SocialDataX TikTok MCP

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

Annotations already declare readOnlyHint=true, and the description reinforces that this is a read-only balance query. It adds useful context by tying the balance to the current API Key and pointing to the billing dashboard for recharges. No contradictions or hidden side effects are indicated.

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 short sentences: the first states the core purpose, and the second provides an actionable billing link. Every word earns its place without unnecessary detail.

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 zero-parameter, read-only balance query with an output schema, annotations, and a billing link, the description is fully sufficient. No additional information is needed for an agent to select and invoke it 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?

The tool has zero parameters Belarusand schema coverage is 100%, so parameter semantics are not a burden on the description. The description still adds value by explaining what the returned balance represents.

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 (query) and resource (current API Key account's SocialDataX points balance), including Chinese and English terms. It is unambiguous and obviously distinct from the YouTube-focused 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 identifies the exact context: querying the balance for the current API Key accounttons. It also provides a relevant follow-up URL for recharging. There are no competing sibling tools for balance checking, so no explicit alternatives are needed.

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 safety is covered. The description adds genuinely useful behavioral context beyond that: page_token is opaque and must be passed back unmodified and not reused across different request chains, and it explains the parent_comment_id/reply_to_comment_id relationship. It stops short of auth requirements or throttling disclosure, so not a 5.

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?

Purpose and pagination support are front-loaded in the first clause, followed by usage rules and the parent/child semantics. It is dense but every sentence carries routing or constraint information; slight redundancy between the description and the schema's own comments keeps it from a 5.

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 params, 2 required, full schema coverage and an output schema present, the description needn't explain return values and correctly focuses on how to acquire IDs and pages. It covers the acquisition flow and pagination contract well; only minor gaps remain (no mention of token expiry or failure/empty-result behavior).

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%, so the baseline is 3 and the schema already documents all three parameters thoroughly (including type warnings). The description still adds value the schema lacks: the rule not to pass the reply item's own comment_id and the opaque-token reuse constraint, which sharpens how comment_id and page_token must be supplied.

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?

States a specific verb (获取回复/get replies), resource (TikTok 一级评论的回复), and scope (identified by post_id + comment_id, paginated by page_token). It implicitly distinguishes itself from the sibling first-level comment tools by instructing to call '对应一级评论工具' to fill missing IDs, so an agent can separate replies from top-level comments without opening either schema.

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?

Gives explicit routing rules: use directly when a complete valid ID combo exists, call the corresponding first-level comment tool when post_id/link exists but required IDs are missing, and ask the user when post-location info is absent. It also adds a negative rule ('不要传回复项自身的 comment_id'), which is exactly the when-not guidance the dimension asks for.

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, covering the safety profile. The description adds that it retrieves top-level comments and supports page_token pagination, which is useful but limited; it does not disclose rate limits, auth needs, or 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?

A single, front-loaded sentence with zero waste. It states the action, input, and a key pagination feature concisely.

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 simple read operation, full schema coverage, annotations, and an output schema, the description is almost complete. It clearly states what is returned (top-level comments) and how to page, though it could briefly mention that replies are handled by a separate 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 100%, so the schema fully documents both parameters. The description only mentions post_id and page_token pagination, adding no meaning beyond what the schema already provides, 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 verb (获取) and resource (一级评论) scoped to TikTok post_id, implicitly distinguishing from siblings that fetch by URL or fetch replies. However, it does not explicitly name or contrast with those alternative tools, so it falls short of full sibling differentiation.

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

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

The description implies the tool is used when you have a post_id, but provides no guidance on when to prefer it over tiktok_get_post_comments_by_url or tiktok_get_post_comment_replies. No prerequisites or exclusions 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 openWorldHint=true, covering the safety profile. The description adds two useful behavioral facts beyond that: results are limited to top-level comments (not replies) and page_token pagination is supported. It does not cover auth requirements, rate limits, or response shape, but those gaps are minor against 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?

A single sentence that front-loads the resource and action, then appends the pagination capability. 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 simple read-only listing tool with a fully documented 2-parameter schema, an output schema, and read-only annotations, the description covers the core purpose and pagination behavior. The only meaningful gap is the absence of guidance on choosing between the URL-based and post_id-based sibling tools.

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

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

Schema description coverage is 100% and page_token is documented in exhaustive detail in the schema, including opacity and non-reuse rules. The description only repeats that page_token pagination is supported, adding no syntax or constraint information beyond the schema, so the baseline 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 and resource ('获取一级评论' / fetch top-level comments) and names the URL-based entry point, and it explicitly scopes results to top-level comments, which distinguishes it from the replies sibling. It does not mention or distinguish itself from tiktok_get_post_comments_by_post_id, so it stops short of full sibling differentiation.

