YouTube MCP Server

Server Quality Checklist

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Latest release: v0.1.2
Disambiguation4/5
Most tools are clearly distinct by domain (analytics, reporting, playlists, comments, video CRUD), with informative descriptions. The only mild confusion is between youtube_list_videos vs youtube_get_video (list vs detail is standard) and the multiple analytics_* tools are well-differentiated by their specific focus (traffic, geography, demographics, etc.). No two tools appear to do the same thing.
Naming Consistency4/5
The server consistently uses a youtube_ prefix followed by a clear verb_noun pattern (list_videos, get_video, create_playlist, upload_video, delete_video). Minor deviations: youtube_search_suggestions vs youtube_get_categories, and the reporting tools use a subnamespace (youtube_reporting_list_*) which is structured and predictable. Youtube_analytics_* tools follow a consistent subpattern, though the flat prefix gets long.
Tool Count3/5
At 40 tools, this is on the heavy side and exceeds the typical well-scoped range (3-15). However, YouTube's API surface is genuinely broad, spanning auth, search, channel/video/playlist CRUD, comments, captions, analytics (10+ dedicated tools), reporting, and uploads. The size is defensible for the scope, though it sits above the comfortable threshold.
Completeness5/5
The tool surface is remarkably comprehensive. It covers video lifecycle (upload, get, list, update, delete, thumbnail), playlist lifecycle, comments (list, post, reply), search, captions/transcripts, trending, channel info, full analytics coverage (overview, top videos, top shorts, demographics, geography, traffic, retention, revenue, day-of-week, content-type), and a complete reporting subsystem. The only minor gap is the absence of playlist update/delete tools, but playlist create/list/add/remove is largely covered.
Average 3.4/5 across 40 of 40 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
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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

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. However, the description provides zero behavioral details — no mention of whether auth is required, whether it's read-only, pagination behavior, or what happens if no jobs exist. For a tool with no annotation coverage, this is completely inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief at six words, which is efficient, but it borders on under-specification rather than true conciseness. A tool named youtube_reporting_list_jobs with the description 'List all active reporting jobs' is nearly tautological — the description adds only the 'active' and 'all' scope qualifiers beyond the name.
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 simple zero-parameter listing tool, the description is mostly adequate on the surface, but given no annotations, no output schema, and no differentiation from multiple reporting siblings, there should be more context about what a 'job' is, what the returned data contains, and how it relates to list_reports and list_types. The description is too thin to fully orient an 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 zero parameters, so parameter semantics are trivially satisfied. The schema coverage is 100% with nothing to document. A baseline of 4 is appropriate for a zero-parameter tool since there is nothing the description needs to add.
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 'List all active reporting jobs' which clearly identifies the verb (list) and resource (reporting jobs), and the 'active' qualifier adds scope. However, it doesn't distinguish itself from the sibling youtube_reporting_list_reports or youtube_reporting_list_types, making differentiation ambiguous. The purpose is clear but not well-differentiated from its reporting siblings.
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?
There is no guidance on when to use this tool versus the other reporting tools (list_reports, list_types), no mention of prerequisites like authentication, and no note about whether it should be used before create_job or download. The description offers no usage context or exclusions whatsoever.
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 and no output schema, the description carries the full burden but does not disclose what the response structure looks like, what 'quota usage' refers to, or what the agent should do based on results. It is a read-only query but this is not explicitly stated, and there is no info about rate limits or auth requirements to interpret results.
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 concise sentence that communicates the core purpose efficiently with no waste.
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 there is no output schema and no annotations, the description should explain what the returned authentication status and quota entries look like and how the agent should respond to them. This is a diagnostic/status tool where the output interpretation matters, so the description is under-specified.
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 zero parameters and 100% schema coverage, so there is nothing for the description to add. Baseline 4 applies for a parameterless tool.
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 checks authentication status and quota usage, which is a clear verb+resource. However, it does not distinguish itself from the sibling youtube_auth tool, leaving ambiguity about whether this overlaps with the actual authentication flow.
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 youtube_auth, or whether it should be checked before other operations. The timing context (e.g., 'call before making API requests') is absent.
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 doesn't disclose whether auth is required, whether adding is reversible (delete via youtube_remove_from_playlist), rate limits, error behavior on invalid playlist/video IDs, or side effects. The description only states the basic mutation action.
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?
Efficient docstring-style format with each parameter on its own line. Each sentence earns its place, no filler or redundancy. Could include more behavioral detail but the structure is clean and scannable.
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 mutation tool with no annotations and no output schema, this description is thin. It doesn't explain auth requirements, return values, error conditions, or whether added videos can be reordered. Given 40+ sibling tools exist and the tool mutates external state, more context is warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully explain the parameters. It describes playlist_id, video_id, and position with reasonable clarity including default behavior ('Defaults to end'). However, it doesn't explain what a Playlist ID vs Video ID looks like, or what 'position' constraints exist beyond 0-based, leaving some ambiguity at 0% 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 verb ('Add') + resource ('a video to a playlist'), which is specific and unambiguous. It distinguishes well from sibling tools like youtube_remove_from_playlist and youtube_create_playlist, though it doesn't explicitly name them.
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 on when to use this tool vs alternatives. It doesn't mention prerequisites like needing authentication (youtube_auth), whether the playlist must be owned by the user, or when one might prefer create_playlist vs add_to_playlist. No exclusion rules or context provided.
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 does not describe what dimensions/metrics are returned, whether results are limited to specific time ranges, how max_results interacts with output, or any thresholds/limits. For a data-retrieval tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, well organized with an Args section. No wasted words. Each sentence earns its place, and the parameter documentation is structured clearly.
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?
No output schema exists, and the description doesn't describe the return format (e.g., country codes vs names, whether it's a ranked list, what metrics besides views are included). For an analytics tool among 13 similar siblings, this under-specification makes it hard to distinguish and trust the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. The Args section documents all three parameters (start_date, end_date, max_results) with formats and defaults, which adds value beyond the bare schema. However, it doesn't clarify details like date format validation or how max_results bounds the country list.
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 states 'Get views by country' which is a clear verb+resource combination. It distinguishes reasonably from the many youtube_analytics_* siblings since it's specifically about geographic breakdown, though it doesn't explicitly differentiate itself from similar analytics tools.
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?
There is no guidance on when to use this tool vs alternatives like youtube_analytics_demographics, youtube_analytics_traffic_sources, or youtube_analytics_overview. No exclusion criteria or context about when geographic breakdown is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not state whether authentication is required, the consequence of creating a playlist (does it appear publicly?), or what the return value/result is. Mutation is implied but no side effects are disclosed.
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?
One-line summary plus a compact arg list. Efficient and front-loaded, no wasted words. The Args section is formatted cleanly for the three parameters.
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?
A mutation/write operation with no annotations and no output schema. It doesn't mention required auth, quota implications, or what a successful creation returns (e.g., playlist ID). For a tool that creates persistent YouTube content, this is a meaningful gap. Parameter documentation is acceptable but the operation-level context is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does list all three parameters with brief meanings (title, description, privacy_status with valid values). However, this adds minimal value beyond the schema itself, which already shows the properties and defaults. The privacy_status enum values ARE useful since there's no enum constraint in the schema.
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?
Clear verb+resource: 'Create a new playlist.' The description states the action and the resource, and distinguishes this from sibling tools like upload_video, list_playlists, and add_to_playlist by the 'create' verb. It's specific enough to not be confused with related playlist operations.
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 on when to use this tool vs alternatives. It doesn't mention authentication requirements (there's a youtube_auth tool that presumably is a prerequisite), or contrast with add_to_playlist (which adds items to an existing playlist). The description is purely declarative with no usage context.
