YouTube

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 only states the high-level action and gives no details about response format, pagination of recent videos, required permissions, or any limitations. This is a minimal disclosure that doesn't enrich the agent's understanding of the tool's behavior.

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

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

The description is a single concise sentence: 'Get details and recent videos for a YouTube channel.' It is front-loaded with the verb and resource, contains zero fluff or redundant phrases, and communicates the core purpose effectively in as few words as possible.

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?

The tool has no output schema and no annotations, and the description provides only a terse summary of the return content ('details and recent videos') without specifying what fields or structure to expect. Given the ambiguity of 'details' and the lack of behavioral context, the description is incomplete for an agent that needs to interpret the tool's output reliably.

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 each parameter (channelId, lang, location) has a schema description. The tool description adds no extra parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.

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

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

The description clearly states the action ('Get') and the resource ('details and recent videos for a YouTube channel'), making its purpose unambiguous. It implicitly differentiates from siblings like video_info (video-specific) and kids_channel (kids-focused) but doesn't explicitly name alternatives, so it doesn't fully earn a 5.

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

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

The description implies when to use this tool (when you need channel details and recent videos) but provides no explicit when-not-to-use guidance or alternatives. There is no mention of using kids_channel for kids content or video_info for video-specific data, leaving selection somewhat inferred.

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 does not mention pagination (nextCursor), sorting options, language/location defaults, or any potential side effects/return format. This leaves significant behavioral traits undisclosed.

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?

One concise sentence that immediately conveys the core purpose. No redundancy or filler.

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?

With 6 parameters, no output schema, and no annotations, the description is too thin. It does not explain what the tool returns, how to use pagination, or how to retrieve specific comment threads, leaving important operational context missing.

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 all parameters. The description adds no extra parameter details, but baseline 3 is appropriate since the schema handles the heavy lifting.

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 function with a specific verb ('Get') and resource ('comments for a YouTube video'), which distinguishes it from all sibling tools that focus on other resources like transcripts, music, or search.

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

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

No guidance is provided on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description simply states what it does without contextual use cases or comparison to sibling tools.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states the action and library, but does not disclose error conditions (e.g., no subtitles available), return format, or any limitations. This is insufficient for an agent to predict behavior.

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

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

The description is a single concise sentence that front-loads the action and resource. It avoids unnecessary words, though it could be more informative without sacrificing brevity.

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?

Since there is no output schema, the description should indicate return structure, but it does not. It also omits usage context like supported languages, failure behavior, and relationship to sibling tools, leaving the agent without enough detail for reliable invocation.

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

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

Schema coverage is 100% with both parameters described (videoId and lang). The description adds no extra parameter context beyond the schema, such as how lang defaults or interacts with the transcript. Baseline of 3 is appropriate since schema handles semantics.

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 retrieves transcript/subtitles for a YouTube video using a specific library. The verb 'Get' and resource 'transcript/subtitles' provide clear purpose, though it does not explicitly differentiate from sibling tools like get_transcript_languages.

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

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

No guidance is provided on when to use this tool versus alternatives such as get_transcript_languages or video_info. There are no prerequisites mentioned (e.g., video must have captions) or exclusions for when not to use it.

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, the description carries full burden for behavioral disclosure. It does not mention return format, whether the list includes auto-generated captions, authentication requirements, or error handling. The word 'available' hints at dynamic results but adds little depth.

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, front-loaded sentence that directly states the tool's purpose with no redundancy or filler.

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 tool with one parameter and no output schema, the description explains the core function, but it lacks details about the response structure (e.g., language codes vs names) and how this integrates with sibling tools like get_transcript. It is adequate but leaves 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% since the only parameter videoId is described as 'The YouTube video ID'. The tool description adds no further parameter semantics, so the baseline of 3 is appropriate.

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

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

The description uses a specific verb ('Get') and resource ('available transcript languages') with a clear object ('YouTube video'). It distinguishes from siblings like get_transcript by focusing on the language availability step.

