SocialDataX YouTube MCP

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

Annotations already declare readOnlyHint=true, and the Chinese description reinforces that this is a query operation. The description adds context about the account-level API Key scope, but it does not disclose details such as response format, rate-limit implications, or whether the balance is cached or real-time.

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 compact sentence with the key information front-loaded. The bilingual repetition and enumeration of 'balance / remaining points / points' is slightly redundant but not harmful.

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 this is a zero-parameter read-only balance lookup, the description is complete. An output schema is present, so return values do not need to be described, and the annotations cover the safety profile.

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 schema description coverage is 100%, so there is nothing for the description to explain about inputs. The description still usefully clarifies that 'points balance' refers to remaining credits.

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

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

The description clearly states a specific action, resource, and scope: querying the SocialDataX points balance for the current API Key account. It is fully distinguishable from the unrelated zhihu_ sibling tools even without inspecting schemas.

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 intended use is reasonably implied by the name and description, but there is no explicit guidance about when to check the balance, how it relates to other tools, or when this tool would not be appropriate. No alternatives 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 and openWorldHint. The description adds useful behavioral detail beyond that, including supported URL forms (/@, /channel/, /c/, /user/) and normalization of tab subpage links to the channel homepage. No contradictions with annotations were 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 tool description is a single focused sentence that states the core purpose, and all supporting detail is appropriately placed in the parameter documentation. 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 single-parameter, read-only tool with an output schema and clear annotations, the definition is complete. The parameter documentation covers edge cases like tab subpage links and invalid inputs, so an agent has everything needed to call 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 coverage is 100%, and the parameter description still adds substantial meaning beyond the schema: it enumerates accepted URL shapes, explains normalization behavior, identifies the proper source field (author.profile_url), and explicitly lists rejected input types. This is excellent guidance for correct invocation.

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

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

The description clearly states the action ('获取频道资料' / get channel info) and the specific input resource (YouTube channel homepage URL). It distinguishes itself from siblings like youtube_get_user_posted_videos_by_channel_url by focusing on channel profile data, though it does not explicitly name or contrast any 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?

The parameter description provides strong usage context: pass author.profile_url from search/detail/comment results, and avoid channel_id, bare @usernames, channel names, video links, playlist links, or search page links. However, it does not explicitly discuss when to choose this tool over the sibling video-focused 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?

Beyond readOnlyHint and openWorldHint, the definition discloses concrete behavior: it returns a list of videos or Shorts, normalizes tab subpage URLs to the channel homepage, treats page_token as an opaque token that must be passed unmodified, and explicitly rules out live/course/playlist types. This gives the agent actionable expectations.

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

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

The main description is a single front-loaded sentence that immediately communicates purpose and input. The schema's page_token explanation is thorough but includes some redundant prohibitions; overall it is well-organized and 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?

For a read-only list operation with an output schema, three well-documented parameters, and detailed pagination/token rules, the definition is complete. An agent has everything needed to make a correct first call and continue pagination 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 100%; channel_url, video_type, and page_token all have detailed descriptions in the input schema. The free-text description adds no additional parameter-level meaning, so the baseline of 3 applies.

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

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

The description states a specific verb-resource pair: 获取频道发布视频或 Shorts 列表 (get the channel's posted videos or shorts) from a YouTube channel homepage link. This clearly differentiates the tool from siblings like channel info, video detail, comments, or search.

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

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

The schema gives strong contextual guidance: acceptable channel_url forms, what not to pass, when to reset page_token, and video_type restrictions. However, the description never explicitly says when to prefer this tool over sibling tools such as youtube_get_channel_info_by_url, so alternative selection is implied rather than stated.

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 openWorldHint=true, so the safety profile is covered. The description adds behavioral context beyond annotations: it specifies pagination support, the requirement to preserve reply_token untouched, and the routing behavior to the sibling tool. It does not discuss errors or rate limits, but those are not critical gaps.

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

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

The description is a single dense paragraph of semicolon-separated directives, purpose first, followed by routing rules and exclusions. It is efficient but packs several conditions together, making it slightly less scannable than a short structured list would be.

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 two-parameter tool with rich schema descriptions, output schema present, and sibling context, nothing essential is missing. The description covers the main workflow, the relationship to youtube_get_video_comments_by_url, user interaction when location info is missing, and pagination constraints.

