Twitch MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose targeting specific Twitch resources like channels, clips, games, streams, videos, and searches. The naming makes it unambiguous what each tool retrieves, with no functional overlap between tools.
Naming Consistency5/5
All tools follow a consistent 'get_' or 'search_' verb prefix with descriptive noun patterns (e.g., get_channel_info, search_channels). This uniform snake_case naming convention makes the tool set predictable and easy to understand.
Tool Count5/5
With 14 tools, this server is well-scoped for the Twitch domain, covering key resources like channels, streams, videos, games, and searches. Each tool earns its place by addressing a specific aspect of Twitch's API without being overwhelming.
Completeness4/5
The tool set provides comprehensive read-only coverage for retrieving Twitch data, including channels, streams, videos, games, and searches. A minor gap is the lack of write operations (e.g., posting comments or managing streams), but for a retrieval-focused server, it's highly complete.
Average 2.8/5 across 14 of 14 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No issues in the last 6 months
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "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. It only states the action ('取得します' - get/retrieve) without mentioning whether this is a read-only operation, requires authentication, has rate limits, or what the return format might be. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single Japanese sentence that directly states the tool's function. There's no wasted language or unnecessary elaboration. It's appropriately sized for a simple retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 is incomplete. It doesn't explain what 'channel information' includes (profile data, statistics, etc.) or the response format. For a tool in a Twitch API context with multiple similar siblings, more context is needed to distinguish its specific purpose.
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 schema description coverage is 100%, with the single parameter 'channelName' clearly documented as 'Twitchチャンネル名' (Twitch channel name). The description doesn't add any parameter details beyond what the schema provides, so it meets the baseline of 3 when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'チャンネル情報を取得します' (Get channel information) states the basic action but is vague about what 'channel information' includes. It doesn't distinguish this tool from siblings like get_stream_info or get_users, which also retrieve channel-related data. While it identifies the resource (channel), it lacks specificity about what information is retrieved.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With siblings like get_stream_info (for stream status) and get_users (for user data), there's no indication of when this specific channel info tool is appropriate. No context, exclusions, or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 tool searches, with no information on permissions, rate limits, pagination, or what the response looks like (e.g., format, fields). This is inadequate for a search tool with zero 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 a single, efficient sentence in Japanese ('ゲームやカテゴリーを検索します'), which translates to 'Searches for games or categories.' It's front-loaded with the core action and resource, with zero wasted words, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 a search tool with two parameters, the description is incomplete. It lacks details on behavioral traits, return values, and usage context, making it insufficient for an agent to understand how to effectively invoke this tool beyond basic parameter input.
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 100%, so the schema already documents both parameters ('query' and 'limit') with descriptions and constraints. The description adds no additional meaning beyond what the schema provides, such as examples or context for the search query. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool searches for 'games or categories' which gives a general purpose, but it's vague about what exactly is being searched (e.g., Twitch categories) and doesn't distinguish it from sibling tools like 'search_channels' or 'get_top_games'. It provides a verb ('search') and resource ('games/categories') but lacks specificity.
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?
No guidance is provided on when to use this tool versus alternatives like 'search_channels' or 'get_top_games'. The description implies usage for searching but doesn't specify context, exclusions, or prerequisites, leaving the agent to guess 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 the full burden of behavioral disclosure. It only states the action ('get stream information') without describing any traits such as read-only vs. destructive nature, authentication requirements, rate limits, or response format. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese, making it appropriately concise. However, it is under-specified rather than optimally concise, as it lacks necessary details. It is front-loaded but does not earn its place fully due to the minimal content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a tool to retrieve stream information), lack of annotations, and no output schema, the description is incomplete. It does not explain what 'stream information' includes, how results are returned, or any behavioral aspects. This leaves the agent with insufficient context to use the tool effectively.
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 input schema has 100% description coverage, with 'channelName' clearly documented as a Twitch channel name. The description adds no additional meaning beyond what the schema provides, as it does not mention parameters at all. Baseline is 3 because the schema does the heavy lifting, but the description fails to compensate or enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '配信情報を取得します' (Get stream information) states the basic action but is vague about what 'stream information' specifically entails. It distinguishes from siblings like 'get_channel_info' or 'get_streams' only by name, not by clarifying scope or content differences. The purpose is clear at a high level but lacks specificity about what data is retrieved.
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?
