YouTube

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

Annotations declare idempotentHint=true and no destructive action. The description adds context about side effects: modifying server config for permanent access, browser login steps, and session-only scope. It doesn't describe the return output, but that's not critical given no output schema. No contradiction.

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

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

The description is two sentences, front-loaded with the purpose and then detailed usage. It is somewhat dense but every sentence provides necessary information, though it could be slightly tighter without losing clarity.

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

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

Despite no output schema and moderate complexity (two auth modes), the description covers the workflow well: browser login, token copy, config header, session token, and no-arg option. It doesn't specify return values but that's acceptable given tools often return links or success messages implicitly.

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

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

Schema coverage is 0%, but the description fully explains the only parameter (token): it's a JWT to paste for session-only login, and explains the alternative of no args for link generation. This adds significant meaning beyond the raw schema.

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

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

The description clearly states the tool's purpose: authenticate for MCP.AI IDE agents. It specifies the verb (authenticate) and resource (MCP.AI), and distinguishes from siblings like connect or marketplace by focusing specifically on token-based auth flow.

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

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

Provides explicit when-to-use guidance: for login, with two distinct options (permanent config header vs. session token) and even explains when to call with no args to get a link. It also implicitly contrasts with other auth methods (sibling tools) by focusing on this server's auth.

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

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable behavioral detail about conditional return values (authenticated:true with empty pending[], or connect_url when missing). It does not contradict annotations and enriches understanding of the tool's output in different states.

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

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

The description is exactly two sentences, front-loaded with the primary action, and every word adds value. It describes the return format and conditional cases without any fluff or repetition.

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

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

Given the low complexity (no parameters, no output schema), the description adequately covers the key scenarios: full connectivity and missing credentials. It does not detail partial connectivity or the exact structure of URLs, but the annotations and simplicity of the tool make this sufficient. Overall, it is complete enough for reliable selection and invocation.

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

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

The tool has zero parameters, and the schema coverage is trivially 100% with no properties. Per rubric, the baseline for 0 params is 4. The description does not need to explain parameters, and no additional parameter information is expected.

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

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

The description clearly states the tool's purpose: returning connection status and URLs. It specifies the verb 'Returns' and the resource 'connection status', and it distinguishes itself from related tools like authenticate by focusing on status rather than performing authentication. The conditional behavior (authenticated:true vs connect_url) adds precision.

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

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

The description implies usage for checking connection status and provides context about when credentials are missing vs all connected. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. Guidance is implied but not actionable.

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

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

It adds rich side-effect context beyond the annotations: writes require example `workspace/owner-admin`, invoke can run a one-off without installing, paying/credential failure returns links the user must open before retrying, and it distinguishes installed_in_toolkit vs exactly installed_in_workspace. These details do not contradict the provided annotations.

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

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

The description is a dense, mostly first-loaded wall of text, but it earns its length by covering 14 separate actions and the distinction between MCP execution, installation, prompt library, and read-only workflows. It would benefit from a short breakdown or bullets, but there is virtually no phrase spreading.

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

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

The description covers the main search→describe→invoke path, the permission boundary, edge cases for auth and payment, per-installation semantics, prompt search/get/publish, and the intent of `reside` actions. However, no output shapes are specified for the common actions and `resime` (a distinct enum action) is never described, so the overall contract isn't quite complete.

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

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

The main action parameters are connected to the prose (query/search, mcp_id/describe, tool_id/arguments for invoke, prompt_slug/prompt_* for the prompt library)which helps compensate for the 0% schema coverage. Still, with a 23-parameter contract, many parameters such as `limit`, `conversation`, `immediate`, `tier_slug`, `cancel_ressureason`, `report_context`, and `prompt_targets` are not explicitly explained, so intent mapping is incomplete.

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

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

The description identifies marketplace as MCP's official catalog and the way to run MCPs, capturing its resource and purpose: 'the official mcp.ai marketplace — the in-title catalog of every MCP/tool, AND the way to run them'. It explicitly states the core search→describe→invoke flow, which clearly separates it from the youtube_* sibling tools.

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

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

The description gives concrete when-to-use guidance: 'Use mount only to make theMCP PERMANENT... prefer invokeMCP for a single/occasional use' and differentiates prompt-library actions from MCP actions. It also explains when to retry after a benefit/credential link is returned, which is a strong operational signal.

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

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

Annotations already indicate the tool is a write operation (readOnlyHint false), idempotent, and non-destructive. The description adds the behavioral detail that the conversation array should be included 'for reproduction,' which is useful context beyond annotations. It does not disclose submission behavior, data retention, or response semantics, but it also does not contradict annotations.

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

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

The description is two sentences with no filler. It front-loads the primary purpose and gives one actionable instructional tip. Every sentence earns its place.

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

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

With no output schema, no param descriptions in the schema, and a required message parameter that is never explained, the description leaves a notable gap. The mention of the conversation array is good context, but the tool's required input format and expected behavior are undeveloped, making the description only partially complete for a simple submission tool.

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

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

Schema description coverage is 0%, so the description must carry the semantic burden. It adds meaning for conversation by mentioning recent messages for reproduction, but it does not explain the required message parameter or the context parameter. It also calls conversation an 'array' while the schema type is string, which introduces potential confusion.

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

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

The description uses specific verb 'Report' with explicit resources: bug, missing feature, and feedback. It clearly distinguishes this tool from all the YouTube-focused siblings and any other support or contact tool.

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

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

The description implies when to use the tool (when reporting a bug, missing feature, or feedback) but does not explicitly state when not to use it or mention alternatives. It gives some instruction ('Include the conversation array...') but no clear exclusion or comparison to sibling tools.

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

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

The annotations already indicate read-only, non-destructive, and idempotent behavior. The description does not add further behavioral context beyond the word 'Show', which aligns with the annotations but does not introduce new details about side effects, auth requirements, or rate limits.