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 mentions neither that posting requires OAuth/auth state, that comments are subject to YouTube moderation/spam filtering, that the comment is public immediately, nor what happens on failure. The description is just a bare directive with no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Reasonably concise - a single-sentence purpose followed by two simple parameter lines. There is no wasted verbiage. However, it could be slightly more structured with clearer separation between the action and parameter documentation, but the brevity is acceptable.
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?
This is a write/mutation tool with no annotations and no output schema. The description offers almost no context: it doesn't explain authentication requirements, rate limits, moderation outcomes, reply behavior, or error cases. For a tool that posts content publicly, significantly more behavioral context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for documenting the parameters. It does list both parameters (video_id and text) with one-line descriptions of what each is. However, it doesn't add format details (e.g., max text length, whether video_id format matters), but 'video_id: YouTube video ID' and 'text: Comment text' are minimally adequate labels.
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 'Post a new top-level comment on a video' with a specific verb ('post'), resource ('comment'), and scope ('top-level'). It distinguishes from the sibling tool youtube_reply_to_comment by specifying 'top-level', which meaningfully differentiates the action.
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 on when to use this tool vs alternatives. It does not mention that youtube_reply_to_comment is for threaded replies, does not state prerequisites like needing authentication (youtube_auth), or any limitations. The 'top-level' qualifier offers implied differentiation but no explicit when/when-not guidance.
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 doesn't state whether authentication is required, whether this is a write/mutation operation, whether there are rate limits, quota impacts, or any error conditions. For a mutation tool ('Reply') with zero annotation coverage, this is a meaningful gap in disclosing behavioral implications.
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 concise with the purpose stated in one line and parameters documented in a compact Args block. No wasted words, though the docstring format used in the Args section is mildly redundant given the schema already lists the parameters.
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 mutation tool with no annotations and no output schema, the description is under-specified. It doesn't disclose authentication requirements, success/failure behavior, return values, rate limits, or character length constraints. Given that tools like youtube_auth and youtube_auth_status are siblings, it seems auth is required, but the description never confirms this. A mutation action warrants more behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for parameter documentation. The Args section explains parent_id is 'The comment ID to reply to (from youtube_list_comments)' and text is 'Reply text'. Parent_id gets its source clarified, but text just restates the parameter name. There's no detail on limits (max length for text, format of parent_id). Minimal value added beyond the schema.
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 'Reply to an existing comment' with the verb 'reply' and resource 'comment'. It distinguishes from youtube_post_comment (which presumably creates a new top-level comment vs a nested reply). Though it doesn't explicitly name the sibling tool that's the alternative, the context makes the distinction reasonably clear.
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?
There is no guidance on when to use this tool vs alternatives. It doesn't mention that parent_id should come from youtube_list_comments output (though the arg docstring hints 'from youtube_list_comments'), nor does it explain when a reply vs a new post is appropriate. The parent_id source is mentioned in the Arg comment which provides some context, but no when/when-not guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It correctly identifies this as a read/retrieval operation, but does not disclose whether the video must be public, whether this requires authentication, what happens for deleted/unavailable videos, or any rate-limit or quota considerations. For metadata retrieval with zero annotation coverage, more behavioral context is warranted.
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?
Two sentences, zero waste. Front-loaded with the primary purpose and follows with a terse arg description. No filler or redundancy.
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?
With only 1 parameter and no output schema, the description should clarify what 'metadata and statistics' includes (views, likes, duration, etc.) and any call requirements such as auth. The description is minimal and leaves the agent unprepared regarding what it will receive back and under what conditions the call succeeds.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It includes an example video ID ('dQw4w9WgXcQ') and labels the param as 'YouTube video ID', adding a small amount of concrete value. However, it doesn't explain where to obtain the ID (e.g., from a URL), describe ID format constraints beyond the example, or mention whether the ID must be canonical versus anything else.
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?
Clear verb+resource: 'get detailed metadata and statistics for a specific video.' The purpose is distinct from siblings like youtube_get_channel (channel metadata) and youtube_list_videos (listing). While it doesn't explicitly name an alternative, the specific 'specific video' phrasing differentiates it from listing/search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by describing what it retrieves, but provides no explicit when-to-use vs alternatives, no prerequisites (e.g., whether auth is needed for private videos), and no exclusions. Slightly above baseline because 'get detailed metadata' implies a fetch/read operation distinct from search or list operations, but this is only implied, not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the operation but doesn't disclose behavioral traits such as whether this requires authentication, whether it consumes quota, what the response format looks like, or that it returns only top-level comments (replies excluded). The description adds a bit of behavior (order/max_results semantics) but falls short of full disclosure for a read operation 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 efficiently structured as a one-line purpose plus an args block. Each parameter is documented in a compact line. No wasted words, though the final line has a trailing blank space. It earns its sentences well, though it could not be considered wasteful.
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?
With no output schema and no annotations, the description provides the only context. While it documents all parameters well, it omits response format details (what fields each comment contains), any authentication requirement, pagination behavior, and rate limit constraints. For a 3-parameter tool with zero annotation coverage, more context would improve usability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and there are 3 parameters. The description compensates well by explaining video_id (YouTube video ID), max_results (number of comment threads, max 100), and order ('relevance' or 'time'). It adds the max cap of 100 and the valid order values, which go beyond the bare schema (which only shows defaults). This meaningfully aids parameter usage.
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 lists top-level comments on a video with a specific verb ('list') and resource ('top-level comments on a video'). It distinguishes from siblings like youtube_post_comment and youtube_reply_to_comment, though it doesn't explicitly differentiate from a potential alternative for listing replies. The purpose is clear and specific.
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 implies usage context (listing comments on a video) but provides no explicit when-to-use guidance or alternatives/exclusions. It doesn't mention that this returns only top-level comments and not replies, and doesn't distinguish from youtube_post_comment or youtube_reply_to_comment scenarios. No prerequisites or limitations are stated.
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 does not state whether this is a read-only operation, what metrics are returned (views, watch time, revenue?), how output is structured, or any rate limiting/auth requirements. For an analytics tool, the return format and metric definitions are critical context that's missing.
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 highly concise: one purpose sentence plus two parameter lines. Every sentence earns its place, and the parameter docs are clearly formatted with defaults. It's efficient though could arguably be extended with return-format info given the lack of output schema.
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?
This is a moderately complex analytics tool with no output schema and no annotations. The description omits what metrics are returned, whether the tool requires prior authentication (sibling tools include youtube_auth, suggesting auth is needed), and how the breakdown is structured. Given zero annotation coverage and no output schema, the description should provide significantly more behavioral and return-value context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully explain the parameters. It does explain start_date and end_date with default behaviors (28 days ago and today respectively). However, it doesn't specify the date format constraints beyond YYYY-MM-DD (already in the description) or describe interaction rules like whether end_date must be after start_date. The defaults are disclosed, which is useful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the purpose: 'Compare performance of Shorts vs long-form videos vs live streams.' This uses a specific verb ('compare') with a clear resource (content types on YouTube analytics), making it distinct from sibling tools like youtube_analytics_top_videos or youtube_analytics_daily. The three-way comparison (Shorts, long-form, live) is explicitly named.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for comparing content-type performance but gives no explicit 'when to use' guidance or exclusions. It doesn't name alternatives like youtube_analytics_overview or youtube_analytics_top_shorts. The context is clear enough that an agent would know when to pick this tool for a content-type breakdown, but it offers no explicit exclusions or alternative references.
