xpay✦ Marketing Collection

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

With no annotations, the description carries full responsibility for behavioral disclosure. It only states the basic action and filters, but does not mention return format, pagination, sorting, or side effects. The limit parameter has a default but this is not surfaced in the description.

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, complete sentence that is front-loaded with the core purpose. There is no redundant or filler content; 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 tool is simple with three optional parameters and no output schema. The description states the core function and filter options, but omits details about response structure or behavior when no filters are applied. Given low complexity, this is adequate but has clear gaps.

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

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

Schema description coverage is 100%, so the parameters (limit, network, category) are already well-documented with their own descriptions. The description adds no additional parameter semantics beyond what the schema provides, which meets the baseline but does not exceed it.

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 ('Find') and identifies the resource ('social media hooks') with clear filtering scope ('by network and/or category'). It clearly distinguishes from sibling tools like get-network-categories-for-hooks, which focuses on categories rather than hooks themselves.

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

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

No guidance is provided on when to use this tool versus alternatives, nor any exclusions or prerequisites. The sibling get-network-categories-for-hooks could be a related alternative but is never mentioned. The use case is implied by the description but not explicitly 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 provided, the description carries the full burden of behavioral disclosure. It states that it 'Returns any flagged phrases found in the text,' which informs the user of the output type. However, it does not describe side effects, limitations, or how the detection works, making it only partially 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 two sentences long, front-loaded with the main purpose and followed by a clear statement of what it returns. Every word serves a purpose, and there is no redundant or filler content.

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

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

The tool is simple with one parameter and no output schema. The description explains the input and output behavior sufficiently: check text and return flagged phrases. It does not mention response format details, but for a straightforward utility, this is reasonably complete. It could benefit from an example or more specifics about the flagged phrases, but it is not inadequate.

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%, with the parameter 'text' already described as 'The text to check for problematic phrases.' The tool description adds minimal extra meaning beyond the schema—it reiterates the text input but does not provide examples or additional details like formatting constraints. The 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?

The description clearly states the tool's purpose with a specific verb and resource: 'Check text for phrases that should be avoided to make content more human and less AI-like.' It explicitly mentions the action (checking text) and the goal (avoiding AI-like phrases), which distinguishes it from sibling tools that focus on fetching data or scraping 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 usage context (when editing content to make it more human), but it does not explicitly mention when to use this tool versus alternatives or provide exclusions. No sibling tools are named as alternatives, so the guidance is only 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 full burden. It clearly implies a read-only operation via the verb 'Get' and specifies the content returned (tweet examples). While it doesn't disclose error handling or authentication, for a simple get tool this is sufficient transparency.

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 states the purpose and a key detail (tweet examples). No wasted words, perfectly concise and structured for quick understanding.

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 with one parameter and no output schema. The description sufficiently covers the core functionality and gives a hint about response content ('including tweet examples'). While it doesn't enumerate all response fields, the low complexity makes the description adequate.

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 the 'name' parameter already well-described with examples. The description doesn't add any additional semantic meaning beyond what the schema provides, so it hits the baseline 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 clearly states the action (Get), the resource (specific voice archetype), and adds a key detail (including tweet examples). It distinguishes itself from sibling tools like list-archetypes, which would list all archetypes, and get-copywriting-framework, which targets a different resource.

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

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

The description implies usage for detailed archetype information, but does not explicitly state when to use it over alternatives or mention sibling tools. Since there is a natural contrast with list-archetypes, the usage is somewhat clear but not explicitly guided, warranting a mid-range score.

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 for behavioral disclosure. It only states that information is retrieved, with no mention of return format, potential errors, required permissions, or any operational effects. Minimal behavioral context is provided beyond the basic action.

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

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

The description is a single, front-loaded sentence that conveys the essential purpose without any filler or redundancy. It is efficient and appropriate for a simple retrieval tool.

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 (two parameters, no output schema, no annotations), the description provides a basic level of completeness. However, it does not clarify what 'detailed information' includes or what the return structure looks like, leaving some gaps for an agent deciding whether to invoke this 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 describes both parameters with clear examples, achieving 100% schema description coverage. The description itself adds no additional parameter semantics, 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 clearly states the action ('Get detailed information') and the resource ('a specific copywriting framework'), with a network scope. It is easily distinguished from the sibling tool 'list-copywriting-frameworks' which implies a listing operation vs. a detail lookup.

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 'a specific copywriting framework' implies this tool is for when the user needs details on a single framework, as opposed to a list. However, there is no explicit 'when not to use' or mention of alternatives, leaving some ambiguity compared to the ideal case.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states what the tool does without explaining the meaning of 'supported', return format, or any side effects. The behavior is not transparent beyond the basic action.

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 is concise and appropriately sized for a tool with no parameters and a simple purpose.

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

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

For a zero-parameter, no-output-schema tool, the description is minimally complete, but it omits what 'supported' means and does not indicate the structure of the response (e.g., names, codes). The low complexity raises the tolerance, yet the ambiguity prevents a higher 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?

The tool has zero parameters, so the baseline is 4. The description adds meaning by specifying the resource ('countries') and the qualifier ('supported'), which is useful context even though there are no parameter details to clarify.

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 'Get list of supported countries' uses a specific verb and resource, clearly stating that the tool returns a list of supported countries. It effectively distinguishes itself from siblings like get_currencies by naming the exact resource.

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 list of supported countries is needed, but it provides no explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned, though the simplicity of the tool makes alternatives less critical.

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 present, so the description must carry the full behavioral disclosure burden. It only implies a read-only operation with 'Get' but omits authentication requirements, rate limits, and response format.

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. It communicates the tool's purpose efficiently.

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

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

The description is adequate for a zero-parameter account balance lookup, but the absence of an output schema means return format and balance units are not clarified. More detail on the response structure would improve completeness.

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 schema fully covers parameter semantics. Baseline 4 applies because no parameter documentation is needed.

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

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

The description uses the specific verb 'Get' and the resource 'your account's credit balance,' clearly identifying the tool's function. It distinguishes itself from the many sibling data-retrieval tools by referencing the account credit balance specifically.

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

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

No guidance is provided on when to use this tool versus alternatives, and no exclusions or prerequisites are mentioned. The phrase 'Get your account's credit balance' implies a balance-checking use case, but this is not explicit.

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

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It does not mention read-only status, rate limits, data freshness, or any other side effects, leaving the agent with only the name 'get' to infer safety.

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

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

The description is a single, front-loaded sentence with no redundant wording. Every word contributes to naming the resource and action.

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 with no parameters. The description states the core return value, a list of supported currencies, but does not specify the format (e.g., codes, names). Given the lack of an output schema, a bit more detail could improve completeness, but it is adequate for a trivial list operation.

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

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

There are zero parameters, so the baseline is 4. The description adds no parameter-related meaning, but there is none needed.

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

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

The description uses the specific verb 'Get' with a clear resource, 'list of supported currencies'. It distinguishes the tool from siblings like get_countries by naming currencies explicitly.

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 when you need to retrieve supported currencies. However, the description does not explicitly state when to use it or mention any alternatives, which is a common omission for such a simple tool.

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 for behavioral disclosure. It only states 'Get backlinks' without mentioning pagination, result limits (despite the num parameter), authentication requirements, or output format. It implies a read operation but offers no additional behavioral context.

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

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

The description is a single, concise sentence that is front-loaded with the verb and resource. Every word contributes to meaning, 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 presence of sibling tools and no output schema, the description is too sparse. It does not clarify what 'backlinks' encompasses, how the num parameter affects results, or how this tool differs from similar alternatives. This incompleteness could lead to incorrect tool 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 description coverage is 100%, with both domain and num documented in the schema. The tool description adds no extra parameter semantics beyond what the schema already provides, so the 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?

The description uses a specific verb ('Get') and resource ('backlinks for a domain'), clearly indicating the tool's function. It implicitly distinguishes from sibling tools like get_page_backlinks by specifying 'domain', but does not explicitly differentiate from get_unique_domain_backlinks, leaving minor 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?

No guidance is provided on when to use this tool versus alternatives such as get_unique_domain_backlinks or get_page_backlinks. There are no context cues, prerequisites, or exclusions mentioned.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the retrieval action and does not mention return format, ordering, pagination, rate limits, or any side effects. The read-only nature is implied by the verb 'Get' but not explicitly disclosed.