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

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

The description is a single, clear sentence without unnecessary words or filler. It is efficiently structured and directly conveys the tool's purpose.

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

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

Given that there is no output schema, the description states what the tool shows (MCP platform and adapter versions), which provides a good expectation of the result. However, it does not specify the format or structure of the returned data, which could be more explicit for full completeness.

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

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

The tool has zero parameters, and the schema fully covers them (i.e., there are none to document). The description does not need to add parameter information, and it does not omit or misrepresent anything.

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

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

The description clearly states the tool's purpose: to show the current MCP platform and adapter versions. It is specific about what information is displayed and leaves no ambiguity about the tool's function.

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

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

The description does not provide any guidance on when to use this tool versus alternatives. It simply states what the tool does without mentioning scenarios, prerequisites, or when it would be preferred over other tools.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds value by specifying the return content scope (installed MCPs, connection status, accounts, catalog counts), but does not disclose whether connection status is live or cached, or what status values look like. With annotations covering safety, this is 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.

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

A single 24-word sentence that front-loads the action ('Returns the current toolkit state') and then enumerates the four data categories. Every clause earns its place; there is zero waste and no repetition of structured annotation data already present.

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

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

For a simple zero-parameter, read-only introspection tool, the description is complete. Annotations fully handle the behavioral safety profile, and the description serves as the de facto return-value documentation by listing the four concrete data categories. Given no output schema exists, this level of enumeration is adequate for the tool's low complexity.

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

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

The tool has zero parameters, and the rule gives a baseline of 4 for 0-param tools. The empty schema requires no explanation, and the description correctly focuses entirely on the output rather than inputs. No parameter documentation burden exists, so the baseline holds.

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

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

The description uses a specific verb ('Returns') with a clear resource ('current toolkit state') and enumerates the exact data returned: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a distinct introspection tool clearly differentiated from siblings like show_version (version info only) and the youtube_* content tools.

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

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

Usage context is implied: a zero-parameter tool named 'toolkit_info' whose description says it returns toolkit state is self-evidently a diagnostic/status check. However, the description provides no explicit when-to-use guidance or exclusions naming alternatives (e.g., 'use show_version for version-only checks'), so the guidance dimension gets no explicit credit.

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

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

The annotations claim readOnlyHint=true and idempotentHint=true, but the description instructs passing a JSON body for POST and the schema allows DELETE/PUT/PATCH. Calling arbitrary backend routes with mutating methods can have side effects, so the read-only hint is misleading. The description does not warn about authentication, scoping, or response behavior beyond the bare call mechanics.

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

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

Two sentences, front-loaded with the 'escape hatch' purpose and containing no filler. Every clause carries operational information.

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

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

The definition covers the core invocation data clearly, and for an arbitrary-route escape hatch a fixed response format cannot be documented. It lacks any mention of error handling or authentication expectations, but given the generic scope and sibling guidance, it is adequately complete.

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

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

Schema description coverage is 0%, so the description is the only source of parameter semantics. It explains path with an example, the method default, the query map, and the body-for-POST usage. That is enough for an agent to construct a call, though body and query structures remain loosely typed.

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

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

The description names the generic backend-call purpose, shows an example path, and explicitly contrasts with the named youtube_* sibling tools. An agent can distinguish this escape hatch from the specialized tools immediately.

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

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

It says to prefer the named youtube_* tools when available and reserve this tool for routes not in the manifest. This is explicit selection guidance with a clear exclusion criterion.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds a useful behavioral detail about batch execution and hints at the returned content, but it does not disclose potential edge cases like response format, invalid identifiers, or interaction between id, ids, and forUsername.

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

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

The description is exceptionally concise: two short sentences front-loading the key outputs and bulk capability. No repeating of the tool name or schema, and every word serves a clear purpose.

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

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

As a simple metadata-fetch tool with no output schema, this description partially covers the return fields (description, links, country, subscriber count, banner) and batch support. However, it leaves significant gaps around parameter semantics and result behavior, so it is adequate but not fully complete for a tool with zero schema descriptions and no output schema.

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

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

Schema description coverage is 0%, so the description must clarify parameter usage. It only hints that 'ids' are for batched execution, but it does not explain the distinction between id and forUsername, the expected format, or how multiple parameters compose. This leaves significant semantic ambiguity for an agent.

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

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

The description lists the specific data returned (description, links, country, subscriber count, banner), clearly indicating a retrieval operation for a channel's 'about' info. It distinguishes the tool from siblings by naming these about-specific fields, even though it lacks an explicit verb like 'get' or 'retrieve'.

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

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

The 'Bulk support: accepts ids for batched execution' line provides a clear usage hint for when to use batch mode, but there is no explicit guidance on when to use this tool instead of alternatives like youtube_channel_home or youtube_channel_videos. Context implies it is the canonical 'about' endpoint, but the description does not state exclusions or preferred use cases.

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

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

Annotations already declare read-only and idempotent behavior. The description adds batched execution via ids, which provides useful context. No contradiction exists, but it does not go beyond this single behavioral note.

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

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

Two short, direct sentences with no filler. The bulk support note is separate and clear, and every word contributes.

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

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

While the tool is simple and read-only, the description fails to explain the purpose of most parameters or provide usage examples. Given the lack of an output schema and 0% schema coverage, the description is too sparse for reliable agent invocation.

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

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

With 0% schema coverage, the description was expected to compensate, but it only indirectly mentions the 'ids' parameter for batching. The 'id', 'token', and 'forUsername' parameters remain undefined, leaving substantial gaps for an agent.

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

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

Describes the tool as the community posts tab for a channel, clearly identifying the resource and differentiating it from sibling tab tools. The noun-phrase style slightly reduces specificity, but the meaning is unambiguous.