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 this tool is used to check available transcript languages for a video, likely before retrieving a transcript. However, it does not explicitly state when to use it versus get_transcript or other siblings, and no exclusions are provided.

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

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only says 'Get', implying a read operation, but lacks details about permissions, rate limits, response structure, or any side effects. This is insufficient for a tool with no annotation support.

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, front-loaded sentence with no filler words. It is appropriately concise for its simple purpose, though it omits potentially useful details. No redundant information is present.

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 an output schema and annotations, the description is too terse. It does not explain what 'channel information' includes, whether videos are returned as a list or paginated, or any expected output format. For a required-parameter tool, this is incomplete.

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 baseline is 3. The description adds no extra parameter context beyond the schema. It does not explain how 'lang', 'location', or 'channelId' affect results beyond what the schema already states.

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 states a clear verb+resource: 'Get channel information and videos on YouTube Kids'. The phrase 'on YouTube Kids' distinguishes it from the sibling 'channel' tool, though it doesn't explicitly name the alternative. The name 'kids_channel' reinforces the specificity.

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

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

No guidance is provided on when to use this tool versus alternatives like 'channel' or 'kids_search'. The description only states what it does, not when it should be preferred. There are no exclusions or alternative tool mentions.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action, with no mention of pagination via nextCursor, return format, or any constraints. This is minimal disclosure beyond the tool's name.

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, front-loaded sentence with no wasted words. It efficiently conveys the core purpose without unnecessary elaboration.

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

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

For a 4-parameter tool with no annotations and no output schema, the description is incomplete. It does not explain pagination behavior, result structure, or usage scenarios. The schema covers parameters but not the broader behavioral context.

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

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

Schema description coverage is 100%, so all four parameters are already documented with clear descriptions in the schema. The description adds no additional parameter context, warranting the baseline score of 3.

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

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

The description clearly states the action (Search) and resource (YouTube Kids for videos), which is specific and unambiguous. However, it does not explicitly differentiate from the general 'search' sibling tool, though the 'YouTube Kids' qualifier hints at the distinction.

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

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

There is no guidance on when to use this tool versus alternatives like 'search' or 'kids_channel'. The description provides no context or exclusions, leaving the agent to infer usage from the name alone.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It indicates a read operation via 'Get', but says nothing about return format, authentication, rate limits, or potential errors. The transparency is minimal beyond the implied read-only nature.

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, front-loaded sentence with no filler words. It efficiently communicates the core purpose without redundancy, making it appropriately sized for the tool's simplicity.

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?

The tool has a simple, well-documented schema and a clear purpose, so it is adequate for basic invocation. However, the lack of annotations and output schema means the description doesn't clarify what 'video information' includes or any edge-case behavior, leaving some ambiguity.

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

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

The input schema provides full descriptions for all three parameters (videoId, lang, location) with 100% coverage. The tool description adds no parameter-level detail beyond what the schema already states, so the baseline score of 3 is appropriate.

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

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

The description uses a specific verb ('Get') and a clear resource ('video information') scoped to 'YouTube Kids', making the tool's function immediately clear. It distinguishes from siblings like 'video_info' and 'music_video' by the platform qualifier, though it doesn't explicitly name an alternative.

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 YouTube Kids video information, but provides no explicit when-to-use guidance or alternatives. There are no exclusions or prerequisites mentioned, relying solely on the tool name and description to convey context.

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

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

No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It only mentions 'Get album information' with no detail on return format, authentication requirements, rate limits, or potential side effects. The tool is likely read-only, but the description does not confirm this or add any operational context beyond the action itself.

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 is front-loaded with the action. It contains no redundant or filler language. While extremely terse, it is appropriately sized for a simple getter tool, though some contextual additions would be beneficial without sacrificing conciseness.

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

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

The tool has no output schema and only a sparse description. There is no explanation of what 'album information' includes (e.g., title, artist, tracks, release date), nor any usage context or return value details. Given that the description is the only source of behavioral context, it is incomplete for an agent to know what to expect. The high schema coverage mitigates parameter ambiguity but does not compensate for the lack of output or usage context.