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 clear sentence with no filler words. It is front-loaded with the action and resource, making it easy to scan and quickly 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?

For a simple read-only tool with fully described parameters, this is minimally adequate. However, there is no output schema and no annotations, so the description does not explain the result structure or edge cases. In an environment with many sibling tools, more context about return shape or usage nuances would improve completeness.

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 provides descriptions for all three parameters (domain, num, country), so the schema coverage is 100%. The description adds no additional parameter meaning beyond what the schema provides, which is acceptable but does not elevate the score.

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 ('Get') and clearly identifies the resource as keywords associated with a domain, stating that they are keywords the domain ranks for. It does not explicitly distinguish itself from closely related sibling tools like get_url_keywords or get_related_keywords, so it falls slightly short of a 5.

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

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

The description provides no guidance on when to use this tool versus alternatives such as get_url_keywords, get_related_keywords, or get_domain_traffic. There is no mention of preferred contexts, exclusions, or fallback tools, leaving usage entirely implied.

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 for behavioral disclosure. It does not mention side effects, data freshness, rate limits, or what 'traffic metrics' specifically includes. For a read operation, it lacks any detail that would help an agent anticipate the tool's 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 concise sentence that is front-loaded and wastes no words. It is appropriately sized for the tool's simplicity.

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 and no annotations, the description must explain what will be returned and in what form. It only says 'traffic metrics' without specifying metrics types or behavior. This is inadequate for an agent to fully understand the tool's output and fit within the broader tool context.

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

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

Schema coverage is 100% as both parameters have descriptions. The description adds no additional semantics beyond the schema, so the baseline of 3 is appropriate. It does not explain how the country parameter affects results or domain format nuances.

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 gets traffic metrics for a domain, identifying the specific verb and resource. However, it does not differentiate between this tool and siblings like get_url_traffic or get_domain_keywords, which could also involve traffic-related data.

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

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

There is no guidance on when to use this tool versus alternatives. It does not mention context, prerequisites, or exclusions. The description is a single sentence with no usage direction.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. However, it only states what data is returned, with no mention of output format, data source, limits on the number of keywords, or any side effects. It does not even explicitly state that this is a read-only operation, though it is implied by 'Get'.

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 entire description is a single, front-loaded sentence with no filler words. It conveys the core purpose immediately and efficiently.

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

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

The description is adequate for a simple data retrieval tool with a complete schema, but it does not specify important details such as the output format/return value, any batch size limits for the keyword array, or the effect of the country and currency parameters. Given the lack of an output schema, more context would be helpful.

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

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

The input schema has 100% coverage, so all parameters are already described. The description adds a marginal benefit by linking the tool's purpose to the 'keywords' parameter, but it does not explain the role of country or currency beyond what the schema already states.

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 'Get' and clearly identifies the resource (a set of keywords) and the data returned (Volume, CPC, competition). This distinguishes it from sibling tools like get_related_keywords or get_domain_keywords, which focus on discovering keywords rather than returning metrics.

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 explicit guidance is provided on when to use this tool versus alternatives. The description implies its use when the user has a set of keywords and needs volume/CPC/competition data, but it does not mention any exclusions or alternative tools for related 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?

No annotations are provided, so the description carries the full burden. It only states the primary action and implies a read operation, but does not mention return format, error behavior, or any side effects. This is minimal disclosure, but not misleading.

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 sentence that is concise and front-loaded with the action and resource. Every word contributes to understanding, with no unnecessary elaboration.

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 tool with high schema coverage, the description is sufficient to know what to pass and what to expect (a list of categories). The lack of output schema is not critical since the description implies the return value. However, slightly more detail about the response structure would improve completeness.

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

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

The schema description covers the 'network' parameter 100%, listing allowed values. The description itself adds no additional semantic value beyond what the schema already provides, so the 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?

The description clearly states the action ('Get') and the resource ('all available categories for a specific social media network'), which distinguishes it from sibling tools like find-hooks or get-archetype. The scope is specific enough to understand what the tool does.

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

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

The description provides no guidance on when to use this tool compared to alternatives, no exclusions, and no context about the broader workflow. It simply states the function without explaining how it fits with 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 only says 'Get backlinks', implying a read operation, but offers no details on pagination, uniqueness of backlinks, result format, or potential rate limits. Given the existence of a 'unique' variant, ambiguity remains about whether this returns all or unique backlinks.

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

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

The description is a single, well-structured sentence with no wasteful content. It efficiently conveys the core purpose, earning a top score for conciseness.

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 with only two parameters, but the description lacks sibling differentiation and return-value details. While the schema covers parameters, no output schema or behavioral notes exist, leaving some gap in understanding the full context.

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

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

Schema description coverage is 100% for both parameters ('Number of results' and 'URL to analyze'). The description adds no extra meaning beyond what the schema already provides, so the 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?

The description clearly states the tool fetches backlinks for a URL, using a specific verb and resource. However, it does not distinguish itself from sibling tools like get_domain_backlinks or get_unique_page_backlinks, which also deal with backlinks.

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

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

No guidance is provided on when to use this tool versus alternatives. It does not mention whether to prefer this over get_unique_page_backlinks or get_domain_backlinks, nor any context about use cases or limitations.

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 is the only source of behavioral disclosure. It only restates the basic function and provides no information about return format, pagination, rate limits, or side effects. Since it's a retrieval tool, the read-only nature is implied but not stated, and no additional behavioral traits are disclosed.

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 directly conveys the tool's purpose without unnecessary words. It is efficient and easy to parse, earning a high score for conciseness.

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 the schema fully covers parameters, but the description lacks any mention of output structure or behavior. Since there is no output schema, the agent must infer what 'Get keywords' returns. The description provides enough for a basic keyword lookup but fails to elaborate on limitations or use cases, leaving it somewhat incomplete.

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 both parameters thoroughly: 'keyword' as the seed keyword and 'num' as the number of results with a max of 1000. The tool description adds no new semantic meaning beyond what the schema provides, so with 100% schema coverage, the baseline score 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 'Get People Also Search For keywords based on a seed keyword' clearly states the tool's function with a specific verb and resource. It implies the input is a seed keyword, matching the schema. It does not explicitly differentiate from siblings like get_related_keywords, but the PASF terminology is specific.

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

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

The description provides no guidance on when to use this tool versus alternatives such as get_related_keywords or get_keyword_data, nor does it mention any prerequisites or exclusions. It simply states the action without context, leaving the agent without decision-making information.

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 only states the core function without disclosing any behavioral traits such as return format, whether it's a read-only operation, rate limits, or how 'related' is determined.

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

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

A single, front-loaded sentence that conveys the essential action in six words. No wasted words or redundant information.

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

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

With no output schema and no behavioral context, the description is minimally acceptable for a simple lookup tool, but it lacks details about the response structure and any caveats. It's complete enough for a basic tool but with clear 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?

The schema fully documents both parameters (keyword and num), so the description adds no extra semantic value beyond what's already structured. Baseline of 3 applies when schema coverage is high.

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 (Get), the resource (related keywords), and the basis (a seed keyword). This distinguishes it from siblings like get_keyword_data or get_domain_keywords, though it doesn't explicitly name alternatives.

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 it (when you have a seed keyword and need related terms) but gives no explicit guidance on when not to use it or which sibling alternative would be better.

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 text is truncated to fit platform limits, but it does not explain what happens when the text already fits, whether an ellipsis is appended, or the exact form of the returned output. These are material behavioral gaps for a truncation tool.

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

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

The description is a single, front-loaded sentence that conveys the core action, target, and context with no redundant words. It is exemplary in conciseness.

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 relatively simple, and the schema covers all parameters. However, with no output schema and no description of return behavior or platform-specific limit details, the description leaves ambiguity about the exact output format and edge cases (e.g., text already under limit, truncation markers). This is a notable gap for a text-transformation 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 descriptions cover all three parameters 100%, so the baseline of 3 applies. The description adds no parameter-specific meaning beyond what the schema already provides, though it links the 'platform' parameter to before-fold limits.