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 shows this is a read-only analytics operation, but doesn't disclose what scope of data it returns (e.g., whether it covers all time or only what's available), auth requirements, rate limits, or what the response structure looks like. For an analytics tool with zero annotation coverage, this is under-specified on 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 compact and well-organized, with a clear first sentence, metric list, and parameter doc section. No wasted words. A minor structural note is that the metric list is nice and front-loaded. Good for the size.
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?
This is a moderately simple read-only analytics tool with 2 optional parameters and no output schema. The description covers purpose and both parameters adequately for basic use. However, given the 28+ sibling analytics tools, it doesn't clarify how 'overview' differs from 'daily,' 'top_videos,' or 'content_type_breakdown' in a way that helps an agent pick correctly. For the complexity level, this is acceptable but leaves differentiation gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does document both parameters (start_date and end_date with YYYY-MM-DD format and defaults). However, with only 0% schema coverage, the description is the sole documentation and doesn't fully compensate—e.g., it doesn't clarify what happens with null values, whether end_date must be >= start_date, or maximum allowed range. The format and defaults are helpful, but sparse.
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 states it gets a channel-level analytics summary with specific metrics (views, watch time, subscriber changes, likes, comments, shares). It's clear what the tool does, though it doesn't explicitly distinguish itself from the many other youtube_analytics_* siblings (top_videos, daily, geography, etc.). The 'channel-level' and 'summary' framing helps differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is for a high-level channel overview across a date range, which is a clear context. However, it doesn't explicitly state when to use this over the many other analytics siblings (daily, top_videos, demographics, etc.). No exclusions or alternatives mentioned. The overview vs. detailed distinction is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It discloses the output shape (100 data points, relative retention comparison) which is useful. However, it doesn't disclose things like whether data may be sparse/empty without enough views, the granularity of the 100 points (are they time-bucketed?), or any auth/attribution requirements. The description adds moderate value but has gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, front-loading the purpose in the first line, then adding the return format, then the Args section. The Args section is redundant with the schema (which already lists parameters and defaults), adding date format detail that belongs better in the schema description field, but overall it's tight and organized.
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?
No output schema exists, so the description partially compensates by describing return values (100 points, relative retention). The tool is moderate complexity—a single-video analytics query. The description covers purpose, output shape, and parameter formats. Missing: how the 100 points map to video length, whether partial data occurs for short videos, and clarity on retention vs average view duration. Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description must compensate for undocumented parameters. The description lists video_id, start_date, end_date and explains the date format (YYYY-MM-DD) plus defaults (28 days ago, today), which is helpful and exceeds the bare schema. However, it doesn't explain what video_id should look like or date range constraints. It partially compensates but with only 3 params the moderate explanation earns a 2 rather than a 1.
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 gets audience retention curves for a specific video, with a specific verb+resource. It distinguishes from siblings like youtube_analytics_overview and youtube_analytics_video_detail by focusing on the retention curve specifically. It could be more explicit about distinguishing from analytics siblings, but the purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (retention analysis for a single video) but doesn't explicitly state when to use this vs alternatives like youtube_analytics_video_detail or youtube_analytics_overview. No exclusions or alternative recommendations are provided. The 100 data points and relative retention framing hints at intended use but doesn't clarify selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It doesn't disclose that this is a read-only safe operation, whether it requires auth (there's a youtube_auth sibling), whether it needs a channel ID, date-range limits, or what the return format looks like. For a data-pull tool with zero annotation coverage, more behavioral context is needed.
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 compact and front-loaded with the core purpose sentence, followed by a brief elaboration and a clear Args section. It's efficient with no wasted sentences, though the Args section partially restates schema parameter titles at a basic level.
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?
For a tool with no output schema and no annotations, the description provides the core purpose but omits the return structure, whether it needs a channel/account selected, and any prerequisites (e.g., auth). The tool complexity is moderate (analytics query with 3 optional params), so the description is adequate but leaves gaps around output shape and setup requirements.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does explain start_date and end_date defaults (28 days ago / today) and video_id as an optional filter, which adds real meaning beyond the schema. However, it doesn't note that start_date and end_date are mutually required, what format errors might occur, or whether video_id requires a specific scope.
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 gets a traffic source breakdown for how viewers find content, listing example sources (search, suggested, browse, external). This clearly distinguishes it from sibling analytics tools like demographics, geography, and retention. However, it doesn't explicitly contrast against its closest sibling youtube_analytics_overview to differentiate scoping.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (get traffic source breakdown) but gives no explicit guidance on when to use this vs alternatives like youtube_analytics_overview or youtube_analytics_top_videos. It doesn't state when NOT to use it or which sibling is better suited for different analytic questions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states results are sorted by view count and exclude Shorts, which is useful. However, it doesn't disclose what per-video metrics are returned beyond sorting, whether this requires authentication/premium access, rate limits, or what error behavior looks like. For an analytics tool with zero annotation coverage, this is a moderate gap.
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 compact and well-organized. It leads with a clear summary sentence, then a return-value note, then structured Args with defaults. Every line earns its place with no irrelevant filler or redundancy. At roughly 40 words of useful content, it's appropriately sized for a simple 3-parameter analytics tool.
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?
For a tool with no annotations, no output schema, and 0% schema description coverage, the description provides the essential basics: purpose, return value, and parameter defaults. However, it lacks disclosure of what metrics are included beyond view count, whether this requires channel authentication (given siblings like youtube_auth exist), and does not explain the excluding-Shorts behavior in sufficient detail to help an agent reason about data completeness.
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 (0% description coverage) provides parameter names and defaults but no formatting details. The description adds date format guidance (YYYY-MM-DD), default behaviors for all three parameters, and the max_results cap of 200, which exceeds what the schema documents. However, it doesn't explain the relationship between date range and metric calculations or any constraints on valid date ranges.
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 returns top-performing videos by view count, uses a specific verb (get) with a clear resource (top videos). It distinguishes from siblings like youtube_analytics_top_shorts by explicitly excluding Shorts, and from youtube_analytics_overview by focusing on per-video metrics sorted by view count. However, it doesn't explicitly name sibling alternatives, which would strengthen differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the default date ranges (28 days ago to today) and that results are sorted by view count excluding Shorts, providing useful usage context. However, it doesn't explicitly state when to choose this tool over siblings like youtube_analytics_top_shorts or youtube_analytics_video_detail, or mention what the output metrics include. The 'excluding Shorts' is the main differentiator but remains implied rather than explicit guidance.
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 output is 'daily metrics' which offers some return-format context, but doesn't disclose auth requirements (likely needs youtube_auth), rate limits, what specific metrics are returned, or implications of missing data. For an analytics read tool this is a moderate transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose in the first line, followed by return-format context and an Args section. The Args block is somewhat redundant with the schema but useful given 0% schema coverage. No wasted sentences; reasonably efficient.
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?
For a tool with no output schema and no annotations, it provides the essentials: purpose, date defaults, and parameter formats. However, it lacks detail on which specific metrics are returned in the 'daily metrics', whether multiple videos require repeated calls, or any filtering options. Given the tool's moderate complexity (date-range analytics query) and many siblings, this is adequate but leaves room for more specificity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for all three parameters. It documents video_id as 'YouTube video ID', start_date with format 'YYYY-MM-DD' and default '28 days ago', and end_date with format 'YYYY-MM-DD' and default 'today'. This is meaningful value beyond the schema, which provides only type and default null, and correctly notes null means defaults apply.
