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

Describes return fields but does not mention any behavioral aspects like authentication, rate limits, or whether it's read-only. With no annotations, more behavioral detail would be beneficial.

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 concise sentences, no waste. First sentence states function and output, second gives usage guidance.

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 no output schema, the description adequately lists return fields. For a simple info retrieval tool, it provides sufficient context for selection.

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 schema adequately documents parameters. The description adds no significant 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?

Clearly states the tool retrieves detailed information for an Amazon product by ASIN, lists specific return fields, and distinguishes from sibling tools like search_amazon and get_walmart_product.

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 states when to use: when user has a specific URL or ASIN. Lacks explicit when-not-to-use or alternatives, but context is clear enough.

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 full burden. It discloses speed (5-15 seconds), comment structure (flat array, reconstruct hierarchy via depth/parentId), and contentUrl for link posts. Lacks info on auth or rate limits, but otherwise 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 concise (three sentences), front-loaded with the main purpose, then provides essential details. No wasted 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 no output schema, the description covers returned fields (body, score, etc.), comment structure, and contentUrl. Single parameter is fully explained. Complete for a tool of this 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?

Only one parameter ('url') with 100% schema description coverage. The description adds no extra meaning beyond the example URL format provided in 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 clearly states it gets a full Reddit post as JSON with specific included fields ('body, score, upvote ratio, flair, awards, and full comment tree'). It distinguishes from siblings like search_reddit (which searches) and other get_* tools for different platforms.

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 when you need a full Reddit post's data by URL. It mentions slower performance (5-15 seconds) setting expectations. However, it does not explicitly state when not to use or mention 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?

No annotations are provided, so the description carries the full burden. It explains the return format (JSON with each reply same structure as a comment) and pagination behavior. However, it does not disclose potential issues like rate limits, authentication requirements, or error handling. The description is adequate but not comprehensive.

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 three sentences: the first states the purpose, the second adds context about reply structure, and the third provides pagination instructions. Every sentence adds value, and the description is front-loaded with the core function. No wasted 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?

With four parameters and no output schema, the description covers the core functionality and pagination. It assumes knowledge of comment structure from a sibling tool, which is reasonable. Missing details like error handling or rate limits lower the score slightly, but it is largely complete for an API 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 covers all four parameters with descriptions. The description adds context about the relationship between comment_id and get_tiktok_video_comments response, and pagination cursor usage. Since schema coverage is 100%, the description provides marginal additional meaning, warranting a 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 specifies 'Get replies to a specific comment on a TikTok video as JSON.' This clearly identifies the action (get), resource (replies to a specific comment), and output format (JSON). It distinguishes itself from sibling tools like get_tiktok_video_comments, which retrieves top-level 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?

The description states that both video_id and comment_id are required, and provides pagination guidance: 'Use data.cursor for next page; stop when data.has_more is 0.' This tells the agent when and how to use the tool effectively. However, it does not explicitly mention when not to use it or provide 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?

No annotations provided, so the description carries full burden. It discloses the output format (JSON) and the fields returned. The parameter constraint (provide either hashtag_name or hashtag_id) is stated. It implies read-only operation. No rate limit or auth info, but for a simple read tool this is acceptable.

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 very concise: two sentences. The first sentence states the purpose and return format, the second explains parameter usage and connection to a sibling tool. No wasted words, front-loaded with key 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?

For a tool with no output schema, the description adequately explains the return values (ID, title, description, video count, view count). The parameters are well-documented in both schema and description. The sibling tool connection is explicitly mentioned, providing complete context for an agent to use this tool effectively.

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% with clear parameter descriptions (e.g., 'Hashtag text without the # symbol'). The description restates the mutual exclusivity and adds a minor clarification ('hashtag_id: Numeric'). But overall, the schema already does the heavy lifting, so the description adds limited semantic value beyond what's in 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 verb 'Get', the resource 'TikTok hashtag details and stats', and lists the returned fields (ID, title, description, video count, view count). It distinguishes from sibling tools by mentioning the returned ID can be used with get_tiktok_hashtag_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 indicates when to use (need hashtag details) and the parameter choices (either name or ID). It also provides a clear next step: use the returned ID with a sibling tool. However, it doesn't explicitly state when not to use or discuss alternatives beyond that one sibling.