No guidance is provided on when to use this tool versus alternatives like 'get_streams' or 'get_channel_info'. The description does not mention any context, prerequisites, or exclusions for usage. It leaves the agent to infer based on tool names alone, which is insufficient for reliable selection.
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 user information') without mentioning permissions, rate limits, response format, or any constraints (e.g., the 100-item max from the schema). 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, though it could be more informative without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a read operation with one parameter) and lack of annotations and output schema, the description is incomplete. It does not explain what user information is returned, any limitations, or how it fits with siblings, making it inadequate for full contextual understanding.
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 schema description coverage is 100%, with the parameter 'userNames' well-documented in the schema as 'Twitchユーザー名の配列' (array of Twitch usernames) with a maxItems of 100. The description adds no additional meaning beyond this, so it meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'ユーザーの情報を取得します' (Get user information) states the basic purpose with a clear verb ('取得します' - get) and resource ('ユーザーの情報' - user information). However, it lacks specificity about what type of user information or how it differs from sibling tools like 'get_channel_info' or 'search_channels', making it somewhat vague rather than precisely distinguished.
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. With sibling tools like 'get_channel_info' and 'search_channels' that might overlap in user-related queries, there is no indication of context, prerequisites, or exclusions, leaving the agent without 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('get chat settings') without explaining what chat settings include, whether this is a read-only operation, any authentication needs, rate limits, or what the response format might be. This leaves significant gaps for an agent to understand 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single sentence that directly states the tool's purpose without any fluff or redundant information. It is front-loaded and wastes no words, making it efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 settings (which could involve permissions or detailed data), the description is insufficient. With no annotations, no output schema, and minimal behavioral context, it doesn't provide enough information for an agent to fully understand how to use this tool effectively compared to its siblings.
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 input schema has 100% description coverage, clearly documenting the single required parameter 'channelName' as a Twitch channel name. The description adds no additional semantic context beyond what the schema provides, such as examples or constraints, so it meets the baseline for high schema coverage without adding value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the purpose ('チャット設定を取得します' translates to 'Get chat settings'), which is a clear verb+resource combination. However, it doesn't differentiate this tool from its siblings (like get_channel_info or get_stream_info), leaving ambiguity about what specific 'chat settings' means in this context versus other channel-related data.
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. With siblings like get_channel_info and get_stream_info that might overlap in retrieving channel-related information, there's no indication of when chat settings are needed specifically, 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 of behavioral disclosure. It only states the action ('get clip information') without detailing traits like whether it's read-only (implied but not explicit), rate limits, authentication needs, error handling, or what the return format might be. For a tool with no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence ('クリップの情報を取得します') that directly states the tool's purpose without any fluff or redundancy. It is front-loaded and efficiently communicates the core action, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a read operation with 2 parameters) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'clip information' entails, how results are returned (e.g., list format, pagination), or any behavioral aspects. For a tool without structured output or annotations, more context is needed to guide effective use.
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 schema description coverage is 100%, with clear descriptions for both parameters (channelName and limit). The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or usage examples. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema adequately documents the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the purpose ('クリップの情報を取得します' translates to 'Get clip information'), which is clear but vague. It specifies the resource (clips) and verb (get), but doesn't distinguish it from potential siblings like get_videos or get_streams, nor does it specify what kind of clip information (e.g., metadata, URLs, statistics). This makes it adequate but with room for improvement.
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 context (e.g., for Twitch clips), prerequisites, or exclusions, leaving the agent to infer usage from the tool name and schema alone. This lack of explicit guidance reduces its 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.
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 action ('search') without details on permissions, rate limits, response format, or any side effects. For a search tool with no annotations, this is inadequate as it leaves key behavioral traits unspecified.
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 a single, efficient sentence in Japanese ('チャンネルを検索します'), which is appropriately sized and front-loaded with the core action. There is no wasted text, making it highly concise and well-structured for its purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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. It doesn't explain what the search returns (e.g., channel details, lists), how results are filtered, or any limitations. For a tool with 2 parameters and no structured output info, the description should provide more context to guide usage effectively.
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 input schema has 100% description coverage, with clear documentation for 'query' and 'limit'. The description adds no additional meaning beyond what the schema provides, such as examples or context for parameter usage. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'チャンネルを検索します' (Search for channels) clearly states the verb ('search') and resource ('channels'), making the basic purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'search_categories' or 'get_streams', which might also involve channel-related operations. The purpose is stated but lacks specificity about what makes this search unique.