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 states 'Get detailed analytics for a specific video over time' with a clear verb+resource (get analytics for a video). It sets itself apart from sibling tools like youtube_analytics_top_videos (aggregate rankings) and youtube_analytics_daily (which likely covers overall channel daily metrics) by being video-specific. However, it doesn't explicitly name alternatives, so some differentiation must be inferred.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (per-video detailed analytics over a date range) but gives no explicit when-to-use vs alternatives. Among many analytics siblings (overview, daily, top_videos, traffic_sources, demographics), it doesn't state when to choose this over youtube_analytics_daily or youtube_analytics_overview. The defaults (28 days ago to today) provide some context but no exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states fields are updated partially ('Only provided fields are updated'), but doesn't disclose whether this requires authentication, whether it's reversible, rate limits, or side effects. It also notes 'tags replaces existing tags' which is helpful but doesn't fully compensate for the missing annotation coverage on a mutating tool.
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 efficient and well-organized, with a one-line summary followed by an Args list that mirrors the parameter layout. The 'Only provided fields are updated' note is valuable and concise. No wasted sentences, though the Args list partially duplicates schema field names.
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?
For a 6-parameter mutating tool with no annotations, no output schema, and 0% schema description coverage, the description covers all parameters with useful constraints but omits behavioral context like authentication prerequisites (there is a youtube_auth sibling suggesting auth is needed), error handling, or what response to expect. It's adequate but not fully complete for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully compensate. It does describe each parameter (video_id, title, description, tags, category_id, privacy_status) with useful constraints: title max 100 chars, description max 5,000 chars, tags replaces existing tags, and enumerated privacy_status values. This adds meaningful semantics beyond the bare schema, though tag format details are light.
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 'Update metadata for an existing video' with a specific verb (update) and resource (metadata for an existing video). It distinguishes itself from siblings like youtube_upload_video (creation) and youtube_get_video (retrieval). However, it doesn't explicitly name sibling alternatives, slightly reducing differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through 'Only provided fields are updated; others remain unchanged' but doesn't explicitly state when to use this tool vs alternatives like upload_video or delete_video. No exclusions or alternatives are named, only implied through the action being described.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that it 'Fetches daily data and aggregates by weekday,' which is a meaningful behavioral trait. However, it doesn't describe the output format, whether auth is required (though siblings suggest youtube_auth), pagination behavior, or performance implications of fetching 90 days of data. Reasonable but not comprehensive.
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 compact: a two-sentence purpose, one-line usage context, and an Args block documenting both parameters. It's appropriately front-loaded with the core purpose first. The Args section is slightly redundant with the description's format mention but is standard formatting. No wasted words.
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?
For a read-only analytics aggregation tool with 2 optional parameters and no output schema, the description covers the essential purpose, defaults, and an example use case. However, it doesn't explain what metrics are included in the aggregation (views? watch time? likes?), which is material since the tool name says only 'performance' generically. It also lacks details on whether the output distinguishes active/upload days.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the schema has no descriptions for start_date or end_date. The description does provide some parameter context in the Args block: both default behaviors are stated (90 days ago, today) and the YYYY-MM-DD format is given. This adds real value beyond the bare schema, though the description covers only 2 parameters (which is all there are). Baseline 3 is appropriate since it compensates for the 0% 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 states a clear purpose: 'Get aggregated performance by day of week,' with a specific verb (get) and resource (aggregated analytics by weekday). It differentiates from sibling analytics tools with distinct dimensions (top_videos, traffic_sources, demographics), though the mention of day-of-week distinguishes it primarily by aggregation dimension rather than naming specific siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes 'Useful for scheduling uploads,' which gives clear context for when to use this tool. However, it doesn't explicitly state when NOT to use it or name alternative tools (e.g., youtube_analytics_daily for raw daily data, or youtube_analytics_overview for high-level metrics). No exclusions or alternatives are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose the return format, whether the tool fails gracefully if not monetized, pagination behavior, or granularity of data. For an analytics read operation, this leaves the agent guessing about response shape and failure modes.
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?
Concise and front-loaded with the core purpose in the first line. Followed by prerequisite and result components, then parameter documentation. Compact and organized with clear sections. Minor waste in repeating defaults that are in the schema.
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?
For a simple 2-param read-only analytics tool, the description covers the essentials: what it returns and the monetization prerequisite. But with no output schema and no annotations, it could add more about response structure or date range behavior. It's adequate but not rich—leaves the agent guessing about the exact shape of the revenue data returned.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does explain both parameters (start_date and end_date) with their defaults mentioned in prose. However, the description's mention of defaults could be construed as duplicating schema defaults. It adds the YYYY-MM-DD format hint which is mildly helpful. Baseline for schema-covered params would be 3, and the description adds some value but doesn't fully compensate for the 0% 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 it returns a revenue breakdown with specific components (estimated, ad, and YouTube Premium revenue). The verb 'get' + resource 'revenue breakdown' is specific. It distinguishes reasonably from sibling revenue tools like youtube_analytics_revenue_by_video, though it doesn't explicitly call out that sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
States the key prerequisite: requires YouTube Partner Program (monetized) membership. This is important contextual guidance that helps the agent know when this tool will/won't work. It lacks explicit alternative guidance but the monetization requirement provides useful context vs 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?
No annotations are provided, so the description carries full burden. It discloses the YPP requirement (useful), but does not describe what happens if the channel isn't in the program, whether revenue is in a specific currency, whether the revenue is estimated, or how zero-revenue videos are handled. For a financial data tool, more behavioral disclosure would be expected.
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 efficiently structured with a one-line summary, a prerequisite note, and a clean Args section. Each element earns its place. The Args block is a good structured format for parameter documentation, and the whole thing is compact without wasted prose.
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?
With 3 params, no annotation, and no output schema, the description needs to cover both invocation semantics and return behavior. It handles the params well and the YPP prerequisite. But for a revenue tool with no output schema, it doesn't describe what fields are returned per video (e.g., revenue amount, currency, views revenue vs. ad revenue breakdown), leaving the agent guessing about the return shape.
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 coverage is 0%, so the description must compensate. The Args section does describe all three params with types and defaults (start_date, end_date, max_results). This adds meaning not in the schema by stating date format (YYYY-MM-DD) and the max_results cap of 200. However, it doesn't explain date-range semantics beyond defaults or what 'max 200' means for the actual cap behavior.
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?
'Get revenue per video, sorted by highest revenue' is a clear verb+resource+sort description. It distinguishes from siblings like youtube_analytics_top_videos (view-based ranking) and youtube_analytics_revenue (aggregate revenue) by specifying per-video granularity with highest-revenue sorting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly notes the YouTube Partner Program requirement as a prerequisite. While it doesn't compare against sibling analytics tools, the 'revenue per video' framing and the YPP requirement give clear context for when this is applicable. It lacks explicit when-not-to-use guidance but provides a meaningful constraint.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states it returns per-Short metrics sorted by view count, but doesn't disclose whether this is read-only, what specific metrics are included, whether shorts-only content is considered, or any rate-limit/auth requirements. The behavior is partially disclosed but lacks depth for a data-retrieval tool.
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 compact and front-loaded with the core purpose in the first sentence. The parameter documentation is efficient. Minor waste: 'sorted by view count' is somewhat redundant given 'top-performing by views' but adds precision about ordering.
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?
For a simple analytics tool with 3 optional parameters and no output schema, the description covers the main inputs and output concept. However, it doesn't specify what metrics are returned (only views are mentioned), whether averages or totals are provided, and doesn't clarify behavior when no Shorts exist in the date range. These gaps matter for an analytics tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must document all 3 parameters. It does describe start_date (format YYYY-MM-DD, default 28 days ago), end_date (format, default today), and max_results (max 200). This adds format and default context beyond the bare schema. However, it doesn't clarify date semantics (inclusive/exclusive) or what happens when max_results exceeds 200.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get top-performing Shorts by views' with a specific verb (get), resource (Shorts), and metric (views). It distinguishes itself from siblings like youtube_analytics_top_videos by specifying 'Shorts' as the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the 'top-performing Shorts by views' framing and describes what it returns. However, it doesn't explicitly state when to choose this over youtube_analytics_top_videos or youtube_analytics_overview, nor does it mention any exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses OAuth requirement and ownership constraint, which is helpful. However, it doesn't describe what the response contains (list of caption track metadata?), pagination, or whether caption tracks exist for all videos. For a list operation with no annotations, it provides partial but not comprehensive 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?