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 provided, so description carries full burden. It discloses pagination behavior and output format but does not mention rate limits, authentication, or data freshness. Adequate for a read-only tool but could be more 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?

Two sentences with no filler. First sentence states purpose and output, second explains pagination. Front-loaded and efficient.

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?

Despite no output schema, the description covers return fields and pagination. Complete for a listing tool with clear input and usage instructions.

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%, baseline 3. Description adds value by explaining hashtag_id's source, cursor usage for pagination, and count range, going beyond 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 it lists TikTok videos for a given hashtag, specifying included fields (ID, caption, author, stats, video URLs). It distinguishes from siblings like get_tiktok_video (single video) and search_tiktok_videos (search-based).

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 tells when to use it (given hashtag_id from get_tiktok_hashtag) and explains pagination using cursor and has_more. It could explicitly state when not to use, but the context is sufficient.

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 must cover behavior. It describes the output (JSON with specific fields) and implies a read operation. However, it does not mention potential constraints like public profile requirements, rate limits, or error handling, leaving room for improvement.

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 concise (two sentences) and front-loaded, stating the function first then usage. Every sentence adds value with no 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 simple retrieval tool with no output schema, the description adequately covers purpose, input requirements, and output fields. It is complete enough for an agent to select and invoke 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 100% with detailed descriptions for both parameters. The tool description adds the context that either parameter can be provided, which is helpful but not a significant addition 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 retrieves a TikTok user's profile as JSON and lists the returned fields, distinguishing it from sibling tools that handle followers, followings, posts, or 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 specifies when to use the tool ('when user wants info about a TikTok account') and provides the requirement to provide either username or sec_user_id. It does not explicitly exclude other scenarios, but the sibling names make the distinction clear.

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 present; description covers pagination behavior and return fields but does not explicitly state that the operation is read-only or mention authentication requirements.

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 sentences, front-loaded with purpose, no redundancy, every sentence 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?

Lists follower fields but does not describe overall response structure beyond mentioning data.has_more; adequate for a simple list retrieval 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 covers all parameters; description adds context beyond schema by linking sec_user_id to get_tiktok_profile and explaining pagination token usage.

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?

Clearly states the tool retrieves a TikTok user's follower list as JSON and lists the fields included, distinguishing it from siblings like get_tiktok_user_followings.

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?

Provides explicit pagination instructions (page_token and min_time) and a stopping condition, but does not contrast with siblings or specify when to choose followers over followings.

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 provided, so the description carries the full burden. It discloses pagination behavior and required parameters (sec_user_id from get_tiktok_profile). It does not mention rate limits or authentication, but for a straightforward read operation, this is acceptable and no contradictions exist.

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 sentences with zero waste: first sentence states purpose and output structure, second provides pagination guidance. 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?

No output schema exists, so the description must explain return values. It lists the fields per entry and describes the pagination termination condition (has_more false). For a list tool, this is complete and actionable.

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 description adds significant context beyond the schema: it explains that page_token and min_time must be passed together from previous response, and that sec_user_id comes from get_tiktok_profile. This helps the agent use parameters correctly.

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 'list of accounts a TikTok user follows', and specifies the output format 'as JSON'. It also lists the fields included, distinguishing it from siblings like get_tiktok_user_followers which returns followers in the opposite direction.

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 explicit pagination instructions: 'Pass both page_token and min_time from previous response for pagination; stop when data.has_more is false.' It does not explicitly state when not to use or compare to alternatives, but the pagination guidance is clear and sufficient for correct usage.

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 full burden. It discloses output fields (ID, caption, timestamp, stats), pagination behavior (cursor, has_more), and a dependency (profile endpoint). It does not cover rate limits or error handling, but for a read-oriented tool, this 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?

Two sentences, front-loaded with the core purpose and output format, followed by essential usage context. Every sentence is valuable and there is no 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?

Given 4 parameters, no output schema, and no annotations, the description explains the prerequisite, pagination pattern, and output fields. It does not cover sort_type enum values (schema does) or all edge cases, but it is complete enough for typical 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?

