nuditok

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

With no annotations provided, the description carries the full burden of disclosing behavior. It adds useful context that the feed is a sample, is limited to public videos, and is ordered by newest. However, it does not disclose pagination behavior, defaults, authentication needs, or what happens when cursor vs. page is used.

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. Every word earns its place: action, resource, ordering, visibility, and limit are all conveyed 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 tool is simple and has an output schema, so return values need not be explained. Still, the description leaves gaps around pagination defaults, whether page and cursor are alternative mechanisms, and what 'sample' precisely means for the result set, which an agent would need to infer.

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 baseline is 3. The description adds no parameter-specific meaning beyond repeating the 'max 20' constraint already present in the per_page schema; page and cursor semantics come entirely from 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 ('Get'), a specific resource ('newest public NudiTok videos'), and a key constraint ('max 20'). This distinguishes it from siblings like get_trending, get_user, get_video, and search_content without ambiguity.

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

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

The description implies when to use the tool: when you need the newest public videos rather than trending, user-specific, or search-driven results. However, it does not explicitly name alternatives or state when not to use this tool, leaving usage guidance mostly implicit.

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 carry the behavioral burden. It conveys a read-only intent, the trending-by-engagement ordering idea, and a limit of 20, but it does not explain page/cursor interplay, direction of engagement ordering, or default behavior. This is minimal but not wholly uninformative.

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 no filler; the core resource, selection criterion, and limit are all stated directly. The most important decision-facing information 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?

The output schema covers return shape and most parameters are documented, so basic invocation is possible. However, the description omits practical context such as how pagination parameters interact, what happens when no params are provided, and when to prefer a sibling tool, leaving the agent to infer.

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 already documents page, cursor, and window, and the description adds only the 'max 20' cap tied to per_page. At 75% schema coverage, the description does not need to compensate heavily, and it provides marginal additional meaning.

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 trending NudiTok videos by engagement', and adds a time-window constraint and a cap of 20. This clearly separates it from siblings like get_feed, get_user, and search_content.

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 about when to use this tool versus the six sibling tools. An agent must infer that 'trending by engagement' is the selection criterion, but no when-to-use or when-not-to-use context is 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?

With no annotations, the description carries the full burden. It usefully discloses that the profile is public and that videos are the newest, which implies a read-only operation, but it does not mention limits, pagination, ordering details, or error 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?

One concise sentence that front-loads the action and outcome with no filler or redundant details. 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?

For a one-parameter read-only tool, the description adequately states both input intent and returned content despite lacking an output schema. Minor gaps like exact response fields or video count limits prevent a perfect score.

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 only parameter, username, is already described as 'Creator username (without @)'. The tool description adds the NudiTok context but no additional parameter-level semantics, 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 uses a specific verb ('Fetch') and names the resource ('NudiTok creator's public profile') as well as the returned content ('newest videos'). It clearly distinguishes this tool from siblings like get_video or list_creators even without reading their 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?

Usage is implied: use this when you need a creator's public profile and their recent videos. However, the description does not explicitly mention alternatives or situations when another tool should be preferred, so guidance is indirect rather than 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 supplied, the description carries the behavioral burden. It meaningfully discloses the important output behavior: it returns a page_url link, not a direct media URL, which prevents the agent from expecting media content. It does not mention errors, auth, or rate limits, but those are less critical for a simple metadata fetch.

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

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

Two short sentences with no filler. The first sentence states the purpose, and the second adds the essential output caveat about page_url versus direct media URL. Every word 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?

The input side is fully covered by one documented required parameter. There is no output schema, but the description partially fills that gap by naming the key return value, page_url. It could describe the metadata fields or page_url format more explicitly, but nothing needed to invoke the tool 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?

The input schema already documents `hash` as 'Video hash (8+ hex chars)' with 100% coverage, and the description only repeats 'by hash.' The description adds no new meaning beyond what the schema already provides, so the baseline score 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 ('Fetch metadata'), a concrete resource ('one NudiTok video'), and the lookup key ('by hash'). This clearly distinguishes it from sibling list/search tools such as get_feed, get_trending, and search_content.