Tight and compact: three short lines plus an Args section. Every sentence earns its place - purpose, auth requirement, scope constraint, and parameter doc. No filler or redundancy.
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?
Single simple parameter with no output schema, so structural complexity is low, which helps. However, for a read operation with zero annotations and no output schema, the description should say more about what gets returned (caption track list with languages/formats?), whether it works for videos without captions, and possible error states. It's adequate for basic selection but thin on behavioral detail.
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?
Only one parameter, video_id, with 0% schema description coverage. The description mentions 'video_id: YouTube video ID' in the Args section, which adds the decoding that it's a YouTube video ID. This adds some value beyond the bare schema (title 'Video Id'), though it's minimal. The parameter is self-evident from naming.
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?
Clear verb+resource: 'List available caption tracks for a video you own.' It specifies it lists caption tracks for a video, distinguishing it clearly from youtube_get_transcript (which presumably retrieves a transcript) and youtube_list_videos. It's specific about scope (videos you own). Not a 5 because it doesn't explicitly contrast with the transcript tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
States it requires OAuth and only works for videos on the authenticated user's channel, giving clear context on when it's applicable. It doesn't explicitly name alternative tools like youtube_get_transcript, but the ownership constraint provides useful exclusions. Doesn't mention alternatives explicitly, so not a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes parameters but doesn't disclose behavioral traits like pagination behavior, whether it requires prior authentication (a relevant consideration given youtube_auth exists), sorting, or what happens with results. The description is minimal and doesn't address the auth dependency this tool presumably has relative to its channel_id vs mine modes.
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 efficient, using a one-line purpose followed by a tight three-item args block. Every sentence serves a purpose (purpose + parameter definitions). It could maybe note the mine/channel_id exclusivity, but overall it's lean.
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?
For a listing tool with 0 required params and no output schema, the description is reasonably adequate. However, it doesn't address the auth requirement (relevant given youtube_auth sibling), result ordering, or the relationship between 'mine' and 'channel_id'. It also doesn't mention the playlist fields returned since there's no output schema to compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so parameter meaning isn't in the schema. The description does explain all three parameters (channel_id, mine, max_results with max 50), which adds real value beyond the schema itself. However, it doesn't clarify edge cases like what happens if both channel_id and mine are set, or whether channel_id is for a channel you don't own.
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 it lists playlists for a channel ('List playlists for a channel'), which is specific verb+resource. It distinguishes from siblings like list_videos and create_playlist by the resource being playlists, though it doesn't explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates the tool is for reading playlists, and the channel_id vs mine parameters suggest two usage modes. However, there's no explicit guidance on when to use this versus alternatives like youtube_search or youtube_reporting tools, nor when mine should be true versus channel_id.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does disclose that reports generate daily and take 24-48 hours to appear, which is useful behavioral context. However, it doesn't disclose whether the job is immediately active on creation, whether an existing job with the same report_type would conflict, or whether this requires specific auth states/permissions. The behavioral disclosure is partial.
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 compact and front-loaded with the core purpose, then adds timing expectations and Args documentation. Every sentence adds value. The Args section is a slight formatting departure but appropriate for Python-docstring style. No wasted words.
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?
With no annotations, no output schema, and 0% schema description coverage, the description must carry substantial weight. It covers the core purpose and timing but lacks detail on what the response contains (job ID? status?), potential error cases (what if report_type_id is invalid?), and lifecycle after creation. For a state-changing scheduling tool, more detail on expected return and failure modes would be warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. The Args section explains both parameters: report_type_id is clarified as coming from youtube_reporting_list_types, and name is described as optional and human-readable. This adds moderate value beyond the raw schema. However, 'report_type_id' is still somewhat underspecified about the exact format/expected value, though the pointer to list_types helps.
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 uses a specific verb ('Schedule a reporting job') identifying the resource and action clearly. It distinguishes this from siblings like youtube_reporting_list_jobs and youtube_reporting_download by implying creation/scheduling rather than listing or downloading, though it doesn't explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the timing behavior (24-48 hours for first report) which sets expectations for when results appear. However, it doesn't explicitly state when to use this versus alternatives like youtube_reporting_list_jobs, nor does it clarify prerequisites (e.g., must an auth exist first? Must report_type_id come from list_types?). The mention that report_type_id comes 'from youtube_reporting_list_types' is a weak pointer but not a full guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It does add some useful behavior context: reports are generated daily and retained for 60 days. This hints at freshness/availability windows. However, it doesn't disclose what report metadata is returned, whether reports require auth, or detail the response structure. Acceptable but not rich.
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 compact: one purpose sentence plus a retention detail plus a parameter note. Every sentence earns its place. The Arg line clarifies provenance of job_id. It's front-loaded with the purpose statement.
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?
For a simple single-parameter list operation with no output schema, the description is largely sufficient. The daily generation and 60-day retention are valuable context. It's complete enough for selection and invocation, though it could mention what fields each report contains or what the return list looks like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description's 'Args' section is the only parameter documentation. It explains job_id comes from create_job or list_jobs, which is genuinely useful provenance context. However, given only one simple parameter exists, the burden is low and the description adequately covers it.
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 states 'List available reports for a job' with a specific verb+resource combination. It's clear this lists reports tied to a particular job. It doesn't explicitly distinguish from siblings like youtube_reporting_list_jobs, but the job_id parameter and 'for a job' scope clarify the difference from listing jobs or types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions reports are 'generated daily and available for 60 days,' which gives contextual timing information. However, it doesn't explicitly state when to use this tool versus alternatives (e.g., list_jobs to find jobs, create_job to make one, download to fetch a report). The usage is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that it's a public endpoint with no quota/cost, which is useful behavioral info. However, it doesn't describe the return format, rate limits, or what happens with invalid language codes. The description gives some value but not rich behavioral context beyond the no-quota note and SEO framing.
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 compact and front-loaded with the core purpose, then adds the SEO use case and no-quota note, then documents the two params. Each sentence earns its place and there's no fluff or repetition. Well-structured and appropriately sized.
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?
For a simple 2-param, no-output-schema tool, the description is reasonably complete. It explains the purpose, use case, cost implications, and params. Gaps include return format/pagination and potential quotas even if the endpoint is 'public'. Given the simplicity, this is adequate but not exceptional — the parameter descriptions could add more depth.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists 'query: Partial search query to get suggestions for' and 'language: Language code (e.g., en, es)', which restates the schema fields with minimal added meaning. The 'partial' qualifier on query adds some value (indicating fuzzy matching), but there's no detail on format, length limits, or how language affects results. This is borderline insufficient for a 2-param tool.
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 it gets YouTube autocomplete/search suggestions for a query, which is a specific verb+resource+scope. It distinguishes from the sibling youtube_search (which presumably does full search) by being autocomplete/suggestions focused. Title is null but name is descriptive.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly notes it's 'useful for SEO keyword research' and that it has 'no quota cost (uses YouTube's public suggest endpoint)', giving clear context on when to choose this tool over other YouTube tools that require auth or quota. It doesn't explicitly name alternatives but the SEO/research framing plus no-quota highlight provides solid guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. The description doesn't disclose any behavioral traits such as auth requirements, return format, or whether it aggregates across channels. However, the operation is a read-only analytics query, which is low-risk, and the description adequately conveys the core function without needing heavy caveats.