Schema coverage is 100%, so the baseline is 3. The description repeats some schema info (e.g., 'requires sec_user_id') but adds pagination context. It does not add new parameter-specific meaning beyond the schema 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 explicitly states 'List a TikTok user's videos with pagination as JSON', providing a specific verb and resource. It distinguishes from siblings like get_tiktok_profile (profile info) and get_tiktok_video (single video) by focusing on listing multiple posts with pagination.

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 explains the prerequisite ('Requires sec_user_id from the profile endpoint') and gives explicit pagination instructions ('Use data.max_cursor for next page; stop when data.has_more is 0'). It does not compare to alternatives like search_tiktok_videos but provides sufficient guidance for proper usage.

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 describes the return format (JSON with specific fields) but does not disclose behavioral traits such as authentication requirements, rate limits, error handling, or whether the request is destructive. The description adds some value but lacks transparency on these important aspects.

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 very concise, consisting of two short sentences. The first sentence front-loads the core purpose and output format. Every word adds value, 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 simplicity (single required parameter, no output schema, no nested objects), the description is largely complete. It provides enough detail for an AI agent to use it correctly. However, it could mention potential error cases (e.g., invalid ID) or rate limits, but these are not critical for a basic retrieval 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 covers the single parameter with a description explaining to extract the video ID from a URL. The tool description reinforces this by mentioning 'URL or ID'. Since schema coverage is 100%, the description provides additional context on how to derive the ID, going beyond the schema's basic definition.

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 retrieves detailed info for a single TikTok video by ID as JSON. It lists the specific data returned (caption, author, music, stats, URLs, etc.), distinguishing it from sibling tools that handle other entities like hashtags, profiles, or 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?

The description explicitly states when to use the tool: 'Use when the user has a specific TikTok video URL or ID.' This provides clear context. However, it does not mention when not to use it or suggest alternative tools for searches or multiple videos, which are available as 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?

Discloses pagination behavior and output structure, but does not mention potential errors, rate limits, or authentication requirements.

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 concise sentences: first for purpose and output, second for pagination. No wasted 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?

Covers output fields and pagination well, but lacks mention of prerequisites (e.g., video must be public) or error handling.

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 has 100% coverage, but description adds pagination usage hints (cursor, has_more) beyond schema 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?

Clearly states it gets comments on a TikTok video, with specific output fields listed. Distinguishes from siblings like get_tiktok_comment_replies and get_tiktok_video.

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?

Provides explicit pagination instructions but lacks guidance on when to use this tool versus alternatives like get_tiktok_comment_replies.

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 full responsibility. It indicates a read operation ('Get...') but does not disclose authentication requirements, side effects, or rate limits. The description is adequate for a simple retrieval but lacks depth.

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 sentences with zero waste. The first sentence states the outputs, the second gives usage context. 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?

Given the tool has no parameters, no output schema, and no annotations, the description is mostly complete. It could mention authentication or that data is for the current user, but it already implies 'current user's'. Slight lack of behavioral depth prevents a 5.

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 no parameters, so the baseline is 4. The description adds no parameter-level detail, but none is needed. The schema already covers 100% of parameters (none).

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 exactly what the tool retrieves: credit balance, plan, searches used this month, and auto-recharge settings. It clearly distinguishes from sibling tools, which are all external platform queries.

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 explicitly states when to use the tool: when the user asks about credits, plan, or usage. While it doesn't mention alternatives or when not to use it, the context is clear and the sibling tools are unrelated.

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 description bears full transparency burden. It discloses that the tool returns title, description, price, rating, images, and seller info, which is helpful. However, it doesn't mention potential error on invalid ID, rate limits, or auth requirements. For a simple read operation, this is sufficient.

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 sentences, no redundant fluff. The first sentence states the purpose and return fields, the second gives usage guidance. Every sentence 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 single-parameter tool with no output schema, the description adequately covers input and output expectations by listing returned fields. It could mention error handling (e.g., invalid ID) or that images require a separate call, but overall it's reasonably complete given the 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?

Schema coverage is 100% and the schema already describes the product_id parameter as a numeric string from the URL. The description adds no additional meaning beyond the schema, so 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?