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

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

The schema has 100% coverage for the three parameters (albumId, lang, location), each with descriptions. The tool description itself adds no parameter semantics beyond what the schema already provides. According to the rubric, when schema coverage is high (>80%), the baseline is 3, and the description does not need to repeat schema details. No additional value is added.

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 function: 'Get album information on YouTube Music.' It identifies a specific verb ('Get') and resource ('album information'), which distinguishes it from sibling tools like music_artist or music_playlist. However, it does not explicitly differentiate from those siblings via an alternative hint, so it misses the top 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?

There is no guidance on when to use this tool versus alternatives. The description simply states what it does, with no mention of exclusions, prerequisites, or scenarios. For example, it does not say 'Use this for album details; for artist info use music_artist.' This leaves the agent without contextual decision support.

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 disclosing behavior. It only says 'Get artist information' without explaining what data is returned, whether the operation is read-only (though implied), what the output structure looks like, or any rate limits or authorization requirements. This is a minimal disclosure for a tool with zero annotation support.

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 concise sentence, 'Get artist information on YouTube Music', which is short and front-loaded with the core purpose. It does not contain wordy or redundant content. However, it is so brief that it sacrifices necessary detail, but for conciseness this is appropriately minimal.

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, one required), the absence of an output schema, and the lack of behavioral detail, the description is incomplete. It does not mention return values, the nature of the artist information, or any distinctions from similar music-related tools. A description with more context about expected output or use cases would be necessary for full completeness.

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

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

The input schema covers all three parameters (lang, artistId, location) with descriptive comments, achieving 100% schema_description_coverage. The description itself adds no additional parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.

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

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

The description 'Get artist information on YouTube Music' clearly states the verb (get) and resource (artist information) and specifies the platform (YouTube Music). It is not a tautology and is understandable. However, it does not differentiate from sibling tools like music_related or channel, which could also serve artist-related information, so it lacks the distinction needed for a 5.

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

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

The description provides no guidance on when to use this tool versus alternatives such as music_album, music_related, or channel. There is no mention of use cases, prerequisites, or exclusions, so an AI agent is left to infer the tool's applicability from the name alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It conveys a simple read operation but does not mention authentication requirements, personalization, locale effects, or response structure. The description adds minimal context beyond the basic action.

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 sentence with no redundant words. It is perfectly concise and front-loaded, stating exactly what the tool does without waste.

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 an output schema and annotations, the description should compensate by explaining what the Explore page contains or what the response looks like. It does not, leaving a sparse picture. For a simple tool with two optional parameters, more context about lang and location effects would be expected.

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?

Both parameters are fully described in the input schema with default values and examples ('en', 'US'), so the description adds no further semantic value. With 100% schema coverage, the baseline score of 3 is appropriate.

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

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

The description uses a specific verb 'Get' and identifies the resource 'Explore page on YouTube Music', clearly stating the tool's function. It is distinguishable from sibling music tools by its unique resource, though it does not explicitly differentiate itself from alternatives.

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

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

No guidance is provided on when to use this tool versus alternatives like music_search or music_suggest. The description only states the action without mentioning 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.

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states the basic operation. It does not disclose behavior for missing lyrics, API limitations, or the response structure, leaving the agent to infer safety and data expectations.

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

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

The description is a single, direct sentence with no filler or redundant information, making it highly efficient.

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?

The tool is simple with three documented parameters, but the description lacks usage guidance, behavioral context, and output expectations. While sufficient for basic selection, it is not complete for an agent handling edge cases or choosing among related music/video tools.

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 covers 100% of parameters with descriptions, setting a baseline of 3. The description adds no additional meaning beyond implying the target video is identified by videoId, so it does not compensate further.

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 lyrics') and the resource ('a YouTube Music video'), distinguishing it from sibling tools like music_video (video details) and get_transcript (spoken transcripts). The verb is specific and the scope is unambiguous.

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

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

The description provides no guidance on when to use this tool versus alternatives such as music_video or get_transcript. No mention of prerequisites (e.g., that videoId must be from YouTube Music) or exclusions is included.