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 ('truncate') and clearly identifies the resource ('text') and scope ('before fold character limits for each social media platform'). It also implicitly differentiates from the sibling tool 'validate-content-before-fold', which likely validates rather than truncates.

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 by stating the purpose ('for previewing purposes') and the platform-specific behavior. It does not explicitly mention alternatives or exclusions, but the use case is sufficiently clear for an agent to know when to invoke it.

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

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only says 'Fetch…' without mentioning pagination, authentication, defaults, rate limits, or response format. It adds minimal insight beyond the basic action.

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

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

A single, front-loaded sentence that states the action and target without any fluff. It is concise and immediately clear.

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, but the description omits critical usage details such as how to specify multiple networks (the schema example is ambiguous) and what the response looks like. With no output schema, the description should provide more context to ensure correct 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?

The schema provides full descriptions for both limit and networks, so the baseline is 3. The description adds no further parameter details, but it doesn't need to since the schema already covers them.

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' with a clear resource ('trending social media content') and source ('HyperFeed API'), distinguishing it from the many scrapecreators_* sibling tools. It plainly states what the tool does.

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 for when to use this tool versus alternatives like scrapecreators_trending_feed. There is no mention of scenarios, exclusions, or preferred 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 full burden for behavioral disclosure. It only states the basic function, omitting details about return format, deduplication logic, 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?

The description is a single concise sentence with no fluff, but it is under-specified. It is not verbose, but its brevity sacrifices useful context.

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?

Though a simple tool with only 2 parameters and no output schema, the description is too minimal to be complete. It lacks explanation of the output structure, the meaning of 'unique', and how results are ordered or paginated.

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 provides 100% coverage with descriptions for both 'domain' and 'num', so the description adds no extra parameter semantics. The baseline of 3 applies since the schema does the heavy lifting.

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 'Get unique domain backlinks' clearly states the action (get) and the resource (unique domain backlinks), distinguishing it from siblings like get_domain_backlinks and get_unique_page_backlinks. However, it does not explain what 'unique' means precisely.

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

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

No guidance is provided on when to use this tool versus the similar get_domain_backlinks or get_unique_page_backlinks. Users are left to infer the difference from the name alone.

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

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It mentions 'unique' and 'specific URL', which hints at filtering/dedup behavior, but it does not disclose what 'unique' means, how backlinks are collected, response format, pagination, rate limits, or any side effects. For a read-only tool, this is a minimal disclosure.

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

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

The description is a single, concise sentence that gets straight to the point. It is front-loaded with the action ('Get') and resource ('unique backlinks'), with no unnecessary words 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?

The tool is simple, with only 2 parameters and no output schema, but it has many similar sibling tools. The description does not clarify what 'unique' means or how this differs from get_page_backlinks, which could lead to incorrect tool selection. Given the lack of annotations and the close siblings, a bit more context (e.g., 'returns deduplicated backlinks, unlike get_page_backlinks') would be needed for full completeness.

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%, with both 'url' and 'num' described in the input schema. The description adds the qualifier 'unique' and 'specific URL', which reinforces the 'url' parameter's purpose but does not add significant new meaning beyond the schema. Baseline for high coverage is 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 'Get unique backlinks for a specific URL' clearly states a verb ('Get'), a resource ('backlinks'), and a scope ('for a specific URL'). The inclusion of 'unique' distinguishes it from sibling tools like get_page_backlinks, which likely returns all backlinks, and from domain-level tools like get_domain_backlinks.

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

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

The description implies usage for a specific URL and hints at uniqueness ('unique backlinks'), but it does not explicitly state when to use this tool over alternatives like get_page_backlinks or get_unique_domain_backlinks. No exclusions or alternative suggestions are provided, leaving the selection criteria 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?

No annotations are provided, so the description bears full responsibility for disclosing behavior. It only states the core action ('Get keywords that a URL ranks for') without mentioning pagination, rate limits, error cases, authentication needs, or what the response contains. This is minimal behavioral transparency.

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, brief sentence that is front-loaded and contains no fluff. It efficiently communicates the core purpose, and 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 tool is simple with well-documented parameters, but the description is terse. It does not explain the output shape (since there is no output schema), nor does it differentiate among the many sibling keyword/URL tools. This is adequate but leaves noticeable gaps for an agent to choose and use it confidently.

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 provides complete descriptions for all three parameters (url, num, country), so the schema carries the semantic weight. The description itself adds no parameter-specific details, but since schema_description_coverage is 100%, the 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?

The description 'Get keywords that a URL ranks for' clearly states the verb and resource, and the focus on 'URL' distinguishes it from sibling tools like get_domain_keywords. However, it does not explicitly name any sibling or explain the distinction, so it lacks differentiation beyond the URL wording.

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 retrieving keyword rankings for a specific URL, but it gives no explicit guidance on when to choose this over get_domain_keywords or get_related_keywords. There are no alternatives mentioned, no prerequisites, and no exclusions, so usage context is only implied.

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

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only offers a minimal hint that the tool reads traffic data. It does not disclose what metrics are returned, time range, authentication needs, rate limits, or any other behavioral traits, leaving the agent underinformed.

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 short sentence and is not verbose, but it is under-specified. While there is no wasted text, the extreme brevity fails to convey useful guidance, making it less a model of conciseness and more an example of minimalism that sacrifices clarity.

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 there is no output schema and no annotations, the description must explain what the tool returns and any relevant context, but it only says 'traffic metrics'. It omits details about metric types, country handling, URL requirements, or how this relates to domain-level traffic, making it incomplete for an agent to confidently use.

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

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

The input schema provides 100% coverage with descriptions for both 'url' and 'country', so the baseline is 3. The description does not add any extra meaning to the parameters, but the schema already documents them sufficiently.

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 ('Get') and resource ('traffic metrics for a URL'), making the tool's basic purpose obvious. However, it does not distinguish itself from sibling tools like get_domain_traffic or get_url_keywords, so it lacks the differentiation needed for a 5.

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

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

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no mention of how it differs from similar traffic or URL tools. The description provides no context to help an agent decide between this and 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?

With no annotations provided, the description carries full responsibility for behavioral disclosure. It only claims 'best-in-class text rendering', which is a quality assertion, not a behavioral detail. It does not mention that the tool generates images (obvious from name), returns a URL, requires authentication, supports inpainting, or has any side effects. The schema notes some parameter interdependencies but the description itself lacks meaningful behavioral transparency.

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. It efficiently conveys the tool's purpose and a key selling point without any wasted words. This is appropriately concise and well-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?

While the tool is complex (10 parameters, inpainting, style presets, etc.) and there is no output schema, the input schema is richly described. The one-line description does not provide usage context, return format, or examples, but the schema compensates for parameter details. Overall, the description is barely adequate for such a complex tool; it needed at least a brief mention of example usage or output expectations.

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-level meaning beyond what the schema already provides. Each parameter is well-documented with its own description, so the tool description's lack of parameter details is acceptable.

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 'AI image generation', specifying the verb (generation) and resource (images). It also highlights a key differentiator ('best-in-class text rendering'), which is a specific capability. Although no explicit sibling differentiation is provided, none of the sibling tools are image generators, so the purpose is 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 no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, use cases, or exclusions. All sibling tools are data-retrieval/scraping tools, but no explicit 'use this for image generation' contextual guidance is given.

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 disclosure. It says 'Get' which implies a read-only behavior, and it states the returned content. However, it does not disclose potential pagination, authentication needs, or any side effects, leaving some behavioral gaps.

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

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

The description is a single sentence that is immediately informative, front-loading the core action and resource. Every word adds value, with no redundant 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 list tool with no parameters and no output schema, the description adequately describes the return value (names and descriptions). It lacks any caveats but is sufficient for low-complexity tools; a perfect score would require more behavioral context.

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

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

The tool has zero parameters and the schema fully covers this (0 properties, 100% coverage). Per the rubric, the baseline for 0 parameters is 4, and no additional parameter explanation is needed.

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

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

The description clearly states a specific verb ('Get') and resource ('all available voice archetypes') with the expected content ('names and descriptions'). It distinguishes from siblings like get-archetype by emphasizing the complete list rather than a single archetype.

