/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
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    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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. While 'Get' implies a read operation, it doesn't specify whether this requires authentication, has rate limits, returns paginated results, or what happens if the player_id is invalid. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with two sentences: one stating the purpose and another explaining the parameter. The Args section is structured but could be more integrated. There's no wasted text, though it could be slightly more polished.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete behavioral context, it doesn't fully prepare the agent for potential edge cases or usage constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal parameter semantics beyond the schema. It explains that player_id is 'The id of the player', which slightly clarifies the schema's 'Player Id' title. However, with 0% schema description coverage and only one parameter, this meets the baseline expectation without providing format examples or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('career stats for a player'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_player_game_log' or 'get_player_awards', which also retrieve player-related data but for different scopes (game-level vs career-level).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools like 'get_player_game_log' (for per-game stats) or 'get_player_awards' (for awards data), leaving the agent to infer usage context 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.
Behavior2/5
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 data ('Get game log'), implying it's a read operation, but doesn't disclose behavioral traits like rate limits, authentication needs, error handling, or what format the game log returns. The description is minimal and lacks crucial operational context for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the purpose stated first followed by parameter details. It uses bullet points for clarity and avoids redundancy. However, the parameter explanations could be more integrated into the main text, and some sentences are brief but necessary, earning a 4 for efficiency with minor structural improvements possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with 0% schema coverage and no annotations, but with an output schema present, the description is partially complete. It explains the parameters but lacks behavioral context and usage guidelines. The output schema handles return values, so the description doesn't need to explain those, but it should cover more operational aspects for a tool with no annotations, making it adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 explaining player_id as 'the id of the player', season format as 'YYYY-YY', and season_type with a pattern list. However, it doesn't fully cover all parameters' semantics (e.g., where to find player_id, valid season ranges, or default behaviors), leaving gaps. Baseline is 3 as it adds some value but incompletely.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get game log') and resource ('for a player'), specifying it retrieves statistical records. It distinguishes from siblings like get_player_career_stats (career vs. specific season) and get_team_game_log (player vs. team), though not explicitly. However, it lacks explicit sibling differentiation, keeping it at 4 instead of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_player_game_log over get_player_career_stats or get_team_game_log, nor does it specify prerequisites like needing a valid player ID. Usage is implied through parameter descriptions but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 what the tool does without mentioning traits like read-only vs. destructive, authentication needs, rate limits, or error handling. For a data retrieval tool, this leaves gaps in understanding operational constraints and response behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the main purpose is stated first, followed by a brief parameter explanation. It avoids unnecessary details, but the structure could be improved by integrating the parameter info more seamlessly rather than as a separate 'Args' section.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple retrieval with 1 parameter) and the presence of an output schema, the description is somewhat complete but lacks depth. It covers the basic action and parameter, but without annotations or details on usage context, it falls short of being fully helpful for an agent navigating among multiple team-related tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantics beyond the input schema: it explains 'team_id' as 'The id of the team,' which is basic but clarifies the parameter's purpose. With 0% schema description coverage and 1 parameter, this compensates slightly, but it doesn't provide format details or examples, keeping it at a baseline level.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 year-by-year stats for a team by their ID.' It specifies the verb ('Get') and resource ('year-by-year stats for a team'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'get_team_details' or 'get_team_game_log,' which might also involve team data, so it misses full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 scenarios like comparing team performance over time or prerequisites such as needing a valid team ID. With siblings like 'get_team_game_log' for game-level data, the lack of context leaves the agent guessing about appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 tool retrieves data ('Get'), implying a read-only operation, but doesn't cover aspects like rate limits, authentication needs, error handling, or response format. The description is minimal and lacks behavioral details beyond the 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the main purpose stated clearly in the first sentence. The parameter explanations are concise and directly relevant. There's no wasted text, though the structure could be slightly improved by integrating parameter details more seamlessly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description doesn't need to explain return values. However, with no annotations and a simple 2-parameter tool, the description is adequate but minimal. It covers the basic purpose and parameters but lacks context on usage, behavioral traits, or integration with siblings, leaving some gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains that 'season' is in 'YYYY-YY' format and 'season_type' follows a pattern like 'Regular Season' or 'Pre Season'. This compensates well for the schema's lack of descriptions, though it doesn't cover all potential values or edge cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 league team standings for a given season and season type.' It specifies the verb ('Get') and resource ('league team standings'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_team_details' or 'get_team_year_by_year_stats', which prevents 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.
Usage Guidelines2/5
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 sibling tools or clarify scenarios where this tool is preferred over others like 'get_team_game_log' or 'get_today_scoreboard'. Usage is implied through the parameters but lacks 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.
Behavior2/5
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 cover aspects like rate limits, authentication needs, error handling, or data freshness (e.g., real-time vs. cached). For a tool with no annotations, this is a significant gap in 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded. The first sentence clearly states the purpose, and the 'Args' section efficiently documents the parameter without unnecessary details. Every sentence adds value, making it 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter) and the presence of an output schema, the description is reasonably complete. It covers the basic purpose and parameter, and the output schema likely handles return values. However, without annotations and with minimal behavioral details, it could be more comprehensive for a data-fetching tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal meaning beyond the input schema. It defines 'game_id' as 'The ID of the game,' which is basic and does not elaborate on format, sourcing, or validation. With 0% schema description coverage, the description compensates slightly by naming the parameter, but does not fully address the coverage gap, resulting in adequate but incomplete parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 the play-by-play data for a specific game by its ID.' It specifies the verb ('Get'), resource ('play-by-play data'), and scope ('for a specific game'), but does not explicitly differentiate it from sibling tools like 'get_live_game_boxscore', which likely provides different game data. This makes it clear but not fully sibling-distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 mentions the tool fetches play-by-play data, but does not indicate scenarios where this is preferred over other game-related tools (e.g., 'get_live_game_boxscore' for summary stats or 'get_today_scoreboard' for scores). This lack of comparative 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.