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 bears full responsibility for disclosing behavior. It only states a benign 'Get' operation but omits any mention of pagination (despite a 'nextCursor' parameter), language/location handling, or potential side effects. This is a significant transparency gap for a tool with multiple parameters.

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, front-loaded sentence that states the core purpose without redundancy. It could be considered too sparse, but as a concise statement it is well-structured and earns its place by naming the tool's scope.

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

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

Given the complexity (4 parameters, no output schema, no annotations), the description is incomplete. It does not mention what the response contains, how pagination works, or how language/location affect results. The presence of multiple sibling tools also demands clearer differentiation, which the description fails to provide.

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 baseline is 3. The description itself adds no parameter information, but the schema already explains every parameter, including defaults and the purpose of 'nextCursor'. The description does not need to compensate, so a score of 3 is appropriate.

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

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

The description uses a specific verb ('Get') and resource ('playlist information on YouTube Music'), clearly distinguishing it from the sibling 'playlist' tool. However, it does not specify what 'information' includes (e.g., metadata, tracks, pagination), leaving some ambiguity about the exact scope.

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 gives no guidance on when to use this tool versus alternatives like 'playlist' or 'music_search'. It does not mention any context, prerequisites, or exclusions, leaving the agent to infer usage solely from the name and sibling list.

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. The word 'Get' implies a safe read operation, but the description does not explicitly state that it is read-only, nor does it disclose what kind of related content is returned, whether pagination or filtering applies, or any rate-limit or error behavior. It adds minimal transparency beyond the verb itself.

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 concise sentence, 'Get related content for a YouTube Music video,' which is front-loaded and contains no filler or repetition. It efficiently states the core purpose without wasting words.

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?

The tool has no output schema, so the description should explain what 'related content' means and what the agent can expect in the response. It fails to do so, leaving a significant gap for a tool with 3 parameters and a behavior that is not self-evident. The sibling context hints at many types of music-related data but does not clarify this tool's exact output.

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?

All three parameters (videoId, lang, location) are fully described in the schema with 100% coverage, so the baseline of 3 applies. The description does not add any additional meaning beyond the schema—it does not even mention the parameters—but because the schema already explains them clearly, no deficiency is introduced.

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 uses the verb 'Get' and identifies the resource as 'related content for a YouTube Music video,' which is clear enough as a read operation. However, it lacks specificity—'related content' could mean videos, songs, artists, or albums—and it does not distinguish this tool from siblings like music_upnext or music_suggest, which likely serve similar purposes.

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 the many related sibling tools (e.g., music_video, music_lyrics, music_artist). It does not mention any alternatives, prerequisites, or typical scenarios, leaving the agent to guess when this should be invoked.

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 available, the description carries the full burden of behavioral disclosure. It only states that it searches, with no mention of result format, pagination, filtering, or any other behavior. This is insufficient for an agent to know what to expect.

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 sentence and front-loaded with the action. However, it is under-specified with vague 'etc.' and lacks meaningful detail beyond the bare function, making it less effective than truly concise but informative descriptions.

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 search tool with full schema coverage and no output schema, the description barely meets the minimum viable bar. It states the core function but omits any guidance on result handling or usage context, leaving the agent to infer too much.

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

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

The input schema provides complete descriptions for all three parameters, including defaults for lang and location. The description adds no additional parameter semantics, so the baseline of 3 applies 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 searches YouTube Music and lists content types (tracks, artists, playlists). The verb 'Search' and resource 'YouTube Music' distinguish it from sibling tools like general search and kids_search, though the trailing 'etc.' is somewhat vague.

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

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

No guidance is provided on when to use this tool versus alternatives such as the general search tool or kids_search. The intended usage is implied by the name and domain, but there is no explicit context, exclusions, or alternative recommendations.

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 explaining behavior. It merely states the function without disclosing return format, pagination, result limits, or any language/location fallback behavior. The read-only nature is implied but not explicitly stated, and no additional context is added beyond the tool name.