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

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

No explicit guidance on when to use this tool versus alternatives. The bulk support note hints at batching but does not explain when to use batched vs single id or how it compares to sibling tools.

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

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond those annotations: the deprecation status, the likely empty/error response, and bulk execution support. No contradiction exists between the description and annotations.

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

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

Two short, focused sentences deliver the core purpose, deprecation caveat, and bulk support without filler. The warning is front-loaded and every sentence contributes useful information.

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

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

The description handles the deprecation and bulk behavior well, which is the most important context for this tool. However, with four parameters, no output schema, and zero schema-description coverage, the missing parameter semantics leave the tool only partially documented for an agent.

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

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

Schema description coverage is 0%, so the description must compensate for four parameters. It only explains the 'ids' parameter via the bulk-support statement, leaving 'id,' 'token,' and 'forUsername' semantically undocumented.

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

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

The description states 'Featured channels listed on a channel,' which clearly identifies the resource and the action. It also distinguishes itself from sibling channel-related tools by focusing on the featured-channels concept, though it could be more explicit with a verb like 'get' or 'fetch.'

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

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

The description provides strong context by noting that YouTube deprecated the featured-channels tab and that this route typically returns an empty/error envelope. This effectively warns the agent against expecting useful results, though it does not name a specific alternative tool.

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

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

Annotations already indicate read-only and idempotent behavior. The description adds no further behavioral details such as permissions, rate limits, or side effects. It only hints at response content ('featured shelves + meta'), which is more about output than behavior, and does not go beyond what annotations already cover.

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

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

The description is extremely concise, with two short sentences and no unnecessary words. It is well-structured and gets straight to the point, providing a clear overview without verbosity.

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

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

The description is sparse: it does not explain the purpose of the parameters (id vs. ids, token, forUsername) or the full contents of the payload beyond 'featured shelves + meta'. Without an output schema, this leaves significant gaps in understanding what to expect and how to use the tool effectively.

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

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

Schema coverage is 0% as parameters have no descriptions. The description explains that 'ids' enables batch execution, but leaves id, token, and forUsername unexplained. It compensates only partially for the lack of parameter metadata, so the meaning of most parameters remains ambiguous.

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

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

The description clearly states the tool retrieves the channel home page payload with featured shelves and metadata. This is specific and distinct from sibling tools like youtube_channel_about, youtube_channel_featured, or youtube_channel_videos, which target different sections of a channel.

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

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

The description provides no explicit guidance on when to use this tool versus alternatives. It only mentions 'Channel home page payload' without differentiating from the many sibling tools (e.g., featured, about, community). Bulk support is mentioned but does not clarify selection criteria.

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

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

Annotations already cover read-only, idempotent, and non-restructive; the description adds a small amount of behavioral context by clarifying this specifically exposes the playlist tab and accepts batched ids. It does not add the output or pagination behavior, but the annotation lower the bar.

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

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

The description is short and the bulk support note is visible, but the first sentence mostly restates the tool name and the entire description is too light to be sufficient. It is concise, but not necessarily effective.

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

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

With five optional parameters, no output schema, and no param documentation, this description leaves core aspects of invocation unknown: what is returned, how token and sort_by work, and whether one of id or ids must always be supplied. It is not complete enough for reliable use.

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

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

Schema description coverage is 0%, so the description needs to compensate, but it only explains that 'ids' supports batched execution. Fields such as token, sort_by, formUsername, and the singular id are left undefined.

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

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

The description identifies the resource ('Channel playlists tab') but does not say what action the tool performs (e.g.fetches/lists/returns). It is distinguishable from sibling tab tools, but the purpose is expressed as a destination rather than an operation.

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

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

No guidance is provided on when to use this tool versus youtube_playlist, youtube_channel_videos, or other channel tab tools. The only actionable note is bulk execution support, which is not a selection guideline.

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

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

Annotations clearly indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows it is a safe, non-destructive read operation. The description adds that it supports bulk execution ('accepts ids for batched execution') and scopes to channel-specific content, which is useful beyond the annotations. No contradiction with annotations.

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

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

The description is very brief, consisting of two sentences that are front-loaded with the main purpose. Every sentence adds value: the first explains the tool's function, the second highlights bulk support. It is efficient and avoids fluff, though it could benefit from slightly more detail on parameter semantics without becoming verbose.

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

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

Given the lack of an output schema and the presence of 5 parameters with no schema descriptions, the description is insufficient. It does not explain return format, pagination (via token?), or how the search differs from listing. The two-line description is too sparse for an agent to use the tool correctly in diverse scenarios, especially with zero schema coverage.

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

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

With 0% schema description coverage, the plain parameter names (id, ids, query, token, forUsername) leave much unsaid. The description mentions 'ids' for bulk support, adding meaning to that parameter. However, it does not clarify what 'id' refers to (channel ID, video ID?), the role of 'forUsername', or the format of 'token'. The description falls short of compensating for the low coverage.

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

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

The description states the tool searches a channel's own videos and playlists, which specifies a clear verb and resource. However, it does not explicitly distinguish it from sibling tools like youtube_channel_videos or youtube_channel_playlists, which might be used to list content without search. The purpose has some ambiguity regarding the exact scope of 'search'.

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

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

The description mentions bulk support for batched execution, providing some context. However, it does not indicate when to use this tool versus alternatives like youtube_search (general search) or youtube_channel_videos (to list all videos). No exclusions or alternative recommendations are given, leaving the agent to infer usage.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds bulk execution behavior, but provides no other behavioral context such as return format or authorization needs.

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

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

The description is very short with no redundant text, but it is more of a fragment than a structured tool description. It front-loads a noun phrase rather than a clear action statement.

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

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

The tool has four parameters and no output schema, yet the description explains neither the return behavior nor the roles of token and forUsername. The bulk support note is helpful but leaves major gaps for an agent.

