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 describes what data is returned but lacks critical behavioral details: it doesn't mention whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or response format. The description is functional but insufficient 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.

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

The description is appropriately concise—a single sentence that efficiently communicates the core functionality. It's front-loaded with the main purpose and includes key data points without unnecessary elaboration. However, it could be slightly more structured by separating the core functionality from optional features.

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 absence of annotations and output schema, the description is incomplete for a tool that retrieves detailed channel information. It lists data points but doesn't describe the return structure, potential pagination for videos, error handling, or API constraints. For a tool with rich data retrieval, this leaves significant gaps for the agent.

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

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

The schema description coverage is 100%, so the schema already fully documents both parameters. The description adds minimal value beyond the schema: it mentions 'optionally recent videos' which corresponds to the 'includeVideos' parameter, but provides no additional semantic context about parameter usage or implications.

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

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

The description clearly states the tool's purpose: 'Get detailed information about a YouTube channel' with specific data points (subscriber count, video count, view count) and optional recent videos. It uses a specific verb ('Get') and resource ('YouTube channel'), but doesn't explicitly differentiate from sibling tools like 'get_channel_videos' or 'get_video_details'.

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 sibling tools like 'get_channel_videos' (which might retrieve videos without channel metadata) or 'get_video_details' (which focuses on individual videos), leaving the agent to infer usage context.

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

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

No annotations are provided, so the description carries the full burden. It mentions sorting and returns video metadata, but does not disclose key behavioral traits such as pagination, rate limits, authentication needs, or what happens with invalid channel IDs. For a read operation with no annotation coverage, this leaves significant gaps in understanding the tool's behavior.

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

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

The description is concise and front-loaded, consisting of two sentences that directly state the tool's function and key features (sorting). There is no wasted text, making it efficient and easy to parse.

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

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

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is somewhat complete but lacks details on output format, error handling, and behavioral constraints. It covers basic functionality but does not fully compensate for the absence of annotations and output schema, leaving room for improvement.

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 fully documents all parameters. The description adds minimal value beyond the schema by implying sorting options, but does not provide additional semantics like examples or edge cases. 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.

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

The description clearly states the tool's purpose: 'List videos from a specific YouTube channel.' It specifies the resource (YouTube channel videos) and verb (list), but does not explicitly differentiate it from sibling tools like 'get_playlist_videos' or 'search_youtube', which also retrieve videos. This makes it clear but not fully distinctive.

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

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

The description implies usage by mentioning sorting options, but does not explicitly state when to use this tool versus alternatives like 'get_playlist_videos' for playlist-specific videos or 'search_youtube' for broader searches. It provides some context but lacks clear guidance on exclusions or prerequisites.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool retrieves information (implying read-only, non-destructive behavior) and lists specific data fields returned. However, it doesn't mention potential limitations like rate limits, authentication needs, or error conditions. The description adds basic context but lacks richer behavioral details.

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

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

The description is a single, efficient sentence that front-loads the purpose and lists key details without waste. Every word contributes to understanding the tool's function, making it appropriately sized and well-structured.

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

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

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally complete. It covers what the tool does and what data it returns, but lacks output format details or error handling. Without annotations or output schema, more context on behavioral aspects would improve completeness, but it's adequate for a simple read operation.

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

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

Schema description coverage is 100%, with the parameter 'playlistId' fully documented in the schema. The description does not add any parameter-specific details beyond what the schema provides (e.g., it doesn't explain format or usage further). According to rules, with high schema coverage, the baseline is 3 even without 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 action ('Get information') and resource ('YouTube playlist'), specifying what information is retrieved (title, description, video count, channel details). It distinguishes from siblings like 'get_playlist_videos' by focusing on metadata rather than video content, though it doesn't explicitly name alternatives. 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.

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

The description implies usage when playlist metadata is needed, but provides no explicit guidance on when to use this tool versus alternatives like 'get_playlist_videos' for video lists or 'get_channel_info' for channel data. It mentions what information is included, which hints at context, but lacks when-not scenarios or named alternatives.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions what data is returned (videos with metadata and position), it doesn't address important behavioral aspects like pagination (beyond the maxResults parameter), rate limits, authentication requirements, error conditions, or whether the operation is read-only (though implied by 'List'). For a tool 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.

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

The description is a single, well-structured sentence that efficiently communicates the tool's purpose and scope without unnecessary words. It's front-loaded with the core functionality and includes relevant details about the returned data. Every element of the description serves a clear purpose.

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

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description provides adequate basic information about what the tool does but lacks completeness. It doesn't address behavioral aspects like pagination, error handling, or authentication that would be important for an agent to use this tool effectively, especially with no annotations to fill those gaps.