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 compact and efficient, with a one-line purpose followed by parameter documentation. No wasted sentences. It's arguably minimal but every sentence earns its place. Not verbose enough to warrant a 5 given it's essentially just the summary line plus arg docs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter read-only analytics tool with both parameters documented, the description is adequate. No output schema exists, so the description could mention return format, but the tool is straightforward enough that the absence isn't critical. It's complete for the low complexity of this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description documents both parameters (start_date and end_date) with format and defaults, adding value beyond the bare schema. However, it doesn't explain semantics like inclusivity, timezone handling, or interaction between dates — the description covers the basics but not deeply. With the defaults explained, this is a baseline-fair compensation.
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 states 'Get audience demographics — age group and gender breakdown' which is a specific verb+resource and clearly identifies what data is returned. It differentiates well from sibling analytics tools (traffic_sources, geography, daily) by naming the specific dimensions. However, it doesn't explicitly contrast with these siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying the metrics (age group and gender) which helps distinguish from analytics siblings. There's no explicit when-to-use vs alternatives guidance, but the demographic focus is reasonably clear from the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does disclose the critical behavioral trait of irreversibility ('This action is irreversible'), which is the most important behavioral warning. However, it does not disclose other behaviors like auth requirements, whether confirmed/owned videos only can be deleted, permissions needed, or what happens to associated metadata/comments. The core destructive nature is disclosed but context around it is thin.
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 short and front-loaded with the key purpose in the first line, followed by the irreversibility warning. The Args section is minimal but useful. Every sentence earns its place, though the Args block is slightly redundant with the schema for a single param.
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?
For a single-param destructive tool, the description covers the essential purpose and the key warning (irreversibility). No output schema exists, but the description doesn't explain what a successful deletion returns, nor does it address edge cases (non-owned videos, already-deleted videos, auth requirements). Given it's a destructive operation with no annotations, more guidance on prerequisites (e.g., auth via youtube_auth) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and there's only one parameter. The description explains video_id as 'YouTube video ID to delete,' which adds semantic meaning by indicating the video must be the one being deleted. With only 1 param and 0% coverage, the description does compensate for the gap, though it could specify the format or where to find this ID.
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 uses a specific verb+resource ('Delete a video') with a clear subject. It distinguishes itself from siblings like youtube_update_video and youtube_upload_video by the deletion action. However, it doesn't explicitly differentiate from youtube_remove_from_playlist which could be confused as a similar destructive action, though the name makes the video-tool target clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear context of use (deleting a video) but does not give explicit when-to-use vs alternatives guidance or exclusions. The irreversibility warning implicitly suggests caution use, but there's no statement about when one would choose this over related tools or any prerequisites like authentication.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It does disclose 'Costs 1 quota unit,' which is useful operational context. However, it doesn't describe return structure or behavior quirks — though with no output schema, this is a minor gap for a simple enumeration tool.
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 tight and efficient — clear purpose, two use cases, quota cost, and a parameter documented in under 40 words. Front-loaded with the purpose statement. Slightly formulaic with the Args section but no wasteful prose.
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?
For a simple 1-param enumeration tool with no output schema, the description is reasonably complete. It covers purpose, usage contexts, cost, and the parameter. However, it doesn't mention what the response contains (categories list format), and there's no output schema to fill that gap, leaving the return format somewhat ambiguous.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It documents the region_code parameter well (format: ISO 3166-1 alpha-2, example 'US'), but the schema already conveys the name, default, and type. The description adds the format clarification and example, though not extensively beyond what the schema's 'Region Code' title hints at.
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 it 'lists available YouTube video categories for a region' — a specific verb+resource+scope. It doesn't explicitly distinguish from sibling tools, but the categories concept is reasonably unique among the variety of analytics/upload/comment tools present.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives two concrete usage contexts: 'useful for filtering trending videos or setting video category on upload.' It doesn't explicitly exclude alternatives, but provides actionable when-to-use guidance that connects to related sibling tools like youtube_trending and youtube_upload_video.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses it's a read operation implicitly ('List videos... Returns video summaries with stats'), notes the uploads-playlist proxy mechanism, and indicates result ordering. However, it doesn't disclose whether auth is required for the 'mine' path, what happens when no IDs/mine are given (error vs default behavior), or pagination details beyond max_results max of 50. Since this is a mutation-free listing tool, disclosure is adequate but not rich.
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?
Well-structured with a summary line followed by a 'Args' list. Efficient and scannable. The Args section is brief but the sibling-tool context shows many alternatives, and the description correctly focuses on what this tool uniquely does. Slight redundancy in stating channel vs playlist modes, but overall lean.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a listing tool with no output schema and no annotations, the description explains the core behavior (returns summaries with stats, most-recent first), the three access modes, and the max limit. This is reasonably complete for the tool's complexity. It could clarify default behavior when no source is specified and whether 'mine' requires prior auth, but given the tool's simplicity, this is near-complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate fully, and it does. It explains channel_id (uses channel uploads playlist), playlist_id (overrides channel_id), mine (authenticated user's videos), and max_results (max 50). This adds meaningful context beyond the raw schema types, though it could note the relationship that mine and channel_id are mutually exclusive or that exactly one source must be chosen.
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 (List) + resource (videos from a channel or playlist) and distinguishes two usage modes (channel vs playlist). It differentiates from siblings: youtube_get_video is singular, youtube_search is by query, youtube_list_comments is comments. However, it doesn't explicitly name alternatives like youtube_get_video, though the purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the channel vs playlist vs mine vs max_results modes and notes playlist_id overrides channel_id. It states 'sorted by most recent' which helps selection. However, it doesn't explicitly say when to use this vs youtube_search or youtube_get_video, nor mention that channel uploads playlist is used as a proxy. Implied usage, not explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a removal operation (implying mutation) and clarifies that the correct parameter is playlist_item_id, not video ID. However, it doesn't disclose prerequisites (e.g., whether auth is required via youtube_auth), error conditions, or consequences of removal. For a mutating operation with zero annotation coverage, more behavioral context would help.
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 compact at roughly 3 lines including Args. It's front-loaded with the action statement and uses a clean Args section. The 'not the video ID' clarification is efficient and earns its place. Slightly under-specified but well-structured.
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?
The description is accessible for a single-parameter tool, and the schema is minimal. It covers the key pitfall (playlist_item_id vs video ID) and points to a way to find the ID. However, with no annotations, no output schema, and no description of return/error behavior, it leaves the agent guessing about outcomes (e.g., success indication, error on invalid ID). For a mutating operation, this is a moderate gap.
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 explicitly adds meaning to the single parameter by warning that playlist_item_id is 'not the video ID', which is valuable semantic clarification beyond what the schema provides (which only labels it 'Playlist Item Id'). However, schema coverage is 0%, and while the description helps, it could elaborate more on how to obtain and verify a valid playlist_item_id.
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 ('Remove a video from a playlist') with a specific verb and resource. It distinguishes itself from siblings by specifying it works on playlist_item_id rather than video ID. However, it doesn't explicitly differentiate from the parallel 'youtube_add_to_playlist' sibling or clarify nested semantics beyond the ID distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells the agent where to find the required ID ('Use youtube_list_playlists or the Data API to find the playlist_item_id'), which is helpful usage context. It clearly distinguishes the playlist_item_id from the video ID, preventing a common error. It doesn't mention when to use this vs alternatives, but the tool is fairly unique in its purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose one important behavior: 'For large reports, the content may be truncated.' This is valuable transparency. However, it doesn't disclose other behaviors like whether the download requires prior API authentication, what happens with an invalid/expired download URL, or the CSV format specifics. The truncation note adds value but more could be disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise at ~30 words, front-loaded with the core purpose ('Download a report CSV'), followed by key behavior notes and parameter documentation. Every sentence earns its place: purpose, truncation warning, and parameter source. No redundancy or fluff.