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

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

With 0% schema description coverage, the description must compensate for undocumented parameters. It only clarifies 'ids' for batched execution, leaving id, token, and forUsername unexplained.

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

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

The description 'Channel shorts tab' identifies a resource but lacks a clear action verb, making it unclear whether the tool lists, retrieves, or performs another operation on shorts. The tool name and sibling context suggest retrieval, but the description itself is vague.

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

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

No guidance is given on when to use this tool versus alternatives like youtube_channel_videos or youtube_channel_shorts_post. The 'Bulk support' note is a parameter usage hint, not tool-selection guidance.

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

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

Despite annotations indicating readOnlyHint=true and idempotentHint=true, the description accurately notes that it requires a continuation token and mentions bulk support. The description does not contradict annotations; in fact, it aligns with the read-only nature since it's likely a continuation of a GET request. It adds value by specifying the token requirement and bulk support, which are not in annotations.

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

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

The description is very concise, with two sentences that convey key points without fluff. It front-loads the most critical information (POST variant and token requirement). The mention of skipping in daily smoke is an extra but valuable note.

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

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

Given the tool's complexity (5 params, no output schema), the description provides some essential context (token requirement, bulk support) but lacks details on parameter semantics and return behavior. It is adequate for a simple continuation tool but not fully complete for an agent to use without additional inference.

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

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

The description only mentions `params` and `ids`, but the schema includes 5 parameters with zero coverage. It doesn't explain the roles of `id`, `token`, or `forUsername`. The description adds some meaning for `ids` (batched execution) but fails to cover the other parameters, leaving the agent with limited understanding.

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

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

The description clearly identifies this as the POST variant of channel shorts, which distinguishes it from the GET variant (youtube_channel_shorts). The verb 'post' and resource 'channel shorts' are specific, but it doesn't fully explain what posting entails (e.g., creating a new short?).

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

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

The description states a critical precondition: requires a `params` continuation token from a prior GET response. It also provides an explicit exclusion for daily smoke tests ('Skip in daily smoke'), which is practical guidance. However, it doesn't explicitly mention when to use POST vs GET or alternatives beyond the continuation token context.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful bulk-execution behavior, but it does not explain response format, authentication expectations, or how id vs ids vs forUsername affect behavior.

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

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

The description is short and front-loaded with the resource identity, and the bulk-support sentence earns its place. It could be improved by using an action-oriented opening phrase, but it contains no wasted text.

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

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

For a simple read-only tool with strong annotations, the description is minimally viable, but with no output schema and 0% parameter coverage it leaves gaps around selector semantics and invocation behavior. It is adequate but not complete enough for confident agent selection and correct parameter use.

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

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

Schema description coverage is 0%, so the description must compensate for the bare string parameters. It clarifies only 'ids' as a batched list; 'id' and 'forUsername' get no semantic explanation, leaving the agent unsure how to choose among the three optional selectors.

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

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

The description identifies the resource ('store / merch shelf') and scope ('for a channel'), which distinguishes it from sibling channel-section tools like youtube_channel_about or youtube_channel_home. However, it lacks an explicit verb such as 'get' or 'fetch', so it reads as a noun phrase rather than a clear action.

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

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

The bulk-support sentence provides one concrete usage hint: use multiple ids for batched execution. The 'for a channel' scope implies when the tool is relevant, but there is no explicit guidance on when not to use it or which sibling tool to prefer.

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

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

Annotations already declare this as read-only, idempotent, and non-destructive, so the description's burden is lower. It adds a useful behavioral note about batched execution via ids, but it does not disclose behavior around token pagination, sorting, or username-based lookup.

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

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

The description is extremely compact, with two short sentences and no filler. It is front-loaded with the core idea, though the brevity borders on under-specification rather than true informative conciseness.

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

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

Given five undocumented parameters, no output schema, and a rich sibling set, the description is incomplete. An agent would not know how to construct a correct invocation, what token means, what sort_by values are valid, or how forUsername relates to id.

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

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

Schema description coverage is 0%, so the description must compensate for explaining parameters. It only clarifies that ids supports batched execution, leaving token, sort_by, and forUsername undefined and with no guidance on how they interact.

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

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

The description identifies the target as the channel videos tab, which loosely suggests listing/reading a channel's videos and distinguishes it from sibling tabs. However, it lacks an explicit verb such as 'list' or 'fetch', so the exact action is implied rather than stated.

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

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

The only usage guidance is 'Bulk support: accepts ids for batched execution', which hints at when to use the ids parameter. There is no guidance about when to choose this tool over youtube_channel_home, youtube_channel_playlists, youtube_channel_search, or youtube_video_related.

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

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds genuinely useful behavioral context: needing a prior GET token, the limitation of the GET surface, smoke-test exclusion, and batched execution. No contradiction with annotations.

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

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

Two tight paragraphs with front-loaded purpose. Every sentence adds distinct value—usage guidance, token requirement, smoke exclusion, and bulk support—with no redundancy or fluff.

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

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

Given no output schema, minimal schema descriptions, and moderate parameter complexity, the description covers the core usage scenario well and provides operational guardrails. The only gap is the undefined parameters beyond `params` and `ids`, which prevents a 5.

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

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

Schema description coverage is 0%, so the description must compensate. It explains `params` (continuation token) and `ids` (bulk execution), but leaves `id`, `token`, and `forUsername` unexplained. Partial compensation for a five-parameter schema.

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

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

Description opens with 'POST variant of channel videos', clearly identifying the resource and operation. It further distinguishes from the sibling GET tool by noting it fetches deeper pages or filtered shelves the GET surface can't address.