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

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

The schema description coverage is 100%, with both parameters clearly documented in the schema itself. The description doesn't add any parameter-specific information beyond what's already in the schema (playlistId and maxResults with default). 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 specific action ('List all videos') and resource ('in a YouTube playlist'), including the scope of returned data ('with their metadata and position in the playlist'). It distinguishes itself from sibling tools like get_playlist_info (which likely returns playlist metadata) and get_channel_videos (which focuses on channel content rather than playlist content).

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 videos from a specific playlist, but provides no explicit guidance on when to use this tool versus alternatives like get_channel_videos or get_video_details. There's no mention of prerequisites, limitations, or comparative scenarios that would help an agent choose between similar tools.

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

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

With no annotations provided, the description carries full burden but only states what data is returned without disclosing behavioral traits like rate limits, authentication needs, error conditions, or response format. It mentions 'comprehensive metadata' but doesn't clarify if all listed fields are guaranteed or optional.

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 lists key fields without waste. Every word earns its place by specifying the tool's function and scope clearly.

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-only tool with 1 parameter and high schema coverage, the description is adequate but incomplete due to no output schema and no annotations. It covers the purpose and data fields but lacks behavioral context and usage guidelines, making it minimally viable with clear gaps.

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

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

Schema description coverage is 100%, so the schema already documents the videoId parameter with an example. The description adds no additional parameter semantics beyond implying it fetches data for 'a specific YouTube video', which aligns with the schema but doesn't provide extra value like format constraints or usage tips.

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

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

The description clearly states the verb 'Get' and the resource 'comprehensive metadata about a specific YouTube video', listing specific fields like title, description, duration, views, likes, tags, and thumbnails. It distinguishes from siblings by focusing on video metadata rather than channels, playlists, transcripts, or search results.

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 like get_video_transcript for transcripts or search_youtube for broader queries. It implies usage for video metadata but lacks explicit when/when-not instructions or named alternatives.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the return format ('full text with timestamps') and use cases, but it doesn't cover critical aspects like potential errors (e.g., if transcript is unavailable), rate limits, authentication needs, or whether it's a read-only operation. This leaves significant 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.

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

The description is appropriately sized and front-loaded, with two concise sentences that directly state the tool's function and utility. Every sentence earns its place by adding clear value without redundancy or unnecessary 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 (3 parameters, no output schema, no annotations), the description is partially complete. It covers the basic purpose and output format but lacks details on behavioral traits, error handling, and integration with sibling tools. With no output schema, it should ideally explain return values more thoroughly, but it does provide some context for a read operation.

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

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

Schema description coverage is 100%, so the schema fully documents all three parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain format details for 'videoId' or 'language' codes). This meets the baseline for high schema coverage but doesn't provide extra value.

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 verbs ('fetch') and resources ('transcript/captions for a YouTube video'), and it distinguishes the output format ('full text with timestamps'). However, it doesn't explicitly differentiate from sibling tools like 'get_video_details', which might also provide transcript-related information, keeping it from a perfect score.

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

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

The description implies usage contexts ('useful for video summarization and content analysis'), suggesting when to use it, but it lacks explicit guidance on when not to use it or alternatives among sibling tools (e.g., 'get_video_details' might offer similar data). This provides some context but falls short of comprehensive guidelines.

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

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

No annotations are provided, so the description carries full burden. It mentions what the tool returns ('video metadata including title, channel, views, and thumbnails'), which is helpful behavioral context. However, it doesn't disclose important traits like rate limits, authentication requirements, pagination behavior, or whether results are real-time. For a search tool with no annotations, 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 perfectly concise: two sentences that directly state the tool's function and what it returns. Every word earns its place with no redundancy or fluff. It's front-loaded with the core purpose followed by return 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 3 parameters with full schema coverage but no annotations and no output schema, the description provides basic purpose and return information. However, for a search tool that likely has rate limits and authentication considerations, the description should do more to compensate for the lack of structured behavioral data. It's minimally adequate but has clear gaps.

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

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

Schema description coverage is 100%, so the schema already fully documents all three parameters (query, maxResults, order) with their types, descriptions, defaults, and enum values. The description adds no parameter-specific information beyond what's in the schema. Baseline 3 is appropriate when the schema does all the work.

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 YouTube for videos by keyword' specifies the verb (search) and resource (YouTube videos). It distinguishes from siblings like get_channel_info or get_video_details by focusing on keyword-based search rather than retrieving specific entities. However, it doesn't explicitly contrast with get_channel_videos or get_playlist_videos which also return videos.

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 prefer search_youtube over get_channel_videos for finding videos from a specific channel, or when to use get_video_details for known video IDs. There's no context about use cases, prerequisites, or exclusions.

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