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

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

Usage is only implied by '根据...链接' (based on the link): an agent can infer this is for when a post URL is available, but the description never states when to prefer it over tiktok_get_post_comments_by_post_id or tiktok_get_post_comment_replies. No exclusions or prerequisites are given.

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=true and openWorldHint=true, covering the safety profile. The description adds that both video and photo posts are supported, but it does not disclose further behavioral traits such as rate limits, authentication needs, or failure behavior. It does not contradict 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 one efficient, front-loaded sentence with no redundant wording. It conveys the verb, resource, and supported content types in minimal space.

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 lookup with a rich input schema, existing annotations, and an output schema, the description is complete enough for an agent to select and invoke the tool correctly. No critical information needed for basic use is missing.

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

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

The input schema has 100% parameter description coverage, including examples and an explicit instruction not to pass post_id instead of url. The tool description only restates that the lookup is URL-based and adds no extra semantic value beyond the schema.

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

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

The description clearly states a specific verb ('获取') and a specific resource (TikTok 作品详情), and explicitly scopes the tool to video and photo post URLs. This makes it easy to distinguish from sibling tools that fetch comments, user info, or post lists.

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 implied: use this when you have a TikTok post page URL and need post details. However, the description does not explicitly say when to prefer this over siblings like tiktok_get_post_comments_by_url or tiktok_get_user_info_by_profile_url, nor does it mention exclusion 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 declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds only that the data is 公开资料 (public), which is marginal context; it says nothing about authentication needs, rate limits, failure modes for invalid or private URLs, or latency.

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 efficient sentence that front-loads the input (profile URL) and the outcome. Nothing is wasted, though the same brevity is also what leaves the definition thin.

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?

Because an output schema exists, return values need not be explained, and the one parameter is fully covered by the schema. What is missing is the routing information against the many similarly named siblings (user info vs. user posts, URL vs. tiktok_id), which is the main thing an agent needs here.

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 single parameter is fully documented in the schema, including a non-empty constraint and a concrete example URL (https://www.tiktok.com/@teamtrump). The description adds no format or syntax detail beyond that, so the baseline 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+lookup key: retrieve a user's public profile from a TikTok profile URL. This implicitly distinguishes it from the sibling tiktok_get_user_info_by_tiktok_id, since the identifier type is named, though the sibling is never referenced explicitly.

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 is only implied — an agent must infer that this tool is chosen when it holds a homepage URL rather than a numeric TikTok ID. There is no explicit when-to-use or when-not statement and no mention of the 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 declare readOnlyHint=true and openWorldHint=true, so the safety and reach profile is covered. The description adds little beyond that – it confirms the data is public but says nothing about rate limits, quota consumption, or failure behavior for a non-existent ID.

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 short sentence is trivially front-loaded and wastes no words, but it is under-specified rather than genuinely concise – it could carry the sibling distinction at almost no cost.

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 an output schema present and only one fully documented parameter, the description does not need to explain return values. It is adequate for invocation, but omits the discriminator against tiktok_get_user_info_by_profile_url that an agent with 14 siblings would benefit from.

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 description already explains the format and even forbids the '@' prefix and full URLs. The description adds no additional parameter meaning, so the baseline 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 names a specific verb and resource combination ('获取用户公开资料' – fetch user public profile) and scopes it to identification by TikTok ID, which implicitly separates it from tiktok_get_user_info_by_profile_url. It is clear but does not explicitly name the sibling or contrast the two input modes.

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 when-to-use guidance, no mention of the profile-URL alternative, and no prerequisites or exclusions. The agent is left to infer that this is the right tool when it holds a TikTok ID rather than a URL.

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 one behavioral fact beyond that — pagination via page_token is supported — but says nothing about result volume, ordering, 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?

A single sentence with the resource and the pagination capability front-loaded, and no filler. Nothing could be removed without losing 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?

With an output schema present and annotations covering safety, the return-value burden is lifted, and both parameters are fully documented in the schema. The remaining gap is routing guidance among the many sibling user/post retrieval tools.

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

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

Schema description coverage is 100% and the page_token description in the schema is extremely detailed (opaque token, must be passed back verbatim, no cross-query reuse). The description merely restates that pagination exists, adding nothing beyond the schema, so the baseline 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 and resource ('获取作品列表' / fetch post list) scoped by input type ('根据 TikTok 用户主页链接'). This implicitly separates it from the sibling tiktok_get_user_posts_by_tiktok_id, but it never names the alternative explicitly, so it falls short of a 5.