Description clearly states action (get detailed information), resource (Walmart product by product ID), and lists specific return fields (title, description, price, rating, images, seller info). It distinguishes from siblings like search_walmart (searching) and get_amazon_product (different retailer).

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 says when to use: 'when the user has a specific Walmart product URL or product ID and wants full details.' This provides clear context for appropriate invocation, though it doesn't explicitly state when not to use or mention 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?

No annotations provided, but description clearly indicates read-only metadata retrieval with no destructive or side effects. Sufficiently transparent for a simple read operation.

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 sentences, no wasted words. Front-loaded with action and parameter, then lists returned fields.

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 one param and no output schema, description fully explains purpose, input, and output. No 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?

Single parameter video_id is well-described with example and extraction hint from URLs. Schema coverage is 100%, and description adds value with usage context.

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?

Clearly states the tool gets metadata for a YouTube video by ID, listing specific fields returned. Distinct from sibling tools like search_youtube.

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 says when to use: 'when the user has a specific video ID or URL and wants details.' Implicitly excludes search scenarios, but no direct mention of 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?

No annotations are provided, so the description must disclose behavioral traits. It mentions returning JSON but does not address side effects, authentication needs, rate limits, or data freshness. The read-only nature is implied but not explicit.

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 sentences with no wasted words. The first sentence front-loads purpose and output; the second provides usage guidance. Highly concise and structured.

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 explains return fields but lacks details on pagination (start_page), sort behavior, domain handling, or error scenarios. For a search tool with 6 parameters and no output schema, more completeness is needed, but the basics are covered.

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 description adds no additional parameter semantics beyond what the schema already provides. 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 clearly states the action 'Search Amazon', the resource 'Amazon', and the output format 'JSON' with specific fields. It distinguishes from sibling tools like search_google and search_walmart by specifying Amazon and product listings.

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 explicitly says 'Use when the user wants to find products on Amazon or compare prices,' providing clear usage context. It does not mention when not to use or list alternatives, but the context is sufficient for selection among 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?

Discloses return format (JSON with title, URL, snippet), additional result types depending on search type, and credit cost (light vs full). No annotations provided, but description covers key behavioral aspects without contradictions.

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?

Three concise sentences, front-loaded with purpose, then output details, then usage guidance. Every sentence adds value, no wasted 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?

Complete for a search tool: covers what it does, output structure, parameter semantics (via schema), usage context, and cost. No output schema, but description adequately describes returned data.

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 has 100% coverage, but description adds context on credit cost for light_request and explains result types (top stories, knowledge graph) that depend on search_type, adding value beyond schema 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 explicitly states 'Search Google' and mentions returning structured results as JSON, clearly distinguishing it from sibling tools that search specific platforms like Amazon or Reddit.

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?

Provides clear guidance: 'Use when the user asks to search the web, find current information, or look something up online.' Does not explicitly list exclusions, but the sibling context implies when not to use.

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 full burden. It discloses that results are returned as JSON with specific fields, mentions pagination behavior (cursor-based), and notes slowness. It does not mention rate limits, authentication, or error handling, but for a search tool of this type, the disclosed behaviors are sufficient.

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 three sentences, front-loaded with purpose, includes key output details and pagination instructions. No superfluous information. Every sentence 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 tool has 3 parameters, no output schema. The description covers the output format (fields), pagination mechanism, and performance caveat. It lacks error scenarios or authentication requirements, but given the tool's simplicity, it is reasonably complete.

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 baseline is 3. The description adds the detail that cursor comes from 'data.nextCursor' and that stop condition is null, which is already in the schema's cursor description. It also describes output fields, not input parameters. Therefore, minimal added value beyond 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 verb 'Search' and the resource 'Reddit posts across all of Reddit' with output format 'as JSON'. It lists included fields (title, URL, subreddit, author, timestamp, NSFW flag), distinguishing it from siblings like search_google or search_amazon which have different scopes.

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 explains pagination: 'Use data.nextCursor as the cursor parameter for the next page; stop when nextCursor is null.' It also notes that the tool is 'Slower than other platforms (5-15 seconds)', which sets expectations. However, it does not explicitly state when to prefer this tool over alternatives or any exclusions.