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 context: use this when you want to see every available archetype. However, it does not explicitly mention when not to use it (e.g., if you need a specific archetype, use get-archetype) or provide alternative tools, so the guidance remains 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 must carry the full behavioral burden. It states the operation is a read-only 'get' that returns a list with descriptions, but it does not disclose error behavior, rate limits, or any potential side effects. For a simple list tool this is minimal, and the agent is left to infer that it is safe.

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, clear sentence with no redundancy. It front-loads the action and resource, making it easy to understand at a glance.

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 list tool with one parameter and no output schema, the description sufficiently covers what it returns (a list of frameworks with descriptions) and the required context (a specific social media network). It could be more explicit about output structure or completeness, but given the low complexity, it is largely 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?

The input schema has 100% coverage for the single 'network' parameter, including a list of valid values. The description adds general context about network-specific listing but does not contribute meaning beyond the schema's property description, so a 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 the action ('Get a list'), the resource ('available copywriting frameworks'), and the scope ('for a specific social media network'). It distinguishes itself from the sibling 'get-copywriting-framework' which implies retrieving a single framework.

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 this tool (when you need all frameworks for a given network) but does not explicitly contrast it with 'get-copywriting-framework' or mention when not to use it. There are no explicit alternatives or exclusions, so the guidance is implied rather than direct.

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. 'Ad Details' says nothing about return format, whether it performs a read-only operation, potential limitations, or any side effects. This is a significant gap for a tool with no other context.

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

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

The description is extremely short, but this is under-specification rather than effective conciseness. It provides almost no useful information and does not earn its place, failing the requirement that every sentence should add 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?

Given the large number of sibling tools with similar names, no output schema, and no annotations, the description is completely inadequate. It does not explain what ad details are returned, which platforms or ad libraries are covered, or how this tool differs from alternatives.

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

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

The input schema has one parameter (url) with a description covering 100% of the schema, so the baseline is 3. The description adds no additional semantic value beyond the schema's 'The url of the ad', but it does not need to compensate since the schema already documents the parameter adequately.

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 'Ad Details' is essentially a restatement of the tool name, providing no verb or specific resource action. It does hint that the tool deals with ad details, but it fails to distinguish from numerous sibling tools like scrapecreators_get_ad or scrapecreators_company_ads.

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

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

There is no guidance on when to use this tool versus alternatives, no context about which platforms or ad types it supports, and no mention of exclusions or prerequisites. The description is completely silent on usage scenarios.

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 and no behavioral description, the tool's effects, return format, authentication needs, or rate limits are completely undisclosed. The description adds zero value beyond the tool name.

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 in word count but this is under-specification, not effective brevity. A single vague noun phrase fails to convey essential information, making it below average.

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 purpose of retrieving ad details, the description is severely incomplete. It does not specify what details are included, how the output is structured, or any constraints on the URL. No output schema exists, so the description carries the full burden, which it fails to meet.

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% because the single parameter 'url' includes 'The url of the ad'. Per the baseline for high schema coverage, a score of 3 is appropriate; the description adds no additional semantic meaning 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 'Ad Details' is a noun phrase that simply restates the tool name. It lacks a specific verb (e.g., 'Get', 'Fetch') and does not clarify the resource or scope, making it indistinguishable from siblings like scrapecreators_get_ad or scrapecreators_ad_details.

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 scrapecreators_search_ads or scrapecreators_company_ads. There are no prerequisites, exclusions, or context that would help an agent select this tool.

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 offers no information about what the tool returns, whether it is read-only, any rate limits, or other behavioral traits. The bare phrase 'Advertiser Search' reveals nothing about side effects or output.

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, but it is under-specified rather than efficient. A two-word noun phrase does not earn its place because it conveys no actionable information and fails to serve the agent's needs.

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 having a simple schema and no output schema, the tool operates in a crowded space of sibling tools. The description is hopelessly incomplete—it doesn't even state the tool's basic function, let alone differentiate it from similar tools or clarify return values or search scope.

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% since the 'query' parameter has a description ('The query to search for'), so the baseline is 3. However, the tool description adds no extra meaning beyond this generic schema text; the nature of the query (e.g., advertiser name, ID) remains unspecified.

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 'Advertiser Search' is a noun phrase that simply restates the tool name (scrapecreators_advertiser_search). There is no verb or resource to specify what action is performed, and it fails to distinguish this from many sibling search tools like scrapecreators_search_ads or scrapecreators_search_for_companies.

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

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

No guidance is provided on when to use this tool versus alternatives. With a sibling list containing multiple search-related tools (search, search_ads, search_for_companies, etc.), the absence of any usage context makes it impossible for an agent to select this tool correctly.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. 'Age and Gender' discloses nothing about side effects, return data, auth requirements, or operational behavior, making this a critical gap.

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 under-specified rather than concise. It is a two-word fragment that provides no functional information, unlike an appropriately sized description that front-loads the essential purpose.

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

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

Given the absence of annotations and output schema, the description is wholly inadequate. It does not explain what data is returned, which social platforms are supported, or how it relates to the many sibling scrapecreators_* tools, making it nearly impossible to select 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 input schema already provides a clear description for the single 'url' parameter ('URL to users social profile'), achieving 100% schema coverage. The description adds no additional parameter semantics, 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 'Age and Gender' is a tautological restatement of the tool name 'age_and_gender'. It lacks a verb and resource context, and does not distinguish the tool from numerous similar scrapecreators_* sibling tools.

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

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

No guidance is provided on when to use this tool versus alternatives. The description contains no context about use cases, prerequisites, or exclusions, leaving the agent without any decision support.

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 must disclose behavioral traits, but it says nothing about what data is returned, whether it is a read-only operation, or any limitations. The two-word description offers no transparency.

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?

While extremely short, this is under-specification rather than effective conciseness. The two words provide no useful information beyond the tool name, so it fails to earn its place as a meaningful description.

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, no annotations, and a minimal description, the tool is severely under-documented. It is unclear what the tool does, what it returns, or how it differs from the many related tools in the sibling list.

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

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

The schema description coverage is 100% for the single 'url' parameter, which is described as 'URL to Amazon Shop page'. This is sufficient, so the baseline of 3 applies even though the description adds no extra 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 'Amazon Shop' is merely the resource name, not an action statement. It lacks a specific verb like 'scrape' or 'retrieve' and does not distinguish this tool from siblings such as scrapecreators_shop_products or scrapecreators_product_details.

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

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

No guidance is provided on when to use this tool instead of the many similar scrapecreators_* tools. There is no mention of use cases, prerequisites, or 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 of disclosing behavior. It does not state whether the operation is read-only, what data is returned, or any side effects. It is completely opaque.

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 short but not usefully concise; it under-specifies the tool's function. It is closer to a label than a description, similar to a tautology.

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 lacks annotations and an output schema, so the description must fully describe what the tool does and returns. 'Basic Profile' conveys no actionable information, making the description completely inadequate for an agent to invoke the tool 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 input schema has full coverage (100%) with a single parameter 'userId' described as 'Instagram user id'. The description adds no additional parameter information, but per baseline rules, high schema coverage yields a 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 'Basic Profile' merely restates the tool name without a verb or explicit resource. It does not specify what the tool does (e.g., fetch, retrieve, scrape a basic profile). There is no differentiation from sibling tools like scrapecreators_instagram or scrapecreators_profile_photos.

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

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

The description provides no context on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or exclusions. It is entirely silent on selection 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 of behavioral disclosure. It discloses nothing about whether this is a read operation, what data it returns, rate limits, or authentication requirements. The single word 'Bluesky' offers zero behavioral context.

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

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

The description is extremely under-specified. A single word is not 'concise' in a meaningful sense; it lacks any informative content. It is similar to the 'Process' example, which warranted a score of 2 for under-specification rather than true conciseness.

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 likely complexity (a scraping tool for a specific platform), the complete absence of description, annotations, and output schema leaves the agent with almost no guidance. The description is wholly inadequate for correct selection and 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?

The input schema has one required parameter 'handle' with a description 'Bluesky handle', providing 100% schema coverage. The tool description adds no additional parameter meaning, but the schema already fully documents the parameter, so a 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?

The description is simply 'Bluesky' – a platform name, not a verb or resource. It does not state what the tool does (e.g., 'Scrape Bluesky profile data' or 'Get Bluesky posts'). This fails to distinguish it from the many other scrapecreators_* tools, which have explicit action-oriented names.