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

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

There is no when-to-use guidance, no conditions or prerequisites, and no mention of when to pick this over tiktok_get_user_posts_by_tiktok_id or tiktok_search_posts. The only usable signal is the input type implied by the name and description.

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 the safety profile (readOnlyHint=true, openWorldHint=true), so the bar is lower. The description adds that the result set is paginated via page_token, which is useful context, but it omits the cost/rate/error behavior typical of an open-world scraping endpoint.

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 short sentence that front-loads purpose and identifier, then notes pagination support. Every clause earns its place with 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?

An output schema exists, so return values needn't be described, and the schema fully documents both parameters. What is missing is only the sibling routing against tiktok_get_user_posts_by_profile_url; otherwise the definition is complete for a read-only paginated listing 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 100% – the schema itself carries unusually rich guidance (must not include '@', no profile URLs, opaque token must be passed back verbatim, no cross-query reuse). The description only echoes pagination support and adds nothing beyond the schema, so baseline 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?

States a specific verb+resource ('获取用户作品列表' – get a user's post list) scoped by identifier ('根据 TikTok 号'), which is clear enough to act on. However, it never distinguishes itself from the near-identical sibling tiktok_get_user_posts_by_profile_url, whose only difference is the identifier type, leaving that choice implicit.

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 when-to-use / when-not-to-use guidance and no mention of the profile-url sibling. The implicit selection signal is only the parameter name 'tiktok_id', so an agent must infer that this tool is for ID-based lookup and the sibling for URL-based lookup.

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 long-polling behavior (up to 240 seconds) and guarantees that no reprocessing is triggered. This is valuable behavioral context that prevents duplicate submissions and sets wait 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?

One dense sentence front-loads the core action and resource, then packs in the key constraints: wait limit, no reprocessing, and no resubmission. No filler or redundant explanation.

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 a single well-documented parameter and an output schema present, the description covers the ID source, polling behavior, and side-effect absence. An agent has enough information to invoke the tool correctly without further 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?

Schema coverage is 100% and the schema's job_id description already specifies valid sources and exclusions. The tool description restates this without adding new parameter-level meaning, so the baseline 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 concrete action—'查询TikTok视频口播转文字任务状态' (query speech-to-text task status)—and clearly ties it to job_id. This distinguishes it from the submit siblings and the other TikTok data-fetching 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?

It explicitly says the tool is for continuing unfinished tasks, instructs the agent not to resubmit jobs, and points to submit-tool-returned job_id as valid input. This gives clear when-to-use and when-not-to-use guidance while naming the source 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 cover the safety profile (readOnlyHint=true, openWorldHint=true), so the bar is lower. The description adds real behavioral context beyond them: it returns both video and image posts, filters out user cards and other non-post results, and supports page_token pagination. It does not discuss rate limits or result caps, keeping it just short of a 5.

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?

Front-loaded with the core action, then layered guidance and constraints, each sentence carrying distinct information (routing rules, continuation reuse, filtering, pagination). No redundancy or filler despite the length.

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 an output schema exists, return values need not be described. The description covers routing, filtering behavior, pagination continuation and result reuse, leaving no material gap for a read-only search tool with fully documented parameters.

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%, so the baseline is 3 and the schema already documents keyword, page_token and content_type in depth. The description adds meaning the schema does not: content_type semantics as a filter, the non-post result filtering, and the instruction to reuse share_url/post_id when continuing from results, which guides downstream calls.

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?

States a specific verb and resource ('搜索 TikTok 作品') and immediately scopes the result set ('可返回视频和图片作品'). It further distinguishes itself from siblings by naming the detail and comment tools it is not, so an agent can route without opening any schema.

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?

Explicit when-to-use ('用户需要按搜索词查找作品时使用') and two explicit when-not-to-use cases with named alternatives: existing post link → detail/comment tools, existing post_id → comment-by-ID tool, '均无需先调用搜索'. It also explains how to continue from a prior search by reusing share_url/post_id.

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 genuine behavioral context beyond them: it does not return post or user details and does not support pagination, which sets agent expectations about result shape and result-set size.

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?

Compact and front-loaded: the core purpose leads, followed by scope limits and routing. Dense but no sentence is wasted, though the run-on clause structure could be broken up slightly.

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?

An output schema exists, so return values need not be described, and the description already covers scope, no-pagination, and alternative routing. Nothing an agent needs to invoke this correctly 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 coverage is 100% and the single keyword parameter is already well documented in the schema (non-empty keyword, no links/IDs/pagination tokens). The description does not add syntax or format detail beyond the schema, so baseline 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?