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

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

Explicitly states when to use: requires a `params` continuation token from a prior GET response to fetch deeper pages/filtered shelves. Also gives a when-not-to-use: 'Skip in daily smoke (no synthetic params).' Mentions bulk support via ids as an additional usage mode.

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

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

Annotation Contradiction: the description explicitly says 'Apaga DEFINITIVAMENTE' and '(não tem desfazer)', which is destructive behavior, but annotations declare destructiveHint=false. This is a serious mismatch that could mislead an agent into treating the tool as a safe, reversible operation. The description otherwise provides excellent behavioral detail, but the contradiction with annotations forces a score of 1 per the rubric.

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

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

The description is compact, front-loaded with the most critical warning ('Apaga DEFINITIVAMENTE'), and uses separated clauses to cover scope, alternative, quota cost, and bulk support. Every sentence adds distinct information with no fluff.

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

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

The description covers the core behavior, limitation, alternative, cost, and batch support. Given the tool's simple input schema (no nested objects) and no output schema, what is provided is nearly sufficient. However, the annotation contradiction and the unexplained `account` parameter leave small but meaningful gaps in the total context an agent has.

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

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

Schema description coverage is 0%, so the description must compensate for parameter meaning. It explicitly explains `comment_ids` for batched execution and implicitly covers `comment_id` as the singular deletion target, but it does not explain the `account` parameter at all. Some credit is given for the bulk-field clarification, but the description is incomplete for all parameters.

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

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

The description uses a precise verb ('Apaga DEFINITIVAMENTE'), names the exact resource (a comment), and adds scope conditions (own channel or connected channel video). It clearly differentiates from youtube_comment_moderate, so an agent can distinguish the intent without ambiguity.

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

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

The description explicitly states when to use this tool (permanent deletion) and when to use the alternative (youtube_comment_moderate with `rejected` for hiding). It also specifies domain constraints and quota cost, giving the agent clear routing and prerequisites.

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

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

There are no annotations, so the description carries the full burden. It discloses the side effects of each status, the special ban_author constraint, the scope limitation to the connected channel, and the operational cost of 50 units per comment. This gives the agent important expectations before invoking the tool.

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

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

The description is short, dense, and every sentence adds value: possible states, parameter restriction, scope boundary, and cost. There is no redundant wording or filler.

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

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

For a moderation action with no annotations and no output schema, the description covers the most important behavioral and operational constraints. It could additionally clarify pagination/return behavior or accepted input size for `comment_ids`, but the core information an agent needs is present.

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

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

The description enriches `status` and `ban_author` by explaining their practical meaning and constraint, which goes beyond the raw schema. However, it does not explain `comment_ids` or `account`, so the agent still has to infer their purpose from names alone. This is adequate but not complete.

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

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

The description states a specific action ('Modera comentários') and defines the three possible target states (`published`, `heldForReview`, `rejected`). This makes the tool clearly distinguishable from related tools like youtube_comment_delete, youtube_comment_post, or youtube_comment_update.

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

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

The description gives clear context: it applies only to comments on the connected channel's own videos, which is a meaningful condition. It does not explicitly mention alternative tools by name, but the usage boundary is clear enough for an agent to decide when this tool is appropriate.

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

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

Annotations already mark readOnlyHint as false and destructiveHint as false, so the mutation intent is expected. The description adds useful behavior: it costs 50 quota units, posts as the connected channel, and is explicitly top-level. This is valuable operational context beyond the annotations, although it does not describe failure modes or raw edge behavior.

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

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

The description is compact and well-structured: core purpose, usefulness of a sibling, quota cost, and bulk behavior. Each sentence adds new information without redundancy, and the most important information appears first.

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

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

For a write-oriented tool with 4 parameters, 0% schema coverage, and no output schema, the description gives enough to use the simplest case but not enough to confidently use optional parameters or batch mode correctly. The account role and the relationship between video_id and video_ids are important gaps.

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

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

Schema description coverage is 0%, so the description should compensate by explaining the parameters. It only adds meaning to video_ids via 'Bulk support', but does not explain what video_id represents more fully, how video_id and video_ids interact, what text means beyond a comment, or how account is resolved.

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

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

The description uses a specific verb ('Publica') and a specific resource ('comentário NOVO de topo em um vídeo'), so an agent can clearly understand the core action. It also immediately distinguishes itself from youtube_comment_reply, which is the closely related sibling tool.

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

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

It explicitly states when to use this tool: for a new top-level comment on a video. It also states the alternative: for replying to a person, use youtube_comment_reply. Additionally, it mentions batch mode via video_ids, guiding usage beyond the defaults.

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

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

Annotations only mark the tool as not read-only, not idempotent, and not destructive, so the description carries the behavioral burden. It usefully discloses that individual item failures do not fail the entire batch, that `parent_id` must point to a top-level comment, and that each reply costs 50 YouTube API quota units. No contradiction with annotations was found.

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

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

The description is compact and efficient: purpose, batching behavior, the `parent_id` constraint, and quota impact are all covered in a few sentences. There is no redundant or filler content.

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

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

For a mutation tool with no output schema and minimal annotations, the description provides strong practical context: it explains batch failure isolation, top-level-only replies, and the quota implication of each reply. It could be more explicit about the exact item shape and response/error behavior, but the core invocation requirements are covered.

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

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

Schema description coverage is 0%, so the description needs to compensate. It does add value by explaining `replies` batching and the special meaning of `parent_id`, but it does not clearly explain the `text` field or the `account` parameter, leaving some ambiguity for callers.

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

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

The description clearly states the tool's action: 'Responde comentários como o canal conectado' (respond to comments as the connected channel). It also adds important scoping details like replying to top-level comments, but it does not explicitly contrast itself with sibling tools like youtube_comment_post or youtube_comment_update.