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 usage context is provided. There is no guidance on when to choose this tool over sibling tools like scrapecreators_basic_profile or scrapecreators_posts. It does not mention any exclusions, prerequisites, or alternatives.

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

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

With no annotations provided, the description carries full responsibility for disclosing behavioral traits. It discloses nothing—no mention of pagination, rate limits, required authentication, or what the response contains. The word 'Board' gives no behavioral insight.

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?

Single word 'Board' is under-specification, not conciseness. It lacks the verb and object needed to be informative, so it fails to earn its place as a useful description.

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?

This is a tool with three parameters and no output schema or annotations. The one-word description is completely inadequate to convey purpose, usage, or behavior, leaving the agent with almost no contextual information.

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 each parameter (url, trim, cursor) has a descriptive comment. The description itself adds no extra meaning, but because the schema already documents the parameters, the 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?

The description is simply the noun 'Board', which restates the tool name without any verb or action. It fails to state what the tool does, e.g., retrieve or scrape board data, and provides no differentiation from sibling tools like scrapecreators_user_boards or scrapecreators_post.

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

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

The description provides no guidance on when to use this tool or how it relates to alternatives. There is no mention of use cases, prerequisites, or exclusions, leaving the agent without any basis for tool selection.

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

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

With no annotations, the description carries the full burden of behavioral disclosure, but it discloses nothing: no mention of pagination via continuationToken, sort behavior, data returned, or any side effects. It is completely opaque about the tool's runtime 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 extremely short, but this is under-specification rather than conciseness. A single noun phrase does not provide enough substance to be considered well-structured or valuable.

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 moderately complex (4 params including continuationToken for pagination and sort), yet the description provides no context about return values, pagination, or how to use the tool effectively. With no output schema and no annotations, the description is wholly inadequate.

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 100% of the four parameters with descriptions, so the baseline is 3. The description adds nothing beyond the schema, but the schema itself is sufficient for parameter understanding.

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 'Channel Shorts' is a noun phrase with no verb or action, making it a tautology of the tool name. It does not state that the tool retrieves or lists short-form videos from a channel, and it does not differentiate itself from sibling tools like scrapecreators_channel_videos or scrapecreators_trending_shorts.

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or how it differs from other scrapecreators_* tools, leaving the agent without context for selection.

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

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

With no annotations, the description carries the full burden of disclosing behavioral traits. It says nothing about whether the operation is read-only, performance implications, pagination, or any side effects. The only behavioral information appears in the schema parameter for includeExtras, not in the description itself.

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 ('Channel Videos'), but this is under-specification rather than efficient brevity. Every word is wasted because it adds no value beyond the tool name. It lacks a leading verb or any context.

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?

This tool has 5 parameters, no output schema, and no annotations. The description provides no explanation of the tool's behavior, return format, pagination, or relationship to other endpoints. For a tool with moderate complexity, this is completely inadequate.

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

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

The schema description coverage is 100%, so the baseline is 3. The description itself adds no meaning beyond what is in the schema, but the schema's parameter descriptions (e.g., includeExtras explaining like/comment counts and alternative endpoints) already provide adequate semantics. The tool description does not compensate further, but also does not detract.

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 'Channel Videos' is a noun phrase, not a verb phrase indicating an action. It merely restates the tool name without specifying what the tool does (e.g., retrieves, lists, scrapes). It provides no distinction from sibling tools like scrapecreators_channel_shorts or scrapecreators_video_info.

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of appropriate scenarios, prerequisites, or exclusions. The description is entirely silent on usage context.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. "Clip" discloses nothing about side effects, return data, permissions, or whether the operation is read-only. The tool could be anything from fetching clip metadata to posting a clip, with zero transparency.

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 word is technically concise, but it is under-specification, not efficient communication. It does not convey any information beyond the tool name and fails to earn its place as a useful description.

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 extremely simple (one parameter, no output schema), but the description is still grossly incomplete. An agent cannot infer what data is returned, whether the operation is safe, or how it differs from related tools. The bare minimum would be a phrase like 'Fetch details for a Twitch clip by URL'.

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 has 100% description coverage, with the only parameter 'url' described as 'Twitch clip URL'. According to the rubric, this warrants a baseline of 3 even though the description itself adds no parameter information. However, the description does not clarify the expected URL format or any constraints 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 "Clip" is a noun, not a verb phrase, and merely restates the tool name. It gives no indication of what action the tool performs (e.g., fetch, scrape, download) on the Twitch clip, and it does not distinguish the tool from the many sibling tools like scrapecreators_twitch.

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

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

The description provides no guidance on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or exclusions, making it impossible for an agent to decide when to select this tool.

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 does not disclose what the tool returns, whether it is a read operation, how pagination works, or any other behavioral details. The description is completely opaque.

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?

At one word, it is extremely brief, but this is under-specification rather than effective conciseness. The description does not earn its place for a tool with two parameters and significant sibling overlap.

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 annotations, no output schema, and a one-word description, the tool is contextually empty. It provides no explanation of expected output, error conditions, or how it relates to similar tools, leaving the agent unable to use it 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 description coverage is 100%, with both url and cursor well documented in the input schema. The description adds no additional parameter context, but the schema alone provides enough meaning, so the 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?

The description is simply the word 'Comments,' which merely restates the tool name. It lacks a verb or specific resource description and fails to distinguish this from sibling tools like scrapecreators_comments_get or scrapecreators_post_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?

No guidance is given on when to use this tool versus alternatives. With a large sibling list and no context, an agent has no way to decide if this is the right tool for obtaining comments.

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 and a one-word description, the tool's behavior is completely opaque. The agent learns nothing about pagination, return format, rate limits, or side effects.

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 under-specified to the point of being a tautology. It is not concise but rather an empty placeholder that fails to communicate any meaningful structure or 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?

The tool has no annotations, no output schema, and only a one-word description. Given the presence of a continuation token parameter, the description should explain how pagination works and what the response contains, but it explains nothing.

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%, with each parameter having a description. The baseline for high coverage is 3, and the tool description adds no additional parameter semantics 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 is a single noun 'Comments', which merely restates the tool name and provides no verb or resource context. It does nothing to distinguish this tool from siblings like 'scrapecreators_comments' or other comment-related tools.

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

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

There is no guidance on when to use this tool versus alternatives. The description does not mention scenarios, prerequisites, or relationships to sibling tools such as 'scrapecreators_comments'.

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. The word 'Community' reveals nothing about read/write behavior, return data, pagination, or side effects, which is a critical gap for a scraping tool.

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

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

At one word, this is maximally concise but severely under-specified. It is not efficient writing; it is an absence of information. The description does not earn its place because it provides no functional 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?

With no annotations, no output schema, and a one-word description, the tool is a complete black box. Given the likely complexity of a community scraper (platform, data fields, auth), this is grossly inadequate.

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 required parameter 'url' has a description 'Community URL', so the baseline is 3. However, the tool description adds no meaning beyond this terse label, and the schema description itself is minimally informative.

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 is just the word 'Community'. It restates a fragment of the tool name without any verb or resource, making it a tautology. It fails to distinguish this from siblings like scrapecreators_community_post_details or scrapecreators_community_tweets.

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

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

There is no guidance on when to use this tool versus any of the dozens of sibling scraper tools. The description gives no context, prerequisites, or alternative suggestions, leaving the agent completely without direction.

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 reveals nothing about data returned, side effects, required permissions, or any constraints. The tool's behavior is completely opaque.

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 short, but this is under-specification rather than effective conciseness. A single vague phrase cannot adequately describe the tool's function or usage.

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 complexity (1 parameter, no output schema, no annotations), the description is still completely inadequate. It fails to explain what 'community post details' includes, how the output is structured, or how it differs from similar 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 description coverage is 100% for the single url parameter, which has a clear description. The tool description adds no additional meaning beyond the schema, 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 'Community Post Details' is a noun phrase that merely restates the tool name without a functional verb. It does not specify what action the tool performs (e.g., retrieve, scrape, get) or what 'details' entails, making it essentially a tautology.

