tiktokporn

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

With no annotations provided, the description bears full responsibility for disclosure. It mentions 'max 20' and 'sample,' but lacks details on pagination (e.g., cursor usage), default behavior, required permissions, or return format. It does not contradict annotations since none exist, but it is thin on behavioral context.

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

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

A single, front-loaded sentence that is concise and free of filler. It communicates the essential purpose efficiently.

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

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

The description covers the core purpose and constraints but leaves pagination behavior and output details to the schema. Given the existence of an output schema and thorough parameter descriptions, the description is minimally viable but not rich. It fails to mention that the cursor should be used for subsequent pages.

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 all parameters (page, cursor, per_page) are already documented. The description adds 'newest' and 'public' context, which help interpret ordering but not parameter semantics. Baseline of 3 is appropriate because the description does not add much 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 identifies the verb ('Get'), resource ('public videos'), and scope ('newest'), which distinguishes it from sibling tools like get_trending or get_user. The term 'sample' introduces slight ambiguity about whether it's a random subset or a paginated page, but the overall meaning is clear.

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 this tool is for retrieving the newest public videos, but it provides no explicit guidance on when to choose this over alternatives like get_trending or search_content. It does not mention exclusions or alternative 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?

With no annotations, the description carries the transparency burden. It discloses a hard limit of 20 and the ordering by engagement, but does not mention pagination behavior, cursor semantics, or whether the operation is read-only. Since 'get' implies a read, it is not misleading, but it lacks richer behavioral context.

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

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

The description is a single, front-loaded sentence that conveys the essential purpose and constraints with zero filler. Every word adds value: 'trending', 'by engagement', 'time window', and 'max 20'.

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 adequate for a simple getter with an output schema, but it omits usage guidance (e.g., when to prefer this over search_content) and any mention of pagination behavior despite the presence of page/cursor parameters. It captures the core purpose but leaves some operational gaps.

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

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

Schema coverage is 75%, and the description adds meaningful context: 'by engagement' clarifies the ordering, 'time window' maps to the window parameter, and 'max 20' reinforces the per_page maximum. It does not elaborate on page or cursor, but those are adequately described in the schema and are self-explanatory.

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 ('Get'), the resource ('trending tik-tok.porn videos'), and key scope ('by engagement for a time window', 'max 20'). It distinguishes itself from siblings like get_feed, search_content, and list_tags by defining trending by engagement.

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 primary use case: retrieving a short list of trending videos within a specific time window. It provides clear context (engagement-based, max 20 results) but does not explicitly mention alternatives or exclusions relative to sibling tools such as search_content or get_feed.

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 transparency burden. It only states that it fetches public data, but does not disclose potential behaviors like error handling for missing usernames, pagination of videos, rate limits, or auth requirements. The description is too thin for full behavioral disclosure.

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

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

The description is a single concise sentence that front-loads the main verb and resource. Every word earns its place with no redundancy or filler.

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

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

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is reasonably complete: it states the action and the high-level return content (profile and videos). However, it could note whether the 'newest videos' are limited in count or paginated, which would add completeness. Still, for a simple read tool, it covers the essential 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 has 100% description coverage for the single 'username' parameter, so the baseline is 3. The description adds no additional parameter semantics beyond the schema, which already clearly states 'Creator username (without @)'.

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 specifies a clear verb ('Fetch') and resource ('a creator's public profile plus their newest videos'). It distinguishes from sibling tools like get_video (which fetches a video) and list_creators (which lists creators), making the tool's unique purpose obvious.

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

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

The description implies usage: when you need a single creator's profile and recent videos, use this tool. However, it does not explicitly state when to prefer alternatives or provide exclusions (e.g., 'for list of creators, use list_creators'). The guideline is implied, not explicit.

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 full burden. It transparently discloses that the tool returns a page_url and no direct media URL, which is a key behavioral trait. It does not mention auth or rate limits, but for a simple fetch this is reasonable.

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

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

The description is a single, concise sentence with a helpful parenthetical. It is front-loaded and contains no unnecessary 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 low complexity (one parameter, no output schema), the description adequately covers purpose, input, and a key output limitation. It might be enhanced by listing the metadata fields returned, but this is not essential.

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 documents the hash parameter. The description only says 'by hash', adding little 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 the tool fetches metadata for a specific video by hash, which is a specific verb+resource. It distinguishes from sibling tools like get_feed and get_trending by targeting a single video identified by hash.

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

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

The description implies usage when you have a video hash, but it does not explicitly compare to alternatives or state when not to use it. The context is clear but exclusionary guidance is absent.

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 must disclose behavioral traits but only mentions 'public' and 'max 20'. It doesn't explain pagination mechanics, result ordering, rate limits, or return structure. This leaves significant behavioral unknowns.

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 wasted words. However, its brevity comes at the cost of critical information, making it efficient but not necessarily appropriate.

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?

No output schema or annotations are present, and the description doesn't specify the return format, pagination details, or ordering. For a list tool with 3 parameters and sibling tools, this is insufficient 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 schema covers page and cursor descriptions, but per_page has no description. The description's 'max 20' simply repeats the schema's per_page maximum, adding no new meaning. No additional detail on parameter usage is provided.

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 it browses the public creator directory, using a specific verb and resource. It distinguishes from sibling tools like get_user and search_content by focusing on the directory list. However, 'by follower count' is somewhat ambiguous as to whether it sorts or filters.

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

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

No guidance is provided on when to use this tool versus alternatives like search_content or get_user. The description gives context but no exclusions or explicit 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?

With no annotations, the description discloses key behaviors: results are ordered by video count and limited to a maximum of 20. However, it does not mention any additional behavior such as output format, pagination, or potential absence of results.

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 redundant words. It concisely conveys the tool's purpose and key constraints.

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 parameterless list tool, the description provides the essential information: what is listed (hashtag categories), the ordering criterion (video count), and the result limit (20). The lack of an output schema is partially offset by the description's clarity, though the exact response structure remains unspecified.

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

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

There are zero parameters, so the schema fully covers parameter semantics. The description adds context that the list is ordered by video count and capped at 20, but no parameter-specific detail 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 clearly states the tool lists the most popular hashtag categories, specifying the ordering by video count and a max of 20 results. This is distinct from sibling tools like get_feed or get_trending, which focus on content rather than tags.

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 retrieving popular hashtag categories but offers no explicit guidance on when to prefer this over sibling tools like search_content or get_trending. No exclusions or 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?

With no annotations, the description carries the full burden of behavioral disclosure. It states what is searched but does not clarify that the operation is read-only, how results are returned (e.g., mixed list, pagination), or any authentication/rate-limit requirements. This is a minimal behavior outline.

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, well-structured sentence with no filler. It front-loads the action ('Search') and the resource, and every word contributes meaning.

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 simple (1 parameter, no output schema), and the description covers the core functionality. However, it lacks details about the response format and boundaries of the search (e.g., result structure, limits), which leaves some ambiguity for an agent invoking it. Still, it is minimally complete for basic use.

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

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

The schema fully describes the only parameter 'q' as 'Search query' (100% coverage). The description adds no additional semantic detail beyond the schema, such as query formats, supported operators, or whether the search is language-sensitive. 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 uses the specific verb 'Search' and names the resource (tik-tok.porn) and the content types (videos, hashtags, creators) with a clear scope ('by keyword'). This clearly distinguishes it from sibling tools like get_video or list_tags, making its purpose unambiguous.

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

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

Usage context is implied: use this when you have a keyword and want to find videos, hashtags, or creators. However, it provides no explicit guidance on when to prefer this over alternatives, nor does it mention any exclusions (e.g., for direct video lookup use get_video).

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