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

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

Schema description coverage is 100%, so the heavy lifting is already done by the schemas for reply_token and page_token. The description still adds value by telling the agent where reply_token comes from (items[*].reply_token from the sibling tool), when to reset page_token, and which identifiers not to pass.

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 opens with a specific action and resource: '根据 reply_token 获取 YouTube 评论回复' (get YouTube comment replies by reply_token). It also explicitly distinguishes itself from the sibling youtube_get_video_comments_by_url by stating when that sibling should be used instead, and clarifies that comment_id must not be passed.

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 conditions are explicit: use directly when a valid reply_token is provided, call youtube_get_video_comments_by_url when only a video link exists, ask the user for missing video identification, and never pass comment_id. This fully covers when, when-not, and alternatives.

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

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

Annotations already declare readOnlyHint=true, so the description does not need to repeat safety. It adds value by specifying 'public' and 'top-level' comments, but it does not disclose behavior such as pagination limits, rate limits, or how many comments are returned. This is acceptable but not strong.

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

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

The description is a single front-loaded sentence with no filler or repetition. It communicates the core operation efficiently; the schema carries the detailed parameter behavior.

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 schema is rich and an output schema exists, so the main gaps are not about return values. However, the description does not explicitly route the agent to youtube_get_video_comment_replies for replies or provide any usage context beyond the basic operation. It is minimally complete but lacks helpful cross-tool guidance.

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

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

Schema description coverage is 100%, so the schema already provides detailed explanations for video_url, sort_type, and page_token. The description adds no parameter-level meaning beyond the schema, so the baseline of 3 applies.

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

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

The description states a clear verb and resource: 'get public video top-level comments based on a YouTube video link.' The phrase '一级评论' (top-level comments) distinguishes it from the sibling tool youtube_get_video_comment_replies, so an agent can tell them apart.

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 top-level comments only by saying '一级评论', but it does not explicitly state when to use this tool versus youtube_get_video_comment_replies or mention conditions for choosing alternatives. There is no exclusions or when-not-to-use 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 provide readOnlyHint and openWorldHint, so the safety profile is covered. The description adds the '公开' (public) scope, implying non-public videos may not be retrievable, but it does not mention failure modes, rate limits, or any other behavioral caveats. 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?

The description is a single compact sentence that conveys the core purpose immediately. There is no filler or redundant repetition of the tool name, and it is appropriately sized for a simple, single-parameter tool.

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 rich parameter schema, read-only annotations, and presence of an output schema, the description covers the essential invocation context. It could be more explicit about edge cases such as private videos or invalid URL behavior, but it is sufficiently complete for straightforward 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 coverage is 100%, and the schema itself documents supported URL formats, share_url usage from search results, and forbidden link types. The description adds no additional parameter meaning beyond restating that the input is a YouTube URL, so the baseline of 3 is appropriate.

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

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

The description states a specific action ('获取公开视频详情') on a specific resource, using a URL as the input, which clearly identifies this as a video-detail fetch. It is distinguishable from sibling tools like comments or channel info by name and phrasing, but it does not explicitly name or differentiate from those 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 offers no guidance on when to choose this tool over alternatives such as youtube_get_video_comments_by_url or youtube_search_videos. The parameter schema advises on valid URL types and what not to pass, but that addresses input formatting, not tool selection 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?

Beyond the readOnlyHint annotation, the description discloses the maximum 240-second wait, the no-reprocessing behavior, and that the tool does not resubmit tasks. This adds meaningful behavioral context not present in annotations, though it does not describe edge-case failure behavior.

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

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

The description is a single compact sentence that front-loads the core purpose and immediately includes the most important constraints: job_id source, 240-second wait, and no resubmission. Every clause 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?

Given this is a simple one-parameter status query with an output schema already present, the description covers all necessary operational details: valid job_id sources, wait behavior, and idempotency expectations. Nothing critical is missing.

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

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

Schema description coverage is 100%, and the input schema already fully explains that job_id is the speech-to-text task ID, where to obtain it, and not to pass video_id or links. The description does not add meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly states the tool queries the status of a YouTube speech-to-text job by job_id, using a specific verb ('查询') and resource ('任务状态'). It is easily distinguishable from the sibling submit tools, which create jobs rather than poll status.

