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

With no annotations, the description carries the full burden and does well: it specifies the return shape (dict with 'logged_in' boolean), which clearly tells the agent what to expect. The verb 'check' implies a read-only, non-destructive operation. It does not mention edge cases or error behavior, but for a simple session status check this level of disclosure is adequate.

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 defines the return format. It is front-loaded, free of filler, and every word serves a 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?

For a tool with no parameters and an output schema already present, the description fully covers what the tool does and what it returns. The simplicity of the operation means nothing important is missing. The distinction from sibling tools is obvious from the purpose statement.

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 is an empty object, meaning the tool accepts zero parameters. The baseline for zero parameters is 4, and the description correctly avoids mentioning any parameters because there are none. No additional semantic information is needed.

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 (check), a specific resource (current Douyin session login status), and is clearly distinct from sibling tools that retrieve content or user data. An agent can immediately understand what this tool does and that it is an authentication status check.

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

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

The description gives no explicit guidance on when to use this tool versus an alternative. However, the tool's purpose is unique among siblings and the intended usage (checking whether the session is logged in) is implied by the description. There are no alternatives for this function, so explicit routing is unnecessary.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does add that refresh_index is for pagination and states the return type, but it omits critical context such as whether authentication is required, how recommendations are generated, or any rate-limit constraints. For a feed tool, login dependencies are especially relevant.

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 Args/Returns structure is clear and front-loaded, with no filler sentences. The long tag list is necessary but could arguably be placed as an enum in the schema; repeating default values that already exist in the schema is minor redundancy.

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 tool with 3 optional parameters and an output schema, the invocation details are mostly covered. However, the definition lacks usage context, such as when to prefer this over search_videos, and does not mention whether login is required, which is a meaningful gap given the sibling check_login_status 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%, and the description fully compensates. It enumerates all 16 allowed tag values, clarifies count as the number of videos, and explains refresh_index as the pagination cursor. Without this, the parameters would be opaque.

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 opening sentence 'Get recommended videos from Douyin home feed' clearly identifies the action and resource with a specific verb. It is distinct enough from siblings like get_video_detail or get_user_posts, though it does not explicitly name alternatives or exclusion conditions.

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 use this tool instead of search_videos, get_user_posts, or check_login_status. It does not mention prerequisites, alternatives, or typical scenarios, leaving the agent to infer usage from the tool name alone.

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

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does disclose the return shape (dict with replies list and pagination metadata) and explains that source_keyword is used for the referer. However, it does not mention authentication needs, rate limits, error behavior, or confirm that this is a read-only operation, leaving some gaps relevant to a no-annotation 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 compact, front-loaded with the core purpose, and uses a clear Args/Returns structure. Every sentence contributes meaning, and there is no repeated 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?

The tool is a straightforward paginated read operation with four parameters, all of which are explained. An output schema is present, so the description does not need to fully document return values. The main gap is the lack of any mention of auth or rate limits, but given the tool's simplicity, the description is largely sufficient.

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 fully compensates by explaining every parameter: comment_id is the parent comment ID, cursor is the pagination cursor, count is the number of replies per page, and source_keyword is an optional search keyword used for the referer. This adds real semantic meaning beyond the bare schema types and defaults.

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 verb+resource combination: 'Get replies (sub-comments) for a Douyin comment.' This clearly identifies the operation and naturally distinguishes it from the sibling get_video_comments, which presumably fetches top-level comments for a video rather than nested replies.

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 makes clear that the tool is for fetching replies to a parent comment, implying it should be used after a comment ID is obtained from a parent-comment tool like get_video_comments. It does not explicitly state when not to use it or name an alternative, but the context is clear enough for an agent to select it correctly.

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

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

With no annotations provided, the description carries the behavioral disclosure burden. It clearly indicates a read-style operation ('Get') and describes the return shape, which is useful. However, it does not disclose auth requirements, failure behavior for invalid sec_user_id, rate limits, or whether a valid login is required.

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 with a clear summary line, an Args section, and a Returns section. Every sentence contributes useful information, and 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 tool with an output schema, the description covers the main operational need: what the tool does and what it returns. It is not fully complete because it omits auth prerequisites and error scenarios, which the sibling check_login_status suggests may be relevant, but the core call contract is adequately specified.

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 only says sec_user_id is a required string, but the description explains that it is the user's security ID and gives a recognizable prefix pattern (MS4wLjABAAAA). This adds significant semantic value beyond the schema, fully covering the only parameter.

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 verb and resource: 'Get Douyin user profile information.' The listed return fields (nickname, avatar, follower count, etc.) make the scope concrete and clearly differentiate it from siblings like get_user_posts, which concern posts rather than profile data.

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

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

The description provides no guidance about when to use this tool versus alternatives. It does not mention exclusions, prerequisites like login status, or point to get_user_posts or check_login_status for adjacent use cases. Usage is only implied by the tool's name and one-line summary.

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

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

With no annotations provided, the description carries the burden, and it does disclose the return shape ('dict containing video list and pagination info') plus pagination parameters. It does not mention authentication requirements, rate limits, or whether only public videos are returned, but for a read-only getter the stated behavior is minimally transparent.