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 any context, prerequisites, or exclusions, such as how it differs from 'get_streams' or 'search_categories'. Without this, an agent might struggle to choose the right tool among siblings.
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 full burden but only states what the tool does without behavioral details. It doesn't disclose if this is a read-only operation, requires authentication, has rate limits, or what the return format might be (e.g., JSON structure, error handling). This is inadequate for a tool with zero 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 a single, efficient sentence in Japanese with zero wasted words. It's appropriately sized for a simple retrieval tool and front-loads the core purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 a simple input schema, the description is incomplete. It doesn't explain what information is returned (e.g., game details, metadata), potential errors, or behavioral context, leaving significant gaps for the agent to infer usage.
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 schema description coverage is 100%, with the parameter 'name' clearly documented as 'ゲーム名' (game name) in the schema. The description adds no additional parameter semantics beyond this, so it meets the baseline of 3 where the schema does the heavy lifting.
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 '取得します' (get/retrieve) and resource '特定のゲームの情報' (information of a specific game), making the purpose understandable. However, it doesn't differentiate from siblings like 'get_top_games' or 'search_categories' which also retrieve game-related information, preventing 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, exclusions, or compare to siblings like 'get_top_games' (for trending games) or 'search_categories' (for broader searches), leaving the agent with no contextual usage information.
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 full burden for behavioral disclosure. It mentions retrieving 'currently live' streams but doesn't describe return format, pagination behavior, rate limits, authentication requirements, or what happens when no streams match filters. For a read operation with 3 parameters, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a straightforward retrieval tool and front-loads the essential information about what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what data is returned, how results are structured, whether there's pagination, or any error conditions. The agent would need to guess about the response format and behavior despite having clear input parameters.
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 100%, so the schema already documents all 3 parameters with descriptions. The tool description adds no additional parameter semantics beyond what's in the schema. This meets the baseline of 3 when schema coverage is high, but doesn't provide extra value like explaining parameter interactions or providing usage 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 verb ('取得します' - get/retrieve) and resource ('現在ライブ配信中のストリーム' - currently live streaming streams), making the purpose immediately understandable. It doesn't explicitly differentiate from siblings like 'get_stream_info' or 'get_videos', but the focus on 'currently live' provides some implicit 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 like 'get_stream_info' (for specific streams), 'get_videos' (for past videos), or 'search_channels' (for channel information). There's no mention of prerequisites, limitations, or comparative use cases with sibling tools.
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 it 'gets a list' but doesn't describe what 'popular' means (e.g., based on views, ratings, or time), whether it's read-only (implied by 'get'), potential rate limits, authentication needs, or the format of the returned list. 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 a single, efficient sentence in Japanese: '人気のゲームのリストを取得します'. It's front-loaded with the core action and resource, with zero wasted words. Every part of the sentence contributes directly to explaining the tool's purpose, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 optional parameter) and no output schema, the description is incomplete. It lacks details on what 'popular' entails, the source of data, potential limitations, or example use cases. Without annotations or output schema, the description should provide more context to help the agent understand behavioral aspects and expected results, but it doesn't compensate for these 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?
The input schema has 100% description coverage, with the 'limit' parameter fully documented in the schema (type, description, min/max). The description doesn't add any meaning beyond this, as it doesn't mention parameters at all. With high schema coverage, the baseline is 3, as the schema does the heavy lifting and no additional param info is needed in the description.
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 purpose: '人気のゲームのリストを取得します' translates to 'Get a list of popular games', which is a specific verb ('get') and resource ('list of popular games'). It distinguishes from siblings like 'get_game' (singular) and 'search_categories', but doesn't explicitly differentiate from 'get_streams' or other list-fetching tools. This is clear but lacks explicit sibling differentiation.
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 this over 'get_game' for a single game, 'search_categories' for broader searches, or 'get_streams' for stream-related data. There's no context about use cases or exclusions, leaving the agent to infer usage from the name and description 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 the full burden of behavioral disclosure. It states what the tool does but doesn't describe any behavioral traits such as rate limits, authentication requirements, pagination behavior (beyond the cursor parameter), error conditions, or what format the comments are returned in. For a read operation with no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose without any unnecessary words or fluff. It's appropriately sized and front-loaded, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations, no output schema, and 3 parameters (with 1 required), the description is incomplete. It doesn't explain what the output looks like (e.g., comment format, pagination details), behavioral aspects like rate limits, or how it differs from sibling tools. For a data retrieval tool with multiple parameters, this leaves too much unspecified.