States a specific verb+resource (获取 TikTok 搜索框联想词) and immediately draws the boundary that it returns neither posts nor users. This distinguishes it from sibling tiktok_search_posts and the detail tools without needing to open any schema.

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 routes the agent: use text for post search, search posts directly when a clear term exists, and use the corresponding detail tools when post/user profile links are already available. Both when-to-use and alternatives are named.

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/openWorldHint it discloses concrete behavior: which fields are omitted (private_account, following_count, posted_content_count), the pagination rule (continue only while next_page_token is non-empty), and downstream chaining (non-empty tiktok_id / profile_url can be fed to the profile and posts tools). These are non-obvious traits the annotations do not carry.

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?

Purpose is front-loaded and the dense semicolon-separated clauses each carry information. There is mild redundancy in restating the two chaining identifiers (tiktok_id and profile_url) in near-identical clauses, which costs a little tightness.

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 an output schema present, return values need not be spelled out, yet the description still adds the field-omission caveat and the identifier-chaining guidance an agent needs to actually use the results. Nothing essential is missing for a read-only search 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 100%, so keyword and page_token are already documented (including the non-empty constraint and the opaque-token rule). The description reinforces the pagination semantics of page_token ('是否继续翻页仅以 next_page_token 是否为空为准') and adds flow meaning, going slightly beyond the baseline.

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?

States a specific verb+resource (按非空搜索词搜索 TikTok 用户) plus the discovery intent (按用户名、昵称或品牌名查找候选用户). It clearly distinguishes itself from sibling search_posts and the get_user_info_* / get_user_posts_* tools, so an agent can select it without opening any schema.

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?

Gives an explicit use case (finding candidate users) and an explicit exclusion: '已知准确用户标识且只需上述后续数据时，使用对应入口，无需先搜索' — i.e. skip this tool and go straight to the profile/posts entry points. This is a genuine when/when-not routing rule with the alternative named.

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 important non-obvious behavior: the call waits up to 240 seconds and returns a job_id plus next-step query action if the job is not complete. This is useful beyond the annotations, though it does not detail success-path behavior or error conditions.

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 compact sentence carries the essential information: input identifier, wait limit, and non-blocking fallback with job_id. No filler or redundant repetition of schema 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 one-parameter submit tool with 100% schema coverage and an output schema, the description covers the key operational facts. It could be more complete by naming the polling sibling tiktok_get_video_speech_text_job or the URL submission alternative, but 'next query action' hints at the workflow.

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 already fully documents aweme_id, including the requirement to pass it as a string, not convert to number, and the post_id alias. The description restates the post_id reuse without adding extra parameter-level meaning beyond the schema.

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

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

The description states a clear action and resource: submit a speech-to-text task for a TikTok video by aweme_id, and notes that a post_id can be reused. It does not explicitly differentiate from the sibling tiktok_submit_video_speech_text_by_url, so some differentiation relies on the tool name.

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 TikTok video aweme_id or a content_type=video post_id. It does not explicitly say when not to use it or name the URL-based alternative, stopping short of full routing 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 mark readOnlyHint=false and idempotentHint=false, so the agent knows this is a mutating, non-idempotent call. The description adds valuable behavioral detail: it waits up to 240 seconds, returns a job_id if incomplete, and hints at a follow-up query. This goes beyond the annotations and helps the agent anticipate latency and response.

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 sentence that conveys the action, the wait behavior, and the return contract. Every clause earns its place, and the most important information (submit task) is front-loaded. No extraneous 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?

Given the tool's role as a submission action, the description covers the essential contract: what it does, how long it blocks, and what it returns. It does not name the exact query tool for later retrieval, but the sibling 'tiktok_get_video_speech_text_job' and the phrase 'next query action' provide enough context. The presence of an output schema further covers return structure, so missing details are minor.

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 100% schema description coverage, the video_url parameter is already well-documented in the schema. The description does not add new meaning about the parameter (e.g., URL format validation or required patterns). It stays at the baseline of 3 because the schema handles parameter explanation sufficiently.

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 speech-to-text task for a TikTok video), the resource (TikTok video via URL), and key behavior (waits up to 240 seconds, returns job_id). It distinguishes from the sibling by URL vs aweme_id through the tool name, and no ambiguity remains.

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 (submit a video transcription task by URL) but does not explicitly explain when to prefer this over the aweme_id variant, nor does it name the companion query tool. It mentions 'next query action' but doesn't specify the tool, making the guidance implicit rather than explicit.

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