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

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

The description provides no guidance on when to use this tool versus alternatives. With numerous sibling tools like scrapecreators_community, scrapecreators_post, and scrapecreators_community_tweets, there is no information to help an agent choose correctly.

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

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

With no annotations, the description is the only source of behavioral information, but it provides none. It does not disclose whether this is a read operation, what it returns, or any limitations.

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 two-word phrase that is under-specified rather than concise. It lacks any structure or informative content, making it closer to a placeholder than a description.

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 absence of an output schema and annotations, the description needed to explain the tool's function and return value, but it is completely absent. The tool is simple, but the description fails to provide even the basic context required for an agent to select it.

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 covers the single 'url' parameter with a basic description. The tool description adds no additional meaning about the parameter, but since schema coverage is 100%, 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 'Community Tweets' merely restates the tool name without any action verb. It does not explain what the tool does (e.g., fetch tweets from a Twitter community) and fails to distinguish it from similar sibling tools like scrapecreators_community or scrapecreators_user_tweets.

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

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

There is no indication of when to use this tool versus alternatives. No context, prerequisites, or exclusions are provided.

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, and the description 'Company Ads' discloses zero behavioral traits. There is no mention of pagination, authentication, data returned, or any side effects, leaving the agent completely in the dark.

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?

While the description is extremely short, this is under-specification rather than conciseness. A one-word phrase with no structure fails to earn its place as a useful description.

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?

This is a 10-parameter tool with no output schema and no annotation support. The description provides no context about return values, required inputs, or operational behavior, making it completely inadequate for an agent to 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?

The input schema provides descriptions for all 10 parameters (100% coverage), so the description need not re-iterate them. However, the description adds no insight into how parameters like companyName, pageId, or status are used or related. Baseline 3 is appropriate given full schema coverage.

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 'Company Ads' is essentially a restatement of the tool name with no verb or action. It does not state whether the tool lists, scrapes, or searches company ads, and it fails to differentiate from sibling tools like scrapecreators_company_ads_get.

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

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

There is no guidance on when to use this tool versus alternatives. Siblings such as scrapecreators_ad_details, scrapecreators_advertiser_search, and scrapecreators_company_ads_get suggest related but distinct purposes, yet the description provides no context for choosing among them.

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 present, so the description must disclose behavior. It fails to mention return format, credit costs, pagination, or side effects. The only behavioral hint (get_ad_details costs 25 credits) appears in the schema, not the description.

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?

'Company Ads' is under-specification rather than conciseness. A two-word phrase cannot convey the semantic load of an 8-parameter tool, and there is no structure to guide an agent's reading.

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 8 optional parameters, no output schema, and no annotations, the description is drastically incomplete. It does not explain the tool's purpose, usage context, or relationship to sibling ad tools, making it nearly impossible 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 description coverage is 100%, with all 8 parameters documented (topic, cursor, domain, region, dates, advertiser_id, get_ad_details). The description adds no parameter-level meaning, but the high schema coverage meets the baseline 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 'Company Ads' is a noun phrase identifying a resource but lacks a verb indicating the action (get, search, list). It does not distinguish among sibling tools like scrapecreators_company_ads or scrapecreators_advertiser_search, leaving the operation ambiguous.

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

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

No guidance is provided on when to use this tool versus alternatives. With many ad-related siblings (e.g., scrapecreators_company_ads, scrapecreators_ad_details_get, scrapecreators_search_ads), the description offers no context, prerequisites, or selection criteria.

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

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

With no annotations, the description must disclose behavior. It only says 'Company Page', revealing nothing about whether the tool performs a read operation, requires authentication, or returns specific data formats. This is a complete absence of behavioral information.

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?

Although only two words long, the description is under-specified rather than concise. It conveys no actionable information and reads as a placeholder label rather than a meaningful summary.

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 and no annotations, the description is the sole information source. 'Company Page' leaves the agent completely uncertain about the returned data, error behavior, and relationship to sibling tools, making it inadequate for task completion.

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 'url' parameter with 'The URL of the LinkedIn company page to get', providing 100% schema coverage. The description adds no additional parameter context, so the 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?

The description is the fragment 'Company Page' with no verb or action. It only names the resource, making it a tautology of the tool name's subject. It does not specify that the tool scrapes or retrieves company page data.

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

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

No guidance is provided on when to use this tool versus alternatives like scrapecreators_company_ads or scrapecreators_search_for_companies. The description lacks any mention of use cases, prerequisites, or 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals nothing about side effects, authentication requirements, rate limits, data returned, or any other runtime behavior, leaving the agent completely in the dark.

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 only two words, which is not conciseness but severe under-specification. It fails to provide any meaningful content that would help an agent, and the minimal text does not earn 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 there is no output schema and no annotations, the description needed to explain the tool's purpose and behavior, but it does not. The description is completely inadequate for an agent to determine what to expect or how to invoke the tool 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 input schema provides a single required 'handle' parameter with a clear description 'Instagram handle', achieving 100% schema description coverage. The tool description adds no parameter-specific information, so the baseline of 3 applies as the schema does the heavy lifting.

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 'Embed HTML' merely restates the tool name in a human-readable form, providing no context about what the tool actually does. It lacks a specific verb+resource explanation and does not distinguish itself from the many similar scrapecreators_* tools.

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

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

The description offers absolutely no guidance on when to use this tool, what scenarios it is suited for, or how it differs from alternatives. There are no exclusions, alternatives, or usage context provided.

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, and the description carries no behavioral details. It does not disclose what happens when the tool is called, whether it is read-only, what data is returned, or any error handling, rate limits, or side effects.

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 short, but this is under-specification rather than effective conciseness. It provides no useful information beyond the tool name fragment and does not earn 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?

With two parameters, no annotations, and no output schema, the description needs to explain the tool's purpose and behavior, but it provides only the word 'Facebook'. This is completely inadequate for an agent to select and invoke the tool 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 input schema covers 100% of the parameters with descriptions ('Facebook profile URL', 'Set to true to get business hours'), so the baseline is 3. The description itself adds no additional parameter meaning beyond what the schema already provides.

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 is the single word 'Facebook', which merely identifies the platform and restates part of the tool name. It does not state what the tool does (e.g., scrape a Facebook profile) or distinguish it from sibling tools like scrapecreators_facebook_ad_library or scrapecreators_facebook_group_posts.

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

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

There is no guidance on when to use this tool or why it should be chosen over any of the over 50 sibling tools. No use cases, prerequisites, or alternative tools are mentioned.

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

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

With no annotations provided, the description must fully disclose behavior, but 'Facebook Ad Library' reveals nothing about side effects, required permissions, rate limits, or response characteristics. It is a bare label, not a behavioral explanation.

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 exceptionally short, but this is under-specification rather than effective conciseness. It contains no actionable information and fails to earn its place as a standalone description.

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, no output schema, no annotations, and a large set of sibling tools, the description leaves nearly all contextual gaps unfilled. It does not explain what inputs mean in context, what the output looks like, or how this tool relates to other ad library 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 description coverage is 100%, so the baseline is 3. The description itself adds no parameter meaning beyond what the schema already provides, but the schema adequately names 'Ad ID', 'Ad URL', 'trim', and 'get_transcript' with short explanations.

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 'Facebook Ad Library' merely restates the tool name without providing a verb or action. It does not say whether the tool searches, scrapes, or retrieves ads, nor does it distinguish it from sibling tools like scrapecreators_search_ads or scrapecreators_ad_details.

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

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

There is no guidance on when to use this tool versus alternatives. Among many ad-related sibling tools, no context, prerequisites, or examples are given, leaving the agent unable to decide on appropriate 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, and the description gives no behavioral details. It does not mention pagination, required parameters, authentication, rate limits, or output behavior, leaving the agent entirely uninformed about the tool's side effects or prerequisites.

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 short, but this is under-specification rather than efficient conciseness. It provides no actionable information and fails to earn its place in a tool definition.

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 zero annotations, no output schema, and a two-word description, the tool is severely under-specified. An agent cannot determine what this tool does, how to invoke it correctly, or what the response will look like.