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, front-loaded sentence that is efficient and free of verbosity. It states exactly what the tool does with no filler words.

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?

The tool is simple and the schema covers parameters, but with no output schema and no annotations, the description could do more to clarify return values or usage context. It does not explain potential limitations (e.g., it only returns suggestions, not full results) or distinguish itself from similar tools, making it minimally viable but not comprehensive.

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

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

The input schema has 100% description coverage, with each parameter (query, lang, location) already described in the schema. The description adds no extra parameter-level semantics, so the baseline score of 3 applies.

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 function: 'Get search suggestions (autocomplete) on YouTube Music.' It uses a specific verb ('Get'), names the resource ('search suggestions'), and scopes it to YouTube Music, which distinguishes it from sibling tools like 'music_search' (full search) and 'suggest' (generic suggestions).

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 explicit guidance on when to use this tool versus alternatives. It does not mention that this is for autocomplete-only and not full search results, nor does it reference sibling tools like music_search or suggest. The only implicit hint is the word 'autocomplete'.

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, and the description does not disclose response format, limitations, or side effects. The word 'Get' implies a read operation, but the description fails to convey what the returned queue looks like or any other behavioral traits.

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

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

The description is a single, direct sentence that front-loads the action and avoids unnecessary detail. Every word contributes to the meaning.

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?

The description covers the core purpose, but with no annotations and no usage guidance, it leaves gaps. For a simple getter, it is minimally adequate but not complete for an agent to fully understand expected behavior or alternatives.

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 parameters are already fully documented. The description adds no additional meaning to the parameters, and the baseline applies.

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 function with a specific verb ('Get') and resource ('Up Next autoplay queue') scoped to a YouTube Music track. This distinguishes it from sibling tools like music_related by referencing a unique feature.

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

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

No explicit guidance is provided on when to use this tool versus alternatives. The intended use is implied by the description but not clearly contrasted with music_related or music_suggest.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the purpose ('Get video information') without revealing traits such as read-only nature, return format, rate limits, or any side effects. This is a significant gap.

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

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

The description is a single, efficient sentence that front-loads the action and resource. It contains no filler or repetition, though it may be too brief to be fully informative.

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?

With 3 parameters, no output schema, and a set of closely related sibling tools, the description is too minimal. It lacks usage context, differentiation from siblings, and any indication of what information is returned, making it incomplete for reliable tool selection.

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% (both 'lang' and 'location' have descriptions, and 'videoId' is labeled 'The YouTube Video ID'), so the schema already explains all parameters. The description adds no additional parameter context, but the baseline of 3 is appropriate.

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

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

The description clearly states the verb 'Get' and resource 'video information on YouTube Music', making the core purpose apparent. However, it does not explicitly differentiate from sibling tools like 'video_info' or 'music_related', so it lacks sibling distinction.

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

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

There is no guidance on when to use this tool versus alternatives. The description does not mention any context, exclusions, or preferred scenarios, leaving the agent without decision-making support.

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 must carry the full burden. It only states 'retrieve' and vaguely mentions output as 'details and videos', but does not disclose output format, pagination, authentication requirements, or any limitations. This is insufficient for a tool with no annotation support.

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, succinct sentence that immediately states the tool's function. Every word contributes to meaning, with no redundancy or filler, making it appropriately sized and front-loaded.

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?

The tool is relatively simple, and the schema covers all parameters. However, there is no output schema and no annotations, leaving the agent to infer return structure and operational constraints. The description provides the essential purpose but lacks finer details like pagination, response format, or edge cases.

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

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

The input schema fully describes all three parameters including defaults and examples, achieving 100% coverage. The description adds no additional parameter semantics beyond what the schema already provides, so a baseline score of 3 is appropriate.

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

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

Clearly states the tool retrieves details and videos from a specific YouTube playlist, with a direct verb and resource. However, it does not differentiate itself from the sibling tool 'music_playlist' or explain the distinction between general and music playlists.

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?

Provides no guidance on when to use this tool instead of alternatives. With siblings like music_playlist, channel, and video_info, the description lacks context about prerequisites, exclusions, or specific use cases.