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 phrase 'for one NudiTok video by hash' clearly establishes the condition for use: when the agent has a video hash and needs that video's metadata. It does not explicitly contrast with sibling tools, but the single-video-by-hash context is clear and effectively excludes list or search use cases.

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

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

With no annotations, the description carries the behavioral burden. It discloses that the data is 'public' and that results are sorted by follower count with a 'max 20' cap, which suggests a read-only directory operation. However, it does not mention pagination behavior, whether the operation requires authentication, or what fields are returned.

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 single sentence is compact, front-loaded with the core purpose, and avoids wordiness. It earns its place by conveying resource, scope, ordering, and a limit, though it leaves behavioral details absent.

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 list tool with three parameters and no output schema, the description is too sparse. It omits guidance on cursor usage, per_page semantics, response shape, and how the tool differs from search_content — all of which an agent would need to 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?

Schema coverage is 67%, with page and cursor documented in the schema. The description adds context by indicating follower-count ordering and a max of 20 results, which aligns with per_page's maximum. It does not add meaningful detail about how page, cursor, or per_page interact.

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

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

The description states a clear verb ('Browse'), a specific resource ('the public NudiTok creator directory'), and an ordering criterion ('by follower count'). It distinguishes this from the sibling tools by identifying the resource as a directory of creators, though it does not explicitly contrast it with search_content or get_user.

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 about when to use this tool versus alternatives such as search_content or get_user. The description implies a browsing use case but does not state exclusions, preferred scenarios, or relationships to sibling tools.

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

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

With no annotations, the description carries the full burden. It does disclose meaningful behavior: results are sorted by video count and capped at 20. However, it does not state whether authentication is required, whether the result is just category names or includes counts, or whether any pagination mechanism exists. For a simple list tool this is acceptable but not rich.

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

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

A single, front-loaded sentence communicates the resource, the ordering, and the limit with no filler. Every word adds value.

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 without an output schema, the description covers the essential behavior: what is listed, how it is ordered, and the maximum result count. The only minor gap is a precise statement of the returned format, but this does not critically hinder an agent from invoking 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, and schema description coverage is effectively 100%. The description adds useful context by clarifying the result ordering and cap, which is all that needs to be conveyed for a parameterless tool.

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 ('List'), resource ('NudiTok hashtag categories'), and the ordering criterion ('by video count'). It also specifies a concrete limit ('max 20'), making it easy for an agent to distinguish this from siblings like search_content or get_trending.

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 guidance on when to use this tool versus alternatives such as search_content or get_trending. There is no mention of use cases, exclusions, or conditions that would favor this tool over its siblings.

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 full burden of behavioral disclosure. It states that the tool performs a keyword search, but says nothing about result format, ordering, pagination, limits, no-result behavior, authentication, or whether results are grouped by content type. This is a meaningful gap for a search tool with no output schema.

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 clear, front-loaded sentence with no filler. Every word contributes to the core purpose, and it names the target content types compactly.

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 tool, the description is close to sufficient, but there is no output schema and no annotations to compensate for missing return-value or result-behavior details. The description explains what is searched but not what the caller receives, which is a clear gap.

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 already documents q as 'Search query'. The tool description adds that the query is a keyword matched against videos, hashtags, and creators, which is mild enrichment but does not provide additional syntax or formatting details. The high schema coverage supports the baseline score of 3.

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

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

The description uses a specific verb ('Search'), names the platform ('NudiTok'), and enumerates the content types covered ('videos, hashtags, and creators') with a clear keyword mechanism. This distinguishes it well from sibling tools like get_feed, list_creators, and get_video, which imply direct retrieval or listing rather than keyword 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?

Usage is implied: an agent can infer this tool is for keyword search across content types, while siblings like get_video or list_tags handle direct retrieval or listing. However, there is no explicit when-to-use/when-not-to-use guidance or mention of alternatives, so the agent must rely on naming conventions and inference.

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