desaira

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

With no annotations, the description carries the disclosure burden. It discloses that the feed is a sample, is limited to newest public adult videos, and caps at 20 items, but it does not explain pagination behavior, stability of ordering, or whether any authentication 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?

A single sentence conveys the action, resource, scope, and limit without any filler. The key constraint is front-loaded, making it easy for an agent to parse quickly.

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 feed-reader with full schema coverage and an output schema, the description is mostly sufficient. It lacks explicit usage guidance and deeper behavioral notes, but it covers the essential purpose, scope, and size limit.

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 page, cursor, and per_page. The description adds only the 'max 20' context already present in the schema, providing no additional parameter-level 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 uses a specific verb and resource: 'Get a sample of the newest public adult videos on DesAira.' It clearly distinguishes the tool from siblings like get_trending, get_user, and search_content by scoping it to newest public videos with a max of 20.

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 for accessing a latest-videos feed, but it does not explicitly say when to use it instead of get_trending or search_content. No exclusions or alternative routing guidance is provided, leaving usage context 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 carries the responsibility of disclosing behavior. It notes that results are capped at 20 and ranked by engagement within a time window, which is useful. However, it does not clarify pagination semantics or whether the cap is total or per page.

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. It states the action, resource, ordering, time-window scope, and result cap 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?

For a read-style tool with four optional parameters and an output schema, the description plus schema gives a workable picture. It omits explicit pagination guidance and sibling-tool routing, but those are largely inferable from the schema and tool name.

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 75% (page, cursor, and window are documented), so the schema already carries most parameter meaning. The description only paraphrases the window and max-20 limit, adding no new parameter-specific semantics; 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 ('Get'), a clear resource ('trending adult videos on DesAira'), a ranking criterion ('by engagement'), and a time-window qualifier. This clearly distinguishes it from siblings like get_feed, get_video, 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 description conveys a clear use case: retrieve engagement-ranked trending videos for a selected time window. It does not explicitly mention alternatives or when not to use it, but the context is specific enough for an agent to select it for trending-content queries.

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. It discloses that the profile is public (implying no auth needed) and that it returns the newest videos. However, it doesn't mention behavior for nonexistent usernames, rate limits, or the exact structure of the response, leaving some gaps.

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

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

The description is a single, front-loaded sentence with no wasted words. It immediately states the action and the target resource, making it easy to scan and understand.

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 (one parameter, no output schema). The description conveys the core functionality and the public nature of the data. However, it doesn't specify how many 'newest videos' are returned or any other return details, which could be important for an agent. Still, it is sufficiently complete for a basic read 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 input schema already fully documents the 'username' parameter with the note '(without @)'. The description adds no additional semantics beyond what the schema provides, so a 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 uses the specific verb 'Fetch' and clearly identifies the resource as 'a DesAira creator's public profile plus their newest videos.' This distinguishes it from sibling tools like get_video (single video), list_creators (listing creators), and get_feed (feed of 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 description clearly implies when to use this tool: when you need a specific creator's profile and videos by username. It differentiates from list_creators and search_content by focusing on a single creator, but it lacks explicit exclusions or 'use X instead' 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?

With no annotations, the description carries the burden of disclosing behavior. It does disclose a key trait: it returns page_url and explicitly states there is no direct media URL. However, it does not mention what happens for invalid hashes, error responses, or any other side effects, leaving some behavioral uncertainty.

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 core purpose and the most important caveat. Every word earns its place, with 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 one-parameter metadata lookup, the description covers the essential context: what it returns (metadata), how to identify the video (hash), and a critical limitation (no direct media URL). It does not enumerate all metadata fields, but since there is no output schema, a bit more detail could be offered; however, the description is still adequate for basic usage.

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

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

The schema fully documents the hash parameter with a description ('Video hash (8+ hex chars)'), and the description merely repeats 'by hash' without adding new meaning. Since schema coverage is 100%, the baseline of 3 applies; the description adds no extra semantic value.