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 schema description coverage is 100%, with all three parameters ('videoId', 'limit', 'cursor') well-documented in the schema itself. The description doesn't add any additional meaning or context beyond what the schema provides (e.g., it doesn't explain what a 'videoId' is or how to obtain it). This meets the baseline for high schema coverage.
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 ('取得します' - get/retrieve) and resource ('アーカイブ動画のコメント' - archived video comments), making the purpose understandable. However, it doesn't distinguish this tool from potential sibling tools like 'get_videos' or 'get_stream_info' that might also retrieve video-related data, so it doesn't reach the highest level of specificity.
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 any prerequisites, exclusions, or specific contexts (e.g., only for archived videos vs. live streams), nor does it reference sibling tools like 'get_videos' that might be related. Usage is implied but not explicitly defined.
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 without mentioning any behavioral traits such as rate limits, authentication requirements, pagination, or what happens if the channel doesn't exist. For a tool with no annotation coverage, this leaves significant gaps in understanding its operation.
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 extremely concise—a single sentence in Japanese that directly states the tool's function. It's front-loaded with the core purpose and contains no unnecessary words or redundancy, making it highly efficient for an AI agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., video metadata, URLs, or a list), error conditions, or how results are structured. For a tool with two parameters and no structured output documentation, this leaves too much ambiguity for effective use.
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 doesn't add any parameter-specific information beyond what's already in the schema, which has 100% coverage with clear descriptions for both parameters (channelName and limit). The baseline is 3 when schema coverage is high, as the schema adequately documents the parameters without needing extra explanation in the description.
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: 'チャンネルのビデオを取得します' (Get videos from a channel). It specifies the verb (取得/retrieve) and resource (ビデオ/videos) with channel context. However, it doesn't differentiate from sibling tools like 'get_clips' or 'get_streams', which also retrieve channel content, 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.
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. With sibling tools like 'get_clips' (for clips) and 'get_streams' (for live streams), there's no indication of when video retrieval is appropriate versus these other content types. 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 the full burden of behavioral disclosure. It only states what the tool does ('get a list'), without mentioning any behavioral traits such as whether it's read-only, requires authentication, has rate limits, or what the output format might be. 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.
Conciseness5/5
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 any wasted words. It is appropriately sized and front-loaded, 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.
Completeness2/5
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 effective tool use. It does not explain what the returned list contains (e.g., badge details, formats), any limitations, or error conditions. For a tool that likely returns structured data, this omission reduces its utility for an AI agent.
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 tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description does not need to add parameter semantics, as there are none to document. This meets the baseline expectation for tools without parameters, as it avoids unnecessary details.
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: 'グローバルチャットバッジのリストを取得します' (Get a list of global chat badges). It specifies the verb '取得します' (get) and the resource 'グローバルチャットバッジのリスト' (list of global chat badges), making it easy to understand what the tool does. However, it does not explicitly differentiate from sibling tools like 'get_global_emotes' or 'get_channel_info', which slightly limits its clarity 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.
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 does not mention any specific contexts, prerequisites, or exclusions, nor does it refer to sibling tools like 'get_global_emotes' for related data. This lack of usage context leaves the agent without clear direction on appropriate scenarios for tool selection.
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 ('get a list') without any additional context on traits like rate limits, authentication needs, pagination, or response format. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence in Japanese that directly states the tool's purpose without any fluff or redundancy. It is appropriately sized and front-loaded, making it efficient and easy to understand, with every word earning its place.
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 (0 parameters, no output schema, no annotations), the description is minimally adequate. It states the basic action but lacks completeness for effective use, as it does not cover behavioral aspects like response format or platform context. With no output schema, the agent is left guessing about return values, making this description incomplete for optimal tool invocation.
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 tool has 0 parameters, and schema description coverage is 100%, so there is no need for parameter details in the description. The baseline for 0 parameters is 4, as the description does not need to compensate for any missing schema information, and it correctly avoids unnecessary parameter discussion.
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: 'グローバルエモートのリストを取得します' translates to 'Get a list of global emotes.' This specifies the verb ('get') and resource ('global emotes list'), making the intent unambiguous. However, it does not differentiate from sibling tools like 'get_global_badges' or 'get_channel_info,' which also fetch lists, 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 does not mention any context, prerequisites, or exclusions, such as whether it's for Twitch or another platform, or how it differs from similar tools like 'get_global_badges.' This lack of usage context leaves the agent without direction on selection.
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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