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

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

It gives concrete usage context: supports multiple replies in one call, `parent_id` must be a top-level thread id from youtube_comment_threads, and quota costs should discourage over-use. It does not explicitly state when NOT to use this tool versus its siblings, but the guidance is clear enough for likely use cases.

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

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

Annotations already declare read-only, non-destructive, and idempotent behavior. The description adds no conflicting information and implicitly confirms a read operation, so transparency is well-served.

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

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

The description is concise, using two short sentences with no redundant or verbose content. It is well-structured and easy to parse.

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

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

While the tool's core purpose is clear, the description omits usage guidance and parameter details, relying on annotations for some behavioral context. It is adequate for a simple read operation but not fully complete.

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

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

The schema provides no parameter descriptions, and the description only hints at the 'ids' parameter for batch execution. No information is given about 'token' or 'sort_by', leaving their semantics unclear.

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

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

The description clearly states that the tool retrieves the top-level comments thread for a video, which is specific and distinguishes it from other sibling tools like playlist or channel operations.

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

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

The description mentions bulk support using multiple ids, but does not provide guidance on when to use this tool versus alternatives, such as when to prefer comments over other video-related tools or when to use the token or sort_by parameters.

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

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

Annotations already establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful context beyond that: the tool costs 1 quota unit, returns threads with existing replies, and behaves differently when video_id is omitted. These are useful behavioral insights not present in the annotations.

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

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

The description is extremely dense and efficient: four sentences carry the primary purpose, sibling differentiation, no-video_id behavior, a quota cost, and bulk support. It is front-loaded with the most important operational details and contains no filler.

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

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

Despite clear core-purpose coverage, a tool with 10 optional parameters and no output schema carries more contextual burden. The description omits pagination, filtering parameters, default ordering, and return shape details, leaving agents to guess for less common calls. It is a viable basic definition but not fully complete.

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

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

The input schema has 10 parameters but 0% description coverage. The description explains only video_id semantically and mentions video_ids/channel_ids as bulk options; order, account, page_token, max_results, search_terms, moderation_status, and channel_id remain unexplained. The description does not sufficiently compensate for the schema's lack of descriptions.

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

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

The description states a specific function: fetching top-level YouTube comment threads (with existing replies), and explicitly distinguishes it from youtube_comments by calling it the source of parent_id for youtube_comment_reply. It describes a concrete resource and scope.

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

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

The description explicitly says to prefer this tool over youtube_comments when the intent is to reply, and explains the no-video_id case for scanning an entire channel ('what I haven't replied yet'). This is clear when-to-use and alternative-selection guidance.

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

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

Beyond the valid annotations, it discloses the 50-unit quota cost, the ownership restriction, and the batch behavior via `comment_ids`. It also explains the benefit of editing over re-interactive: adding likes, but not fully. It does not explain auth details or error behavior, but the added behavioral context is valuable.

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

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

Two short sentences plus a batch note. Every sentence carries important information: purpose, scope, cost, and bulk behavior. No filler.

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

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

Given the small mutation, the description covers purpose, validation constraint, cost, and batch. It leaves out return/error semantics and the precise parameter relationship, but it is largely enough for an agent to know what the tool does and when to invoke it.

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

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

Schema description coverage is 0%, so the description must compensate. Only `comment_ids` survivor: batch. The `text`, `comment_id`, and `account` parameters are left to be inferred from their names, and the relationship between `comment_id` and `comment_ids` is not explained.

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

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

The description states a specific verb-resurgy action: edit the text of a published comment or reply belonging to the connected channel. It clearly positions itself as a correction tool and distinguishes it from delete, post, reply, and moderation siblings.

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

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

It gives real usage conditions: it is only for comments published by the connected channel and is meant for fixing errors without deleting and reposting. It does not explicitly name an alternative tool, but the conditions and exclusions are clear.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, so the agent knows this is safe. The description adds value by noting this retrieves metadata (not video bytes), mentions specific return fields, and discloses bulk/idempotent execution behavior. The description is consistent with annotations.

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

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

Extremely concise: two sentences, each providing essential information. First sentence explains the core function, second explains bulk execution behavior. No wasted words.

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

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

For a read-only metadata retrieval tool with no output schema, the description covers the key aspects: what it returns, the operational nuance (downloads metadata, not content), and bulk support. Minor gaps exist: no explanation of 'cgeo' parameter semantics or format of the id/ids relationship.

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

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

Schema description coverage is 0%, meaning none of the three parameters have schema-level descriptions. The description only references 'ids' for bulk support, leaving 'id' and 'cgeo' unexplained. However, 'id' is inferable from the tool name and 'bulk support' context. The description partially compensates but doesn't fully close the gap.

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

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

The description says 'Stream/download metadata for a video' which gives a clear verb+resource action and includes the types of data returned. However, the tool name 'youtube_download' is a bit misleading since the description states it's actually metadata/stream info and not actual content download, and this distinction from sibling tools like 'youtube_api' could be clearer.

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

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

The description implies the tool returns metadata (formats, URLs, status) rather than downloading actual video content, which is critical guidance. However, there is no explicit distinction between this and similar sibling tools, nor when to choose alternatives. The line 'Bulk support: accepts ids for batched execution' gives some usage context 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.

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds only the note about the hashtag format, which is not a behavioral trait. It does not disclose return format, pagination, or any other runtime behavior beyond what annotations already imply.

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

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

The description is a single, concise sentence, well front-loaded with the core purpose. However, it is concise because it is under-specified, not because it's efficiently detailed. The sentence earns its place but leaves out essential information needed for correct usage.

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

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

With no output schema, 3 parameters (0% schema description coverage), and a description that only covers the tag format, the tool is severely underdetermined. It fails to explain what the tool returns, what values 'type' can take, or how 'token' is used. This falls far short of what an agent needs to invoke the tool correctly.