Behavior2/5
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 awards') without mentioning permissions, rate limits, error handling, or what the output contains (though an output schema exists). For a tool with no annotations, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and well-structured: it starts with a clear purpose statement, followed by a brief 'Args' section that explains the parameter. Every sentence earns its place with no wasted words, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the basic purpose and parameter semantics, though it lacks usage guidelines and behavioral details, which are partially mitigated by the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'player_id' by explaining it as 'The id of the player,' which clarifies its purpose beyond the schema's title 'Player Id.' With 0% schema description coverage, this compensates well, though it could be more detailed (e.g., format examples).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 awards for a player by their ID.' It specifies the verb ('Get') and resource ('awards for a player'), making it easy to understand. However, it doesn't differentiate from sibling tools like 'get_player_career_stats' or 'get_player_game_log' in terms of what specific data is retrieved, which prevents 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.
Usage Guidelines2/5
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 (e.g., needing a valid player ID), exclusions, or comparisons to sibling tools like 'get_player_career_stats' for broader player data. This lack of context leaves the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 this is a read operation ('Get details'), but doesn't mention potential limitations like rate limits, authentication requirements, or error handling. The description adds some context about what details are included, but lacks critical behavioral traits 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with two sentences followed by a parameter explanation. The first sentence states the core purpose, the second provides helpful examples, and the Args section adds necessary parameter context without redundancy. It's front-loaded with the most important information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), a single parameter with good semantic coverage in the description, and no complex behavioral requirements beyond basic read operations, the description is reasonably complete. It could benefit from more behavioral context given the lack of annotations, but covers the essential purpose and parameter meaning adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides clear semantic meaning for the single parameter ('team_id: The id of the team'), which is valuable since schema description coverage is 0%. This compensates well for the lack of schema descriptions, though it doesn't specify format constraints or provide examples of valid team IDs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get details') and resource ('team by their ID'), with specific examples of included information like championship awards and background. It distinguishes this from sibling tools that focus on standings, game logs, or player data rather than comprehensive team details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the description's focus on retrieving comprehensive team details, suggesting it's for when detailed team information is needed. However, there's no explicit guidance on when to use this versus alternatives like get_team_year_by_year_stats or get_team_game_log, nor any prerequisites or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 what data is retrieved but doesn't disclose behavioral traits like pagination, rate limits, authentication needs, error handling, or what the output contains. For a data retrieval tool with no annotations, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with a clear purpose statement followed by parameter details. The Args section is structured but could be more integrated; however, every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with no schema descriptions and an output schema exists, the description adequately covers parameter semantics but lacks behavioral context. For a retrieval tool with no annotations, it should mention output format or limitations, but the output schema mitigates some completeness needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds crucial semantic context beyond the schema, which has 0% coverage. It explains that team_id is 'the id of the team', season uses format 'YYYY-YY', and season_type includes specific patterns like 'Regular Season'. This compensates well 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.
Purpose5/5
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 'game log for a team', specifying it retrieves data based on team ID, season, and season type. It distinguishes from siblings like get_team_details (general info) and get_player_game_log (player-specific) by focusing on team game logs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing a team's game log with specific season parameters, but doesn't explicitly state when to use this tool vs. alternatives like get_team_year_by_year_stats or get_live_game_boxscore. 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.
Behavior2/5
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 'live data' and 'game statuses', which hints at real-time updates, but does not disclose behavioral traits such as rate limits, data freshness, authentication needs, or error handling. The description adds minimal context beyond the 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that are front-loaded with the core purpose and efficiently elaborate on the data provided. Every sentence adds value without redundancy, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, simple read operation) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers what data is fetched and its temporal scope, though it lacks details on behavioral aspects like data latency or limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are 0 parameters, and schema description coverage is 100% (empty schema). The description appropriately does not discuss parameters, focusing instead on the tool's output scope ('today's games', 'live data'). This aligns with the baseline of 4 for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get'), resource ('NBA scoreboard'), and temporal scope ('today's games'). It distinguishes from siblings like get_league_team_standings (standings) and get_live_game_boxscore (detailed boxscores) by focusing on the current day's game overview with scores and statuses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context ('today's games', 'live data') but does not explicitly state when to use this tool versus alternatives like get_team_game_log (historical logs) or get_live_game_play_by_play (detailed play data). 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that the tool retrieves live data, implying real-time or current game status, which is useful behavioral context. However, it lacks details on permissions, rate limits, error handling, or whether data is cached/static, leaving gaps 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by additional context in the second, and includes a structured 'Args' section for parameters. Every sentence adds value without redundancy, making it efficient and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and low schema coverage, the description is reasonably complete. It covers purpose, parameter semantics, and data inclusions, but could improve by addressing behavioral aspects like error cases or data freshness, given the lack of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 explaining that 'game_id' refers to 'The ID of the game,' clarifying the parameter's purpose beyond the schema's basic type. However, it does not specify the ID format (e.g., numeric, string pattern) or provide examples, which could enhance usability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 box score') and resource ('for a specific game by its ID'), distinguishing it from siblings like get_live_game_play_by_play (which provides play-by-play data) and get_today_scoreboard (which lists multiple games). It explicitly mentions what the box score includes (live data, scores, player stats, timeouts).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'for a specific game by its ID' and listing included data types, which helps differentiate from siblings like get_team_game_log or get_player_career_stats. However, it does not explicitly state when not to use this tool or name alternatives (e.g., vs. get_live_game_play_by_play for different data).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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