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?
For a single-parameter download tool, the description covers the core essentials: purpose, output format, truncation behavior, and parameter source. However, it lacks details on error handling (expired URLs), authentication requirements, and whether the download URL expires (a common concern with YouTube reporting API URLs which have time-limited validity). Given there's no output schema to compensate, it's adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. The single parameter (download_url) is well-documented: the description says it comes from youtube_reporting_list_reports, which fully explains its origin and format. The 'Args:' section explicitly defines the parameter with its source. This is solid compensation for 0% schema coverage given there's only one parameter.
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 states a clear verb+resource: 'Download a report CSV.' It identifies the output (CSV content as text) and notes it relates to youtube_reporting_list_reports, which distinguishes it from other reporting tools. It could be slightly more explicit about the distinction from siblings like youtube_reporting_list_reports and youtube_reporting_list_jobs, but the purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'Download URL from youtube_reporting_list_reports,' which implicitly guides usage by linking to the upstream tool that produces this parameter. However, it doesn't explicitly state when to use this vs alternatives, nor does it note prerequisites like needing to run youtube_reporting_list_reports first. It also doesn't mention auth requirements, though the presence of youtube_auth/youtube_auth_status siblings suggests auth is relevant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that a browser window opens (user-facing behavior) and that it's a prerequisite step, but doesn't mention that this is a blocking/awaiting-user action, how long the flow may take, whether it's non-reversible, or what success/failure looks like. The description adds value but leaves gaps about the interactive nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately brief at two short paragraphs. It front-loads the core purpose in the first line and adds the prerequisite context in the second sentence. Minor spacing waste with the blank line, but otherwise efficient.
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?
This is a simple 0-param tool, so a short description is acceptable. However, given it's an authentication flow likely requiring user interaction in a browser, the description could mention the interactive/blocking nature and what happens on success or failure (e.g., a token is stored for subsequent calls). The return behavior is unspecified but no output schema exists to compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are 0 parameters and schema description coverage is 100% (vacuously, as there are no properties). With 0 params, the baseline is 4. The description appropriately doesn't attempt to document nonexistent parameters.
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 states 'Initiate OAuth 2.0 authentication flow' which is a specific verb+action, and clarifies it opens a browser window for Google OAuth consent. It's clear what the tool does, though it doesn't explicitly differentiate from youtube_auth_status, which is the nearest sibling representing the status check of this flow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states 'Required before using any tools that access private channel data or analytics,' providing explicit when-to-use context. It doesn't mention exclusions or alternatives, but does clarify the prerequisite nature clearly enough to guide usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the quota cost (1 unit), which is a meaningful behavioral trait. It's a read-only operation implied by 'get', which is fairly clear. It could add more about what the response looks like, but the quota disclosure and the nature of the operation provide reasonable transparency for a read-only fetch tool.
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 compact and well-structured. The one-line purpose statement, quota note, and parameter list with clear formats/examples are front-loaded and efficient. No wasted words. It could format the args more tightly, but it earns its place with useful specifics like the ISO reference, the category example, and the max limit.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only fetch tool with 3 self-documented parameters and no output schema, this is reasonably complete. The quota disclosure compensates for missing annotations. It lacks detail about the response shape (fields returned per video) and pagination, which would push toward a 5, but for a straightforward trending list tool the description covers the essentials.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides inline explanations for all three parameters: region_code (ISO code with examples), category_id (with example '28' for Science & Technology), and max_results (with max 50 limit). This adds value beyond the raw schema, which only shows titles and defaults. However, coverage of each parameter's meaning is somewhat thin, and the category example is single.
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?
Description clearly states the purpose: 'Get currently trending videos on YouTube.' This is a specific verb+resource combination that distinguishes it from siblings like youtube_search (search by query) and youtube_list_videos (list channel/user videos). It doesn't explicitly name an alternative, which would be needed for a 5, but the contrast with trending vs. search vs. list is reasonably clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (trending videos for a region/category) but doesn't explicitly state when to choose this over alternatives. It mentions the quota cost (1 unit) which is useful context. However, there are no explicit when-not-to-use conditions or named alternative tools, so it stops short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It doesn't disclose return format, authentication requirements, or whether this is a read-only operation. The description does usefully explain the exclusive nature of the three parameter forms (suggesting they're alternatives), which adds behavioral insight, but it omits notable details like required auth for the 'mine' case.
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 concise and well-structured, using a docstring-style format with an Args section that front-loads the purpose then enumerates parameters clearly. Each sentence earns its place, though some redundancy exists since the Args section partially repeats what the schema's parameter names already convey.
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 there are no annotations and no output schema, the description is reasonably complete for a simple lookup tool. It explains all three invocation modes and their parameter formats. However, an agent might want to know whether the return data includes subscriber counts, description, etc., and whether specifying multiple identifier forms simultaneously causes an error - neither is addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully explain parameters. It does so effectively: each parameter (channel_id, handle, mine) gets a concrete description with examples and its purpose. It clarifies that mine='True' maps to the authenticated user's channel, and gives realistic format examples (UCxxxxxxx, @mkbhd) that the schema itself lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves channel details and explicitly enumerates all three supported lookup methods: channel ID, handle (@username), and the authenticated user's channel. This is a specific verb+resource pairing that distinguishes it well from sibling tools like youtube_get_video or youtube_list_videos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by showing the three mutually exclusive lookup options (channel_id, handle, mine), which tells the agent how to invoke it. However, it doesn't explicitly explain when to choose one identifier form over another, nor does it contrast with alternatives like youtube_search when only partial channel info is known.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses a key behavioral trait: 'Costs 100 quota units per call — use sparingly.' This is real behavioral information beyond the schema. However, it doesn't describe the return format, pagination behavior, or error conditions, so there's some gap, but the quota disclosure is valuable and specific enough to merit a 4.
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 reasonably concise, front-loaded with the core purpose and cost warning before the parameter list. The cost warning is placed early which is appropriate. The parameter list is organized cleanly. No wasted sentences, though the cost note could arguably be its own preceding sentence. Efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a moderately complex tool (8 params) with no annotations and no output schema, so the description must do substantial work. It covers all 8 parameters with semantic detail, adds the cost constraint, and provides format examples. The main gap is not describing the return values (since there's no output schema), but for a search tool the return shape is fairly intuitive. The description is adequate-to-good for this complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully compensate. The description documents each parameter with its type and even provides example values for query format ('ISO 8601', 'ISO 3166-1 alpha-2'), which is helpful beyond the bare schema. The 'max 50' constraint on max_results adds valuable semantic detail not present in the schema. This exceeds what the schema provides and compensates well for the 0% 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 'Search YouTube for videos, channels, or playlists' with a specific verb+resource+scope. It distinguishes from siblings like youtube_trending and youtube_search_suggestions since the scope (search across three content types) is explicit. The cost note adds useful context, though the purpose itself is clear but doesn't explicitly name alternative sibling tools for differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context by listing all parameters and the cost warning ('use sparingly'), which implies a cost-conscious usage constraint. However, it doesn't explicitly state when to use this vs alternatives like youtube_list_videos, youtube_trending, or youtube_search_suggestions, nor does it provide exclusions or prerequisite conditions (e.g., whether auth is needed). Usage guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. 'Upload' implies a write/mutating operation, and file format/size constraints are given (JPEG, PNG, GIF, BMP; max 2MB). However, it doesn't disclose ownership/permission requirements (must own the video), whether the change is reversible, or what happens on failure. The format/size constraints are decent but the behavioral profile is incomplete for a mutating operation.