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

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

Schema description coverage is 0%, so the description must compensate. It clarifies that 'tag' should be provided without leading '#', which is useful, but it says nothing about the 'type' or 'token' parameters. This leaves the agent guessing on how to use those parameters, even though they are optional.

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

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

The description 'Posts under a hashtag (without leading #)' gives a resource (hashtag) but the verb is ambiguous—'Posts' could mean retrieving posts or creating them. It is not as explicit as 'Retrieve posts' or 'List posts under a hashtag'. It does hint at the purpose but lacks clarity and doesn't distinguish from sibling search tools.

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

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

There is no guidance on when to use this tool versus alternatives like youtube_search or youtube_channel_shorts. The only usage hint is the 'without leading #' note, which is about parameter formatting, not about the tool's context or exclusions. No alternatives or preconditions are mentioned.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety. The description adds context about anonymity and geo/lang awareness, but does not disclose return format, pagination, or any additional behavioral traits.

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

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

Single sentence with no fluff, front-loaded with the core purpose. Every word adds value, making it highly concise and well-structured.

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

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

With 3 optional parameters and no schema details, the description fails to explain the token parameter or describe the output shape. It is minimally complete for a simple read-only tool but leaves significant gaps for an agent to infer usage.

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

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

Schema has 3 parameters (geo, lang, token) with 0% coverage. The description implies geo/lang usage but does not explain their format or any meaning, and the token parameter is completely undocumented, leaving it ambiguous for the agent.

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

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

The description clearly states what the tool does: returns the YouTube home feed with anonymous access and geo/lang awareness. It distinguishes itself from siblings like youtube_trending or youtube_channel_home, though it doesn't explicitly name alternatives.

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

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

No guidance on when to use this tool vs alternatives. It does not mention exclusions, prerequisites, or specific scenarios where this tool is preferred over others like youtube_search or youtube_trending.

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

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

Annotations declare readOnlyHint and idempotentHint, which already indicate a safe read operation. The description adds minimal behavioral context beyond labeling it a 'feed'—no mention of pagination, rate limits, or what happens with the token parameter.

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

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

The description is a single short sentence, which is concise, but it is under-specified. It reads more like a title than a description, failing to provide enough substance to be genuinely useful.

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

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

With no output schema and minimal description, the tool is severely incomplete. It does not explain what data is returned, how to paginate (token is likely used for that), or what geo/lang filters do. The agent would have to guess or test extensively.

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

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

Schema has 0% description coverage for three parameters (geo, lang, token). The description does not explain any of them, leaving the agent to guess what these parameters control. This is a critical gap for a tool with no parameter documentation.

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

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

The description states it's a feed of viral/hyped videos, which identifies the resource but is vague about exact scope. It doesn't differentiate from youtube_trending or youtube_home_feed, making it unclear when this tool should be preferred.

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

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

No guidance on when to use this tool versus the numerous sibling tools. There is no mention of alternatives or contextual triggers, leaving the agent without direction.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond the annotations: the quota cost ('Custa 1 unidade da cota') and the semantic restriction that only comment-capable channels are listed. No contradiction with annotations.

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

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

The description is short and each sentence earns its place: it states the object, the output shape, the usage timing, and the quota cost. The most decision-relevant information is front-loaded, and there is no filler or repetition of schema data.

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

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

For a read-only list tool with a single optional parameter and no output schema, the description covers what is listed, when to use it, and cost. The only notable gap is the unexplained 'account' parameter, which prevents the description from being fully complete for a caller who wants to be selective about which account's channels to list.

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

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

There is exactly one parameter, 'account', and the schema describes its properties but has 0% schema description coverage. The description never mentions 'account', so the agent cannot tell what the parameter means, whether it is genuinely optional despite the schema, or how it affects which channels can be returned. With low coverage, the description is responsible for compensating, but it does not.

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

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

The description uses a specific verb and resource: 'Lista os canais do YouTube conectados', and adds the distinctive scope 'os que podem responder e moderar comentários'. It enumerates the included fields (id, nome e estatísticas), which makes the tool easy to tell apart from broader channel, search and feed tools among the siblings.

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

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

The description gives an explicit instruction on when to call the tool: 'Use antes de responder para confirmar de qual canal a resposta vai sair'. It does not name explicit alternatives or exclusions, but the context where this should be invoked is clear enough to place it before commenting-related actions.

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

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds the bulk execution capability and clarifies the return type (playlist items), but it doesn't mention pagination via the 'token' parameter or any other behavioral aspects. This is minimal value beyond annotations.

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

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

The description is two sentences, front-loaded with the main purpose, and includes the bulk support note. Every word earns its place; there is zero fluff.

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

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

Given the tool's simplicity (3 params, no output schema, read-only annotations), the description covers the core purpose but fails to explain the token parameter, which is likely needed for large playlists. It doesn't describe the response format either, which is not covered by an output schema. It's adequate but not thorough.

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

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

Schema description coverage is 0%, so the description must compensate. It maps 'id' to playlist id and mentions 'ids' for bulk, but it completely omits the 'token' parameter (likely for pagination). The description provides insufficient detail for all parameters, leaving the token unexplained.

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

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

The description clearly states the tool retrieves playlist items given a playlist id, using a specific verb ('Playlist items') and resource ('by playlist id'). It distinguishes from generic tools but doesn't explicitly differentiate from sibling tools like youtube_channel_playlists (which lists playlists of a channel) or youtube_video_related. Still, the purpose is unambiguous.

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

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

The description gives clear context: use when you have a playlist id and want its items. It also mentions bulk support with 'ids' for batched execution, which guides when to use the plural parameter. However, it doesn't mention any exclusions or alternatives, so it's not fully explicit about when NOT to use it.

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

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds minimal extra behavioral context beyond stating the purposeaaa; it doesn't disclose error behavior, return format specifics, or any side effects. With annotations present, the description provides a modest addition by naming the output fields (videoId/pageType), so a 3 is appropriate.