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 must convey behavioral details. It only mentions the search targets, omitting any information about result format, pagination, sorting, or read-only nature. This is a significant gap for a tool with no annotation safety hints.

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, concise sentence that immediately conveys the core purpose. No unnecessary words or repetition.

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?

With full schema coverage and no output schema, the description provides the minimum viable context. However, it omits usage alternatives and behavioral details, which are important for a tool with no annotations. It is adequate for simple use but not complete.

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

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

The input schema provides thorough descriptions for all 4 parameters (100% coverage), so the baseline is 3. The description adds no extra parameter-specific meaning, but the schema already handles this dimension adequately.

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 a specific verb ('Search'), resource ('YouTube'), and scope ('videos, channels, and playlists'). It distinguishes itself from specialized sibling tools like kids_search and music_search by being the general YouTube search.

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

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

No guidance is given on when to use this tool versus alternatives such as kids_search, music_search, or suggest. The description only explains what the tool does, not when it should be selected.

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 must carry the full burden of behavioral disclosure. It only states 'Get search suggestions', which implies a read-only operation, but fails to mention output format, rate limits, authentication needs, or any other behavioral characteristics. The description is too thin to give the agent confidence about side effects or constraints.

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, front-loaded sentence with no unnecessary words. It gets directly to the point and is perfectly sized for the tool's simplicity.

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?

The tool is simple, and the schema fully documents parameters, but the description lacks details about the return value structure (e.g., whether it returns a list of strings) and any usage caveats. Since there is no output schema, the description could have provided a bit more context to be complete, but it is adequate for this basic suggestion tool.

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

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

The input schema has 100% coverage for all three parameters with clear descriptions, so the description adds no additional parameter meaning. The baseline for high schema coverage is 3, and the description does not compensate with any parameter-specific details that go beyond the schema.

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

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

The description clearly states a specific action ('Get') and resource ('search suggestions (autocomplete) for a query'). It is unambiguous about what the tool does. However, it does not explicitly differentiate itself from the sibling tool 'music_suggest', which is for music-specific suggestions, so it loses a point for lack of 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 for autocomplete suggestions but provides no explicit guidance on when to use this tool versus alternatives like 'search' or 'music_suggest'. There are no exclusions or preconditions mentioned, so the usage context is only implicit.

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 implies a read-only operation ('check') but does not mention what the response contains, whether it consumes quota, or any side effects. This is minimal transparency.

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

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

The description is a single, concise sentence that immediately states the action and resource. It is front-loaded and contains no unnecessary words.

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?

The tool lacks an output schema and annotations, so the description should explain the response format and usage timing. It does not, leaving the agent uncertain about what 'check' returns or how to act on the result. The description is too sparse for the available context.

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

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

Schema coverage is 100% with both 'lang' and 'location' fully described in the schema. The description adds no additional parameter semantics beyond what the schema already provides, so a baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: checking remaining API requests quota. It uses a specific verb (check) and resource (remaining API requests quota), and no sibling tool covers this functionality, so it distinguishes well.

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, nor any context such as prerequisites or typical scenarios. It simply states the action, leaving the agent to infer usage.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only hints at a read-only operation via the verb 'Get' but does not state side effects, permissions, output format, or any other behavioral characteristics.

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, tightly written sentence with no filler. Every word contributes to the core 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.

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

Given the absence of an output schema and annotations, the description should explain what 'detailed information' includes, but it does not. The presence of many sibling video tools increases the need for clarifying context, which is missing.

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

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

The input schema provides descriptions for all three parameters (videoId, lang, location), so the schema coverage is 100%. The tool description adds no additional meaning beyond the schema, so the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's action ('Get') and resource ('detailed information about a YouTube video'), which is a specific verb+resource pair. However, it does not differentiate from sibling tools like kids_video or music_video, so it loses the top score.

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

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

The description provides no guidance on when to use this tool versus alternatives, nor does it mention any preconditions or exclusions. The only implied usage is the basic purpose, which is not explicit enough for effective selection.

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