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?
Concise, front-loaded with the core action, and the Args section neatly documents parameters without excess. There's minimal waste. Could arguably drop the Args header format, but the structure is clean and efficient.
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?
For a 2-param tool with no output schema and no annotations, this description is adequate but leaves gaps. It explains both parameters and the file constraints, but doesn't cover whether the video must be owned by the authenticated channel, whether thumbnails are validated asynchronously, or what a successful upload returns. It's sufficient for invoking the tool correctly but not richly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates. It documents video_id as 'YouTube video ID' and file_path as 'Absolute path to the thumbnail image' with format and size constraints. This adds meaning beyond the bare property names in the schema, giving the agent concrete guidance on valid inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear specific verb+resource: 'Upload a custom thumbnail for a video.' The purpose is unambiguous and distinguishes from siblings like youtube_update_video (which updates video metadata) and youtube_upload_video (which uploads a video). It clearly scopes to the thumbnail-setting action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states what the tool does but provides no when-to-use guidance or exclusions vs alternatives. It doesn't mention that video must exist first, or when this should be used relative to youtube_upload_video. No explicit alternatives are named, though the purpose makes the use case fairly intuitive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosure. It describes what metrics are returned (views, watch time, subs, likes, shares) and the per-day granularity, which is useful. However, it doesn't mention date defaults behavior consequences, rate limits, authorization requirements (youtube_auth sibling exists), or whether data is delayed/eventually consistent. The 28-day-default and today-default behavior is disclosed, which is a plus.
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 tight and efficient: a one-sentence summary of purpose, a one-sentence value proposition, a one-sentence output format description, and explicit Args with dates and defaults. Every sentence earns its place with no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter, no-output-schema tool, the description covers purpose, output shape (metrics per day), and both parameters with defaults and format. The only gaps are around auth requirements and data freshness/delay, which matter given youtube_auth sibling exists as a prerequisite. It doesn't specify return format structure beyond column naming, but that's adequate for this complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate fully. It documents both parameters: start_date (YYYY-MM-DD, defaults to 28 days ago) and end_date (YYYY-MM-DD, defaults to today). This adds format and default-value semantics that the schema lacks entirely. It also adds the output columns returned, which gives the agent expectations of the result shape. This exceeds what the bare schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get daily performance metrics over time' with a specific verb+resource. It distinguishes itself from sibling analytics tools by specifying 'one row per day' with explicit metrics (views, watch time, subs, likes, shares), and positions itself for 'spotting trends and finding optimal posting days', separating it from top_videos, traffic_sources, demographics, and other daily-aggregate siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use it ('spotting trends and finding optimal posting days'), which implies temporal analysis use cases. However, it doesn't explicitly exclude alternatives like youtube_analytics_overview or youtube_analytics_day_of_week, nor state when NOT to use this tool. It names the output granularity (per-day rows) which helps differentiate from day_of_week aggregates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the transparency burden. It discloses the cost/quota distinction between the two API paths and the ownership restriction for the official API, which is valuable behavioral context. However, it doesn't disclose error behavior (e.g., what happens when captions are unavailable/disabled), return format, or failure modes—gaps given 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with an intro sentence, a clear default-vs-official distinction, and a compact Args list. Every sentence earns its place. It could arguably trim some redundancy, but the content density is appropriate for a 3-param tool with this much behavioral nuance around API selection.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a moderate-complexity tool with 3 parameters and no output schema or annotations, the description covers the main decision point (which API to use), all parameters, and key tradeoffs. It lacks error-case documentation (missing captions) and return-format details, but the essential decision-critical information—especially differentiating it from youtube_list_captions—is present and actionable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description fully compensates by documenting all three parameters: video_id, language (with format hint 'en', 'es', 'ja'), and use_official_api (with semantics about ownership and quota). Each parameter's purpose is explained beyond the plain schema definitions, which offers no descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb+resource: 'Get the transcript/captions for a video.' It distinguishes itself from siblings by clarifying it retrieves transcript data (vs youtube_list_captions which lists captions metadata, or youtube_get_video which gets video details). The 'for a video' scope is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly contrasts two usage modes: default youtube-transcript-api (any public video, no quota) vs official API (own videos, quota cost). It names the alternatives and provides the tradeoff context needed for an agent to choose correctly, plus notes the official API is restricted to own videos.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the quota cost (1,600 units), the private-by-default behavior, and the publish_at/privacy_status dependency. This adds meaningful behavioral context about cost and side effects that an agent needs to know before invoking. Could mention auth requirements but is otherwise strong.
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 tightly structured with an opening summary followed by a clear Args list. Every sentence earns its place - the quota cost and default privacy are high-value facts, and the parameter annotations are one line each with no fluff. Well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 7-parameter mutation tool with no annotations and no output schema, the description covers the essentials: defaults, constraints, and the scheduling dependency. It could add what the function returns (e.g., video ID) and auth requirements, but the core usage is well specified. Minor gaps only.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate entirely. It does: each parameter gets a clear one-line explanation, including value constraints (title max 100 chars, description max 5,000, default category ID meaning, valid privacy_status values, and the publish_at requires private constraint). This is exactly the semantic depth the schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb+resource: 'Upload a video to YouTube.' It distinguishes from siblings like youtube_update_video (update existing) and youtube_set_thumbnail (set visual), making the purpose unambiguous. The scope is fully defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains core behavior (private by default, 1,600 quota cost) and notes the publish_at scheduling constraint, but doesn't explicitly state when to use this vs alternatives or list prerequisites (e.g., needs youtube_auth first). No when-not-to-use guidance is given, though for an upload tool the context is moderately inferable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the burden of behavioral disclosure. The description discloses that this is a read-only listing operation (safe, no side effects), which the tool name implies but the description reinforces. It also enriches the output by listing the most common report types, giving the agent concrete awareness of what values it might retrieve. However, it doesn't explicitly state that no authentication is required or specify response format, but for a listing tool the key behavioral trait (non-destructive, read-only) is adequately conveyed.
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 compact and front-loaded: the purpose sentence comes first, followed by a tight bulleted list of the common report types. Every line earns its place; there is zero filler or redundancy. The format is easily scannable for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema listing tool, the description is highly complete. It explains what report types are available and gives concrete examples of the most common ones. It could additionally note that the returned list may differ from the examples, but the description is sufficiently complete for an agent to understand and invoke this tool correctly. The sibling pair with youtube_reporting_create_job makes the usage flow clear.
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, so all schema coverage is trivially 100%. With no parameters to document, the baseline is 4. The description compensates by explaining the enum-like values (channel_basic_a3, channel_demographics_a1, etc.) that the tool will return, adding semantic meaning beyond the empty schema. This directly helps the agent interpret returned report type values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List available report types that can be scheduled.' The verb 'list' plus the specific resource ('available report types') creates a clear purpose. It distinguishes itself from sibling tools like youtube_reporting_list_reports (which presumably lists scheduled jobs/reports) by focusing on report *types* that can be scheduled, not the reports themselves.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly communicates usage context: this is a discovery tool for seeing what report types are available for scheduling. It pairs naturally with youtube_reporting_create_job / youtube_reporting_list_jobs in the sibling set. However, it doesn't explicitly state when to use or NOT use this tool versus alternatives (e.g., when to use youtube_reporting_list_reports instead), though the distinct purpose is inferable.
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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