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 discloses the output structure (JSON with specific fields) and pagination behavior (using data.cursor and data.has_more), which are important behavioral traits. It does not cover error conditions or rate limits, but the pagination detail adds significant value beyond the 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 extremely concise at two sentences, front-loading the main action and result format. Every sentence serves a purpose: stating the action and output, and providing pagination instructions. No wasted 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?

With no output schema, the description compensates by listing output fields and explaining pagination. The schema covers parameters well. It lacks error handling or fallback behavior, but for a search tool with siblings covering other platforms and TikTok-specific queries, the description is reasonably complete.

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% with descriptions for all three parameters. The description adds value by explaining how to use the cursor parameter for pagination, but does not add meaning for keyword or count beyond what the schema provides. Baseline 3 is appropriate given high schema coverage and the additional cursor context.

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 'Search' and the resource 'TikTok users', specifies the output format (JSON) and key fields included in each result. This distinguishes it from sibling tools like search_tiktok_videos which search videos, making the 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?

The description provides clear context for using the tool (searching users by keyword) and includes pagination instructions, but does not explicitly advise when not to use it or mention alternative tools. However, sibling tool names like get_tiktok_profile and search_tiktok_videos make the differentiation fairly obvious.

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?

Discloses pagination behavior (cursor, has_more), sorting/filtering support, and that output is JSON with specific fields. No annotations present; description carries burden well. Lacks mention of authentication or rate limits, but these are common for search tools.

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?

Three sentences, front-loaded with purpose, then core features, then pagination detail. Highly efficient, no redundant 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?

Covers key behaviors: output format, result fields, sorting, filtering, pagination. Lacks error handling or rate limit info, but for a search tool with no output schema, it 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?

All 5 parameters have descriptions in schema (100% coverage). Description adds value by explaining pagination flow ('Use data.cursor...') and summarizing result contents beyond schema. Baseline 3, plus extra informativeness.

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?

Description clearly states verb 'Search', resource 'TikTok videos', and specifies output format 'as JSON' with result fields. Distinguishes from siblings like 'get_tiktok_video' (single video) and 'search_tiktok_users' (users).

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?

Provides clear context for when to use (searching videos by keyword) and pagination instructions, but does not explicitly mention when not to use or compare to alternative sibling tools like 'get_tiktok_hashtag_videos'.

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?

Describes return format (JSON with specific fields) and implies read-only behavior. No annotations provided, so description carries the burden. Could mention pagination or result limits, but overall 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?

Two concise sentences front-loaded with purpose and usage. No unnecessary 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?

Covers core functionality and usage context. With 5 parameters and no output schema, could benefit from a brief note on sorting/filtering, but still complete for its 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?

Schema description coverage is 100%, so parameters are well-documented in the schema. Description does not add additional meaning beyond the schema, which is acceptable per 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?

Clearly states the action 'Search Walmart' and resource 'product listings as JSON'. Distinguishes from sibling tools like search_amazon by mentioning price comparison with Amazon.

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?

Provides explicit usage: 'Use when the user wants to find products on Walmart or compare prices with Amazon.' This guides the agent on when to invoke this tool versus 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?

No annotations are provided, so the description must carry the burden. It discloses that results include specific fields (video ID, title, channel, etc.), but does not mention any behavioral traits like rate limits, authentication, or error handling. Adequate 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?

Two concise sentences: the first states purpose and output, the second provides usage guidance. No redundant or unnecessary 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?

Given 5 parameters, no output schema, and no annotations, the description is fairly complete. It explains the output format and when to use. However, it implies only video results yet the 'type' parameter allows channels and playlists, which is a slight inconsistency.

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 description does not add significant meaning beyond what the schema already says (e.g., sort_by options, type filter, duration). The description restates output fields but does not clarify parameter nuances further.

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 'Search' and resource 'YouTube', and specifies that it returns JSON with video details (ID, title, channel, etc.). This differentiates it from sibling tools like search_google or search_tiktok_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 includes explicit guidance: 'Use when the user asks to find YouTube videos on a topic.' While it does not mention when not to use or provide alternatives, this is clear enough for an AI agent.

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