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

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

The description is a single concise sentence that fully conveys the tool's function without redundancy. It is front-loaded and free of unnecessary details.

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

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

For a simple one-parameter tool, the description is sufficient for the core purpose but lacks details on expected output structure, edge cases (e.g., invalid URLs), or how to interpret pageType values. Since there is no output schema and no additional context, the description is minimally complete but not rich.

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

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

The input schema has 100% coverage (url param with type string), and the description adds crucial semantics by specifying it accepts 'YouTube URL or share link', which clarifies the expected format beyond the schema's generic 'url' field. This compensates for the 0% schema description coverage.

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

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

The description clearly states the tool resolves a YouTube URL or share link into videoId and pageType. The verb 'resolve' and resource 'YouTube URL' are specifichol and distinguish this tool from siblings like youtube_search or youtube_download, which perform different actions.

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

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

The description implies usage (when you need to extract an ID from a URL), but it does not explicitly state when to use this tool versus alternatives, nor does it mention any prerequisites or typical scenarios. It's a single purpose tool, so usage is somewhat obvious, but lacks explicit guidance or exclusions.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds no behavioral context beyond the annotations, such as pagination via token, result limits, or that it searches across multiple content types. With annotations covering the safety profile, a 3 is appropriate.

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

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

The description is a single, efficient sentence with no wasted words. It is appropriately sized for a simple search tool, though it could be slightly more informative without becoming verbose.

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

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

Given the tool has 8 parameters, 0% schema coverage, no output schema, and no parameter descriptions, the description is severely incomplete. It does not explain the meaning of parameters like 'geo', 'lang', 'token', or 'sort_by', nor does it describe the return format. The complexity of the tool demands much more detail.

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

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

Schema description coverage is 0%, and the description does not explain any of the 8 parameters. The schema provides only types (all strings) with no enums or descriptions, so the agent has no idea what values are valid for 'type', 'sort_by', 'duration', 'upload_date', or 'token'. The description must compensate for the low coverage but fails to do so.

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

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

The description 'Search videos, channels, playlists' clearly states the verb (search) and resource (YouTube content types), but it does not distinguish this tool from siblings like youtube_channel_search or youtube_hashtag, which also perform searches. The purpose is clear but not differentiated.

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

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

No guidance is provided on when to use this tool versus alternatives. With many sibling search tools (youtube_channel_search, youtube_hashtag, youtube_home_feed), the description should specify that this is a general search across all content types, while others are scoped. The lack of exclusions or alternatives makes usage ambiguous.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the tool's non-mutating nature is known. The description adds no extra behavioral context such as pagination, rate limits, or return format. It merely restates the core function, which is already implied by the name and annotations.

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

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

The description is extremely terse (one sentence) but insufficiently informative. While it avoids verbosity, it under-delivers even basic details like parameter hints or output expectations. It is not appropriately sized for a tool with three parameters and no output schema; conciseness is achieved at the expense of utility.

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

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

With no output schema and minimal parameter documentation, the description does not provide enough context for an agent to invoke the tool effectively. It doesn't mention what data is returned, how filters apply, or any limitations. The tool appears relatively simple, but the description still leaves significant gaps in understanding.

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

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

The schema has 3 parameters (geo, lang, type) with zero description coverage. The description only hints at 'region' (geo), leaving lang and type completely unexplained. It does not compensate for the lack of schema metadata, failing to clarify parameter meanings, formats, or enums. This is a critical gap for a tool with no schema descriptions.

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

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

The description clearly indicates the tool's purpose: retrieving trending videos filtered by region. It is specific enough to distinguish from sibling tools like youtube_search or youtube_home_feed, though it lacks an explicit verb (e.g., 'list' or 'get'). The resource is implied as trending videos, which is unique among the siblings.

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

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention any exclusions, prerequisites, or contexts where another tool would be more appropriate. Given the many youtube-related siblings, this lack of differentiation could lead to misuse.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, covering the safety profile. The description adds the bulk execution capability (accepts 'ids' for batching) which is a behavioral trait not in annotations. However, it does not mention behavior like pagination, required authentication, or what happens with invalid IDs. Annotations carry most of the burden, and the added context is minimal but accurate.

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

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

The description is extremely concise at two sentences, front-loading the core purpose in the first sentence and adding bulk support in the second. Every word is informative. However, it could have included a brief mention of 'token' without sacrificing conciseness, but it is appropriately sized for the tool's simplicity.

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

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

The tool has no output schemaalert, and the description does not explain what the response looks like (e.g., list of video objects with titles, thumbs?). With 0% parameter schema coverage and no output schema, the description should provide more context on return values or additional behavior. Its simplicity works for a basic read tool, but it lacks details like pagination, error cases, and auth requirements, making it incomplete for an agent to use confidently.

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

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

Schema description coverage is 0%, meaning neither the description nor the schema provides explanations for 'id', 'ids', or 'token'. The description only mentions 'id' implicitly and 'ids' in the bulk note, but does not explain their relationship (e.g., precedence, mutual exclusivity) or the purpose of 'token'. With 3 parameters and no coverage, the description fails to compensate, leaving the agent without critical parameter semantics.

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

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

The description clearly identifies the tool as retrieving related videos for a given video ID, using a specific verb ('Related videos') and resource ('video id'). It distinguishes from siblings by focusing on the 'related' concept, but it doesn't explicitly contrast with similar tools like youtube_home_feed or youtube_search, which could fetch recommendations.

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

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

The description implies usage when a user wants related videos for a specific video ID and mentions bulk support for batched execution. It does not explicitly state when not to use it (e.g., if the user wants search results or channel content), but the sibling tool list provides alternative context. The guidance is clear enough for typical scenarios.

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