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 says to use a user-provided job_id or one returned by the submit tool, and tells the agent not to resubmit or trigger reprocessing. This provides clear conditions for use and explicitly warns against the main 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 and openWorldHint=true, so the safety profile is covered. The description adds context: it mentions 'only returns video results', filtering support, page_token pagination, and the exclusion of playlist links. These behavioral traits go beyond the annotations and are useful for the agent. Since annotations cover the base safety, a 4 is appropriate—it adds meaningful context without needing to repeat the read-only property.

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, purpose first, then usage guidance and limitations. No redundant phrasing, each clause earns its place. The description is front-loaded with the core action and scope, and the usage guidance follows naturally. It is concise without sacrificing substance.

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 6 parameters, one required, 100% schema coverage, and an output schema, the description covers everything an agent needs: when to use, when not, pagination behavior, and limitations (playlist links). The output schema handles return structure, so nothing is missing. The description is complete for correct invocation and routing.

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

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

Schema description coverage is 100%, and each parameter (keyword, sort_type, page_token, video_type, duration_range, publish_time_range) has detailed descriptions in the schema, including enums, defaults, and explicit instructions (e.g., not to modify page_token, what not to pass as keyword). The overall description adds no extra parameter-specific meaning beyond what the schema already provides. With coverage at 100%, the baseline of 3 is appropriate; the description does not need to compensate.

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

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

The description clearly states the verb 'search', the resource 'YouTube public videos', and the scope 'only returns video results'. It distinguishes itself from video detail, comment, and channel tools by explicitly listing what to use when the user already has a link or channel. This is unambiguous and separates it from 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?

Provides explicit when-to-use: 'when the user needs to find videos by search term'. It gives exclusions: 'if the user already has a video, Shorts, or youtu.be link, use video detail/comment tools; if they have a channel homepage link, use channel profile/posted videos tools'. It also states playlist links are not supported as search input. This is thorough routing that needs no inference.

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 description discloses meaningful behavioral traits beyond annotations: the operation may wait up to 240 seconds, and if not completed it returns a job_id plus a next query action. This gives the agent a clear model of the asynchronous task lifecycle. No contradiction with annotations exists.

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 focused sentence that front-loads the action and resource, then states the timeout and fallback behavior. Every clause provides necessary operational information with 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?

The description is largely complete for an async submission tool: it specifies wait time, job_id return, and next-step instruction. The output schema covers return details, and the URL parameter constraints are in the schema. A minor gap is that the 'next query action' is not concretely named, and the sibling by_video_id alternative is not referenced, though both are inferable from context.

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

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

The input schema covers the only parameter, video_url, with 100% coverage and a rich description of accepted URL formats and exclusions. The main tool description adds no additional parameter semantics, so the baseline of 3 is appropriate.

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

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

The description clearly states a specific action (submit a YouTube video speech-to-text task) and the resource (YouTube video by URL). It is obvious what the tool does, but it does not explicitly differentiate this from the sibling youtube_submit_video_speech_text_by_video_id within the description text itself.

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 about when to use this tool versus the by_video_id variant or when not to use it. The tool name implies the distinction, but the description itself provides no usage context or alternative selection hints.

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 description adds useful behavioral context beyond annotations: it reveals the tool is an async submission that waits up to 240 seconds and returns a job_id with a next query action when incomplete. Annotations already indicate a non-read-only, non-idempotent operation, so this behavior disclosure is valuable and not contradictory.

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 compact sentence that front-loads the main action, then adds the critical timeout and fallback behavior. There is no filler or redundant 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?

For a one-parameter async submission tool with an output schema, the description sufficiently covers the task, the wait limit, and the job_id handoff for incomplete results. It could be slightly more explicit about the completed-case response and the exact sibling for querying the job, but those are inferable from the schema and sibling names.

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

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

Schema description coverage is 100%, and the schema itself provides detailed semantics for video_id: 11-character ID, use from search results, and do not pass links. The tool description only restates 'video_id' without adding semantic detail, so the baseline of 3 applies.

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

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

The description states a specific verb ('提交'), a specific resource ('口播转文字任务' / speech-to-text task), and a specific input basis ('根据 YouTube video_id'). It also distinguishes itself from the by-URL sibling by emphasizing video_id, and clarifies the async submission behavior.

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 for when to use the tool: when you have a YouTube video_id and need to submit a speech-to-text job. It also explains the post-submission flow (wait up to 240 seconds, then receive job_id if not complete). It does not explicitly name alternatives or exclusions, but the by-URL sibling is easily inferable from the naming.

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