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%, with each parameter having a basic description (e.g., 'The URL of the group'). The description itself adds no parameter semantics beyond the schema, so the baseline score 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 'Facebook Group Posts' is a noun phrase that merely restates the tool name without a verb or action. It does not specify what the tool does (e.g., scrape, fetch, list) or differentiate it from siblings like scrapecreators_facebook or scrapecreators_subreddit_posts.

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

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

There is no guidance on when to use this tool versus alternatives. Given the large number of sibling scrapecreators tools, the lack of any context for selection is a clear gap.

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 and no descriptive text, the tool's behavior is entirely undisclosed. There is no information about read-only nature, pagination behavior, response format, or any side effects, which is a significant gap for a scraping tool.

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

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

The description is under-specified to the point of being a single word. This is not efficient conciseness but rather a lack of substance, providing no actionable information for the agent.

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 four parameters, no output schema, and many closely related sibling tools, a one-word description is completely inadequate. The agent has no way to understand the tool's scope, return values, or relationship to other followers-related 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?

The input schema descriptions cover all four parameters (trim, handle, user_id, min_time) with clear meanings, including pagination hints. Since schema description coverage is 100%, the baseline of 3 is appropriate even though the tool description itself adds no parameter information.

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 'Followers' merely restates the tool name without specifying an action or resource. It does not indicate that this tool retrieves follower lists for a TikTok handle, nor does it distinguish itself from sibling tools like scrapecreators_following.

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or exclusions, leaving the agent to infer context from the tool name alone.

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

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

No annotations are provided, so the description carries full responsibility for disclosing behavior. It says nothing about pagination (despite a 'min_time' parameter hinting at it), rate limits, output format, or whether it requires special permissions. The single word 'Following' provides zero behavioral insight.

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 short, which is not genuine conciseness but under-specification. It has no structure, no summary, and wastes the opportunity to convey essential information in a few more words.

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

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

Given the lack of annotations and output schema, the description must compensate but does not. The tool likely returns a following list with pagination, yet nothing in the description explains the response shape, pagination flow, or any constraints. It is completely inadequate for effective tool selection and 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?

The schema covers 100% of parameters with descriptions, so the baseline is 3 even though the tool description adds no parameter information. The 'min_time' parameter description mentions pagination, but the tool description does not reinforce or add meaning 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 is a single word 'Following', which merely restates the tool name and gives no verb or resource context. It does not clarify whether this retrieves a user's following list, a follow action, or a category, and it fails to distinguish from the sibling tool scrapecreators_followers.

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

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

There is no guidance on when to use this tool or when to prefer alternatives. The description provides no context about prerequisites, typical use cases, or how it differs from other scrapecreators 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 provided, the description carries the full burden of disclosing behavioral traits, but it reveals nothing about side effects, return format, required permissions, or edge cases. The phrase 'Get Ad' alone is insufficient for an agent to understand the tool's 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 extremely short (two words), but this is under-specification rather than effective conciseness. It lacks essential details such as what the tool returns, the expected format, or any usage context, making it unhelpful despite being brief.

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 no output schema, no annotations, and a description that provides almost no contextual information. Given the tool's complexity (one parameter) and the presence of many sibling tools, the description is completely inadequate for an agent to select and invoke this tool 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 input schema has 100% coverage with a single parameter 'id' described as 'Ad id'. While the description itself adds no semantic meaning, the schema already documents the parameter adequately. Following the baseline rule for high schema coverage, a 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 'Get Ad' is a tautology that restates the tool's name without specifying what 'ad' refers to, what platform or data source is involved, or what the tool actually does. It fails to distinguish itself from sibling tools like scrapecreators_ad_details or scrapecreators_company_ads.

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

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

There is no guidance on when to use this tool versus alternatives. The description offers no context, prerequisites, or examples, leaving the agent to guess from the name and parameter.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals nothing about pagination behavior, default sort order, response format, or rate limits. This is completely opaque.

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 severely under-specified rather than concise. It consists of a single tautological phrase that provides zero additional value beyond 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?

This is a discovery tool with 5 optional parameters and no output schema. The one-phrase description fails to explain what 'popular' means, what platforms are covered, how results are ordered, or what response shape to expect. It is completely inadequate.

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 per the baseline, a score of 3 is appropriate even though the description adds no parameter context. The schema already documents each parameter minimally.

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 'Get popular creators' is a tautology of the tool name. It provides no specific verb beyond the name and fails to distinguish this tool from many siblings like scrapecreators_search_users or scrapecreators_trending_feed.

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 given on when to use this tool versus alternatives. There is no mention of context, exclusions, or which sibling tools might be more appropriate for searching or trending content.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it offers none. It does not explain pagination, default periods, country filtering behavior, or what 'popular' means, leaving the agent without critical operational context.

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

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

The description is only three words long, which is extremely concise, but it is under-specification rather than effective brevity. It lacks any structural or contextual detail needed for a tool with 4 parameters.

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 moderate complexity (4 optional parameters, no output schema, no annotations), the description is severely incomplete. It does not explain what constitutes 'popular,' which platform or data source is involved, or how the parameters affect results.

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 4 parameters with descriptions, so the baseline is 3. The description adds no additional meaning beyond the schema, but since schema coverage is 100%, this is acceptable.

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 'Get popular hashtags' uses a specific verb and resource, clearly distinguishing it from sibling tools like get_popular_creators and get_popular_videos. It is minimal but unambiguous about the tool's primary function.

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

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

No guidance is provided on when to use this tool versus alternatives such as scrapecreators_search_by_hashtag. There is no mention of intended contexts, prerequisites, or 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention side effects, auth requirements, rate limits, or return shape, making it impossible for the agent to anticipate what invoking this tool will do.

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 short, which might seem concise, but it is under-specification. It does not convey enough information to be useful and does not earn its place as a meaningful tool guide.

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 6 optional parameters, no output schema, no annotations, and a broad name, the description is completely inadequate. It lacks any explanation of return values, platform context, or how parameters interact, making it unusable for effective tool 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?

The input schema covers all 6 parameters with descriptions, so schema coverage is 100%. The tool description adds no additional meaning beyond the schema, meeting the baseline but not compensating for the vague parameter names like 'timePeriod' or 'commercialMusic'.

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 'Get popular songs' clearly states a verb and resource, but it is essentially a restatement of the tool name. It fails to define what 'popular' means, which platform or context it applies to, and does not distinguish it from sibling tools like scrapecreators_get_popular_videos or scrapecreators_get_song_details.

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

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

No guidance is provided on when to use this tool versus the many sibling scraping tools. There is no mention of preferred use cases, required filters, or alternative tools, leaving the agent with no directional help.

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 and a description that only says 'Get popular videos,' there is no disclosure of read-only status, pagination behavior, rate limits, or return format. The description fails to convey any behavioral trait beyond the implied 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?

'Get popular videos' is brief and front-loaded, but it is under-specified to the point of being uninformative. This is an instance of under-specification rather than effective conciseness, as the phrase adds no value beyond the 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?

The tool has 4 parameters, no output schema, and no annotations, yet the description offers no explanation of popular criteria, default period, pagination, or return values. This is completely inadequate for the tool's 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% with each parameter (page, period, orderBy, countryCode) having a description, so the baseline is 3. The tool description adds no additional parameter context, but the schema already handles the semantic burden.

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 'Get popular videos' is a direct restatement of the tool name and provides no platform, source, or definition of 'popular.' It fails to distinguish this from sibling tools like scrapecreators_get_popular_creators or scrapecreators_get_popular_songs.

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

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

No guidance is provided on when to use this tool versus alternatives. The description gives no context about suitable scenarios, prerequisites, or advantages over any of the many sibling get_* and scrapecreators_* 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?

Annotations are absent, so the description carries the full burden of behavioral disclosure. It does not state that the operation is read-only, describe the return format, mention required permissions, or note any rate limits or side effects. The phrase 'Get Song Details' simply restates the name without revealing observable 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?

Three words is under-specification, not conciseness. The description adds no information beyond the tool name and fails to earn its place; an appropriate description would at least define the resource scope or the output expectation.

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 no output schema and no annotations, yet the description does not explain what 'song details' will be returned. While the single parameter is well documented, the overall context of what the agent can expect from this tool is missing, making it incomplete for an agent to invoke confidently.