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, with a single-purpose opening line followed by args and returns sections. There is no filler or repetition of the schema beyond useful defaults.

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 paginated read operation, all parameters are documented and the return type is summarized while an output schema provides further detail. The main missing context is when to choose this versus sibling search/feed tools, and how to advance pagination.

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%, yet the description documents all three parameters with meaningful one-line explanations: sec_user_id, max_cursor as pagination cursor, and count as page size. The semantics are clear, though max_cursor could explain that it comes from the previous response.

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 clear verb and resource: 'Get videos posted by a Douyin user,' so an agent knows the tool lists a user's videos. It doesn't explicitly compare against siblings like get_homefeed or search_videos, but the user-scoped wording makes its job identifiable.

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 prefer this tool over alternatives, nor any exclusions. Given siblings such as get_homefeed and search_videos that could also return video lists, an agent is left to infer the appropriate 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?

With no annotations, the description carries the behavioral disclosure burden. It does disclose pagination behavior, cursor/count defaults, and the referer purpose of source_keyword. However, it does not clarify whether these are only top-level comments, what pagination metadata is returned, or any rate-limit/auth considerations, leaving meaningful behavioral 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 compact and well-structured with a one-line purpose followed by a clear Args/Returns breakdown. Every element earns its place, and the key action is front-loaded.

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

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

For a paginated retrieval tool, the description covers the core invocation details: required ID, pagination parameters, and return shape. It is slightly incomplete because it does not distinguish top-level comments from nested sub-comments, especially given the get_sub_comments sibling, but it is otherwise sufficient for calling the tool.

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

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

The schema description coverage is 0%, but the description fully compensates by explaining every parameter: aweme_id identifies the video, cursor drives pagination, count sets page size, and source_keyword is for the referer. This adds meaning well beyond the raw schema fields.

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 and resource: 'Get comments for a Douyin video.' It is unambiguous about what the tool does, but it does not differentiate itself from the sibling get_sub_comments, so an agent must infer the difference between comments and sub-comments.

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 implied: use this tool when you need comments for a Douyin video. However, there is no explicit guidance about when to choose get_video_comments over get_sub_comments or other siblings, so the selection guidance remains implicit 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?

No annotations exist, so the description carries the full disclosure burden. It does reveal the return shape (dict with statistics, author info, URLs), which is useful behavioral context. However, it omits auth requirements (relevant given the check_login_status sibling), behavior for invalid or nonexistent IDs, and error handling.

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?

Docstring-style layout with a one-sentence purpose, an Args line, and a Returns line — scannable and free of filler. Each line earns its place, though the purpose line and Returns section overlap slightly in what they promise.

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 read tool with an output schema present, the main contract is documented: what it does, what the parameter means, and roughly what it returns. Missing pieces are sibling differentiation, auth needs, and error behavior, which an agent would need to invoke it reliably in a real Douyin session.

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% and the schema only types aweme_id as a bare string. The description compensates by clarifying it is 'the video/aweme ID' and a 'numeric string', adding both semantic role and format. It stops short of an example or guidance on where to obtain the ID, but the core meaning is conveyed.

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?

Uses a specific verb+resource ('Get detailed information about a Douyin video') and enumerates the concrete payload (title, description, statistics, author info, URLs). This clearly distinguishes it from siblings like get_video_comments, get_homefeed, and get_user_info, whose scopes are narrower or focus on different resources.

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 choose this over sibling tools. It never references get_video_comments, search_videos, or get_homefeed as alternatives, and states no exclusions or prerequisites. Usage context must be inferred entirely from the tool name and return payload.

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

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

No annotations are provided, so the description carries the behavioral burden. It clearly states that the tool searches and returns a dict with a video list, which is core behavior, but it does not disclose authentication requirements, rate limits, pagination behavior beyond parameter defaults, or error conditions. This is adequate but not rich.

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

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

The description is well-structured with a one-sentence purpose, a clean Args list, and a Returns line. Every line adds useful information and nothing is redundant or wasteful.

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?

All six parameters are semantically documented and the return type is stated, so an agent can invoke the tool correctly. Minor gaps remain around usage boundaries relative to sibling tools and any authentication or rate-limit caveats, especially given there are no annotations to provide safety context.

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

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

Schema description coverage is 0%, but the description fully compensates by explaining every parameter: keyword, offset, count with max, search_channel with allowed values, sort_type with meaning, and publish_time with filter ranges. This adds significant meaning beyond the bare 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 opens with a specific verb and resource: 'Search for Douyin videos by keyword.' This makes the tool's purpose immediately clear and distinguishes it from sibling tools like get_homefeed, get_video_detail, or get_user_posts, which serve different retrieval needs.

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 keyword-based search purpose implies when this tool should be used, but the description provides no explicit guidance about when to prefer it over alternatives or when not to use it. For example, it doesn't mention that get_video_detail is for a single video or get_homefeed is for feed browsing.

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