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 identifies the exact resource ('metadata for one DesAira video') keyed by hash. This clearly distinguishes it from sibling tools like get_feed or get_trending, which operate on collections rather than individual videos.

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 a hash is available (e.g., 'by hash'), but it does not explicitly state when to prefer this over alternatives or when not to use it. It provides no comparison to sibling tools or exclusion criteria, leaving the usage context 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 provided, the description carries the transparency burden but only partially. It adds useful details: 'public' (no auth), 'by follower count' (ordering), and 'max 20' (result cap). However, it does not disclose sort direction, pagination continuation semantics, response format, or rate limit behavior.

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

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

The description is a single, focused sentence that front-loads the tool's purpose and constraints with no filler. Every phrase adds value: 'public', 'by follower count', 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 tool has moderate complexity (pagination via page/cursor/per_page) and no output schema, so the description should ideally clarify the return shape or pagination behavior. It states the core purpose and constraints but omits what the response contains and how to continue pagination beyond the schema's cursor description. This is a clear gap for no-output-schema 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 descriptions cover page and cursor (67% coverage), leaving per_page undocumented. The description adds context that results are ordered by follower count and capped at 20, which helps interpret per_page. It does not deeply explain parameter interactions like how cursor relates to page, but the schema already provides baseline descriptions.

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's action and resource: 'Browse the public DesAira creator directory by follower count (max 20).' The verb 'browse' plus the specific resource and ordering distinguishes it from sibling tools like get_user (single user), get_feed, 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 description implies the intended context—browsing a public creator directory ordered by followers—but does not explicitly state when to use this tool over alternatives or when not to use it. No alternatives or exclusions are mentioned, so it stops at implied usage rather than clear 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?

No annotations are provided, so the description carries the full burden. It usefully discloses the ordering basis and result cap, but it does not explicitly state that this is a read-only operation, whether counts are included in the response, or whether pagination exists. For a simple list tool this is acceptable but not thorough.

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 immediately states the resource and the ranking criterion. Every word contributes meaning, with no filler or repetition of the tool name.

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

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

Given that this is a zero-parameter, simple list tool with no annotations and no output schema, the description covers the essential invocation details: what is listed, the ordering, and the maximum result count. It does not describe the response shape, but that is a minor omission for this level of complexity.

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, so the baseline of 4 applies. The description's reference to 'max 20' is an output constraint, not a parameter, and there is nothing else for parameter semantics to add beyond the empty 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 uses a specific verb ('List') and a specific resource ('adult hashtag categories on DesAira') with clear qualifying criteria ('by video count', 'max 20'). It is self-evidently distinct from sibling tools like get_feed, get_user, or search_content because it targets hashtag categories.

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 the agent needs the most popular adult hashtag categories ranked by video count. However, it does not explicitly address alternatives or say when not to use it, such as when broader content discovery or search is more appropriate.

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 burden of explaining behavior. It accurately conveys that this is a keyword search across NSFW content, which is useful context. However, it does not disclose result ordering, pagination, content-filtering, or whether results are grouped by type, leaving some behavioral ambiguity.

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 phrase contributes to the agent's understanding of the tool's scope and query semantics.

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 one-parameter search tool with no output schema, the description is adequately complete: it identifies the platform, the keyword-based nature, and the three content categories searched. It could specify whether results are combined or separate, but this is not critical for initial invocation.

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%, as the q parameter is described as 'Search query'. The description adds the term 'by keyword', which slightly clarifies q as a keyword string, but this is largely redundant with the schema. 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 states a specific action ('Search'), a specific platform ('DesAira'), and specific result types ('adult videos, hashtags and creators'). It clearly distinguishes from siblings like get_feed and list_creators by indicating keyword-based search across multiple content types.

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 use for keyword-driven discovery across videos, hashtags, and creators, which differentiates it from browsing or direct retrieval tools. However, it does not explicitly state when to prefer this tool over siblings like list_creators or list_tags, nor does it mention any exclusions.

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