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 single parameter clipId has 100% schema description coverage, including a clarifying note that it is a clip ID rather than a song ID. The tool description itself adds no parameter semantics, but with the schema already providing detailed meaning, the 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?

The description 'Get Song Details' is essentially a verbatim restatement of the tool name 'get_song_details', making it a tautology. It adds no specifics about what 'song details' includes, nor does it clarify that the required input is a clipId rather than a songId. It also fails to distinguish itself from related sibling tools like scrapecreators_get_popular_songs or scrapecreators_reels_using_song.

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

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

The description provides no guidance on when to use this tool versus the many alternative scrapecreators_* tools. There is no mention of typical use cases, prerequisites, or exclusions, leaving the agent to infer from the name alone.

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

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

There are no annotations and no description content to disclose behaviors. The description does not say whether this tool returns search results, requires authentication, paginates, or has any side effects. This is a complete transparency failure for a scraper tool.

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

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

One word is maximally short, but this is under-specification rather than conciseness. Every word is wasted because it carries no useful information. There is no structure, front-loading, or purposeful 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?

With no output schema and a two-parameter input, the description must explain what the tool returns and its operational context. It does neither. The agent cannot determine what a Google scrape means, how results are formatted, or when to select this 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 has 100% description coverage for both parameters, providing baseline clarity. However, the description 'Google' adds no extra meaning beyond the schema, and does not contextualize the query or region parameters beyond what the schema already states.

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 is exactly 'Google', which is a noun and a tautology restating part of the tool name. It does not specify any verb or resource, leaving the agent to guess that it performs Google searches. It fails to distinguish from the many other scrapecreators_* tools.

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

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

No guidance is provided on when to use this tool vs the dozens of sibling tools. There is no mention of use cases, alternatives, or exclusions. The agent receives zero contextual direction.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but 'Highlights Details' reveals nothing about side effects, output format, required permissions, or whether this is a read-only operation. It fails to describe the behavior entirely.

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 words is underspecified, not appropriately concise. The phrase provides no actionable information and is not front-loaded with useful content. It reads as a label rather than a tool description.

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 lack of annotations, output schema, and description content, this is completely inadequate. The tool may be simple (one ID parameter), but the description still needs to explain what 'details' means or what kind of data is returned, which it does not.

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

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

The input schema has one parameter `id` with a clear description: 'The ID of the highlight to get details for'. With 100% schema coverage, the baseline is 3, and the description adds no additional semantic value beyond what the schema already states.

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 'Highlights Details' is a noun phrase that essentially restates the tool name 'scrapecreators_highlights_details'. It lacks a verb or explicit action, making it a tautology rather than a clear statement of purpose.

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

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

The description provides no guidance on when to use this tool or how it differs from the many sibling tools like scrapecreators_story_highlights or scrapecreators_postreel_info. There is no mention of prerequisites, alternatives, or 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 full responsibility for behavioral disclosure. It reveals nothing: no mention of what data is returned, whether it performs scraping, authentication needs, rate limits, or side effects. The single word 'Instagram' discloses zero behavioral traits.

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 word is maximally short but this is under-specification, not conciseness. There is no front-loaded explanation, no structure, and no useful content. It earns a 2 because it is not a broken or rambling description, but it is a placeholder rather than a deliberate concise statement.

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 and no annotations, the description must explain what the tool returns and how it behaves. It provides none of that. For a tool likely fetching Instagram data, the description is wholly insufficient to guide an agent.

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

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

The input schema has 100% coverage with explicit descriptions ('Instagram handle', 'Set to true for a trimmed response'). Per rubric, high schema coverage warrants a baseline of 3. The description adds no additional parameter meaning, but the schema already provides adequate semantics.

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 is exactly 'Instagram' – a single platform name, not a verb or resource. It fails to state what the tool does with Instagram data (e.g., scrape, fetch profile, retrieve posts). It is less informative than the tool name 'scrapecreators_instagram' and provides no distinction from sibling tools like scrapecreators_facebook or scrapecreators_tiktok.

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

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

There is no guidance on when to use this tool versus alternatives. The description does not mention any context, prerequisite, or exclusions among the many scrapecreators 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 must disclose behavioral traits. The single word 'Kick' reveals nothing about side effects, data returned, rate limits, or error conditions, leaving the agent entirely in the dark.

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 short, but this is under-specification rather than effective conciseness. A single word that repeats the tool name does not earn its place; it fails to convey any functional 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 scraping tool with no output schema and many sibling tools, a one-word description is completely inadequate. The agent cannot infer what data will be returned, what platform specifics are involved, or how this differs from similar tools like scrapecreators_clip.

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 only parameter 'url' with 'Kick clip URL' (100% coverage), so the schema carries the burden. The description 'Kick' adds no extra meaning, but the baseline of 3 applies given the full schema coverage.

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 is simply 'Kick,' which merely restates the platform name and gives no indication of what the tool does. It lacks a verb and resource, making it tautological with the tool name and indistinguishable from many other scrapecreators_* tools.

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

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

There is no guidance on when to use this tool versus alternatives. With siblings like scrapecreators_clip and scrapecreators_channel_videos, the description offers no context for selection, prerequisites, or 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, and the description gives no behavioral information. There is no disclosure of what the tool does, side effects, rate limits, or expected output. The description carries zero burden of transparency.

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 word, which is not concise specification but rather severe under-specification. It does not front-load any useful action or context, and a single word does not earn its place as a meaningful description.

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 tool with one parameter and no output schema, the description should at least state the purpose. The word 'Komi' provides no actionable context, leaving the agent unable to understand the tool's function, inputs, or outputs. This is completely inadequate.

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 has 100% description coverage for the only parameter, 'url', described as 'URL to Komi page'. Since the schema already documents the parameter, the baseline is 3; however, the description adds no additional meaning beyond the schema, so it cannot score higher.

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 is simply the word 'Komi', which is a proper noun and does not state any verb, action, or resource. It fails to distinguish this tool from its many scrapecreators siblings, and is essentially a tautology of the tool name.

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

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

There is no guidance on when to use this tool vs any alternative. The description does not mention context, prerequisites, or exclusions, leaving the agent with no basis to select this tool over similar scrapecreators 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 are present, and the description carries the full burden of behavioral disclosure. It says nothing about what the tool returns, whether it is read-only, what happens on errors, or any side effects. The description adds zero behavioral context.

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

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

The description is extremely short, but this is not conciseness — it is under-specification. A single noun 'Linkbio' does not form a coherent tool description. The structure is essentially absent, providing no actionable 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 one parameter and no output schema or annotations, the description is entirely inadequate. It fails to explain the tool's purpose, behavior, return value, or any usage context. This is comparable to the low-quality examples provided.

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% for the single 'url' parameter, which is described as 'URL to Linkbio (lnk.bio) page'. The tool description 'Linkbio' adds no additional meaning beyond the schema. Per the baseline for high schema coverage, a 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 is only 'Linkbio' — a bare noun with no verb or action. It does not state what the tool does, e.g., 'Scrape a Linkbio page'. It fails to distinguish itself from sibling tools like scrapecreators_linktree, and offers no specific resource or operation.

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 usage context is provided. The description does not mention when to use this tool over alternatives, nor any prerequisites or exclusions. It is impossible for an agent to know when this tool is the right choice among the many scrapecreators_* 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 must disclose behavioral traits. It says nothing about what the tool does, what data it returns, whether it is a read operation, or any side effects. The description sheds zero light on 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?

A one-word description is under-specification, not conciseness. It is too terse to be useful, and while there is no waste, it fails to convey necessary 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?

Despite the tool having only one parameter, there is no output schema, no annotations, and the description explains nothing about return values, expected behavior, or use cases. The description is practically empty and inadequate for an agent to understand the tool.

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

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

The input schema has 100% coverage; the parameter 'url' is described as 'LinkedIn profile URL'. The baseline of 3 is appropriate because the schema documents the parameter, even though the tool description adds no parameter-related 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 is simply 'LinkedIn' - a noun naming the platform, not a description of what the tool does. It does not state any verb or resource beyond what the tool name already implies. It is effectively a tautology and gives no specific functionality.

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

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

There is no guidance on when to use this tool versus the many similar scrapecreators_* tools. No context, no exclusions, no mention of alternatives. The user is left without any information about the intended use case.

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