xpay✦ Marketing Collection

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 offers minimal information. It does not indicate whether hooks are returned randomly or deterministically, what happens if no matches exist, or what format the response takes.

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, efficient sentence of eight words that front-loads the action verb. Every word earns its place with zero redundancy 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?

Given the tool's simplicity (three flat parameters, 100% schema coverage) and lack of output schema, the description is minimally adequate. However, it could improve by briefly explaining what constitutes a 'hook' in this context or noting that results are paginated via the limit parameter.

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

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

Schema coverage is 100%, so the schema already documents all three parameters adequately. The description adds implicit value by using 'and/or' to suggest these are optional filters, matching the schema's zero required parameters, but does not elaborate on valid values or syntax 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 uses a specific verb ('Find') and clear resource ('social media hooks'), and identifies the filtering dimensions ('by network and/or category'). However, it does not explicitly distinguish from sibling tool 'get-network-categories-for-hooks', which returns metadata 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 like 'get-network-categories-for-hooks' or the various 'scrapecreators' content tools. There are no prerequisites, exclusions, or conditions 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 carries the full burden. It successfully discloses the return value ('Returns any flagged phrases found in the text') to compensate for the missing output schema. However, it omits explicit read-only safety guarantees or details about what constitutes a 'problematic' phrase.

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

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

Two sentences total, both earning their place: the first establishes purpose and scope, the second discloses the return behavior. Front-loaded with the action verb and no redundant or filler text.

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

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

For a single-parameter validation tool without output schema or annotations, the description is adequately complete. It compensates for the missing output schema by describing the return value, and the 100% schema parameter coverage handles input semantics.

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%, providing a complete baseline. The description mentions 'Check text' which aligns with the schema but does not add additional semantic details (format requirements, length limits, encoding) 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 uses a specific verb ('Check') and resource ('text') with a clear value proposition ('make content more human and less AI-like'). It effectively distinguishes this content validation tool from SEO and social media scraping siblings in the tool list.

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?

While there are no explicit 'when to use' statements or named alternatives, the specific purpose ('avoided to make content...less AI-like') provides clear implied usage context. The agent can infer this is for editing/refining content before publication.

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 successfully discloses that the response includes 'tweet examples,' adding context about output content. However, it omits safety characteristics (read-only status), error behaviors (not found scenarios), or rate limit considerations.

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, front-loaded sentence with zero redundancy. Every phrase earns its place: 'Get' (action), 'detailed information' (depth), 'specific voice archetype' (resource), and 'including tweet examples' (distinguishing output feature).

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

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

Given the tool's low complexity (1 string parameter, no nested objects) and lack of output schema, the description provides minimum viable context by hinting at output content via 'tweet examples.' However, it leaves 'detailed information' undefined and doesn't clarify what other fields might be returned.

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%, providing the parameter name, type, and examples ('AUTHORITY', 'COMEDIAN'). The description adds no explicit parameter semantics, but baseline 3 is appropriate when the schema is already comprehensive.

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

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

The description clearly identifies the action ('Get'), resource ('voice archetype'), and scope ('detailed information...including tweet examples'). It distinguishes from sibling 'list-archetypes' by emphasizing 'specific' and details the unique content type returned (tweet examples), though it could explicitly name the sibling contrast.

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 by the phrase 'specific voice archetype'—suggesting this requires a known identifier versus listing all archetypes—but lacks explicit guidance on when to use this versus 'list-archetypes' or prerequisites like needing to know valid archetype names beforehand.

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 disclosure burden. It states the tool retrieves 'detailed information' but does not clarify what that includes (templates, examples, structure?), nor does it mention caching, 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, efficient sentence of 11 words that leads with the action verb. While appropriately sized for the input schema complexity, the extreme brevity leaves gaps given the lack of output schema and annotations.

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 simple 2-parameter structure with complete schema coverage, the description is minimally adequate. However, it lacks explanation of return values (no output schema exists) and fails to contextualize the tool's relationship to listing alternatives, leaving operational gaps.

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

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

With 100% schema description coverage, the parameters are fully documented in the schema itself. The description references both 'network' and 'framework' concepts but adds no additional semantic value (format details, valid combinations) beyond what the schema already provides. Baseline 3 is appropriate.

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

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

The description uses a specific verb ('Get') and clearly identifies the resource (copywriting framework) and scope (for a network). It implicitly distinguishes from sibling 'list-copywriting-frameworks' by emphasizing 'specific'. However, it lacks detail on what 'detailed information' entails.

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 like 'list-copywriting-frameworks'. It fails to mention the prerequisite of knowing valid framework names beforehand or when retrieval versus listing is appropriate.

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

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

With no annotations provided, the description carries full burden but discloses nothing about return format (ISO codes vs. names), data freshness, list size, or rate limiting. The agent cannot infer if this is static data or dynamically filtered.

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 sentence with no wasted words; appropriately brief for a simple enumeration tool. However, the extreme brevity comes at the cost of omitting useful context, preventing a perfect score.

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?

Adequate for a zero-parameter list tool, but lacks description of return structure (objects vs. strings) and meaning of 'supported' in this specific domain. Without output schema or annotations, the description should have included at least a hint about the return format.

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?

Zero parameters exist (empty schema), so per calibration guidelines, baseline is 4. The description appropriately does not invent parameters, and the schema coverage is trivially complete at 100%.

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 provides a basic verb ('Get') and resource ('list of supported countries'), but 'supported' lacks domain context—supported for what purpose? It does not differentiate from siblings like get_currencies or clarify the service domain, leaving the scope ambiguous despite being grammatically clear.

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

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

No guidance provided on when to use this tool versus alternatives (e.g., whether this applies to shipping, billing, or content targeting). No mention of prerequisites, caching considerations, or related sibling tools that might return country-related data.

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, yet it fails to mention whether this is a read-only operation, what format the balance is returned in, rate limits, or whether the balance is real-time or cached. 'Get' implies reading but lacks explicit safety or 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 consists of a single, efficient sentence that immediately communicates the tool's purpose without redundant words or wasted space. It is appropriately front-loaded with the essential 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 the tool's simplicity (zero parameters) and lack of output schema or annotations, the description minimally suffices by identifying what is retrieved. However, it should ideally describe the return value format (e.g., numeric balance, currency) since no output schema exists to document this.

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 contains zero parameters, establishing a baseline score of 4 per the evaluation rules. The description correctly implies no user input is needed by focusing solely on the retrieval action without referencing parameters.

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 (account's credit balance). However, it uses the generic verb 'Get' rather than a more specific alternative like 'Retrieve', and does not explicitly differentiate from siblings, though the credit-related functionality is unique among the listed 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 provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites such as authentication requirements or when credit checks should be performed. It solely states what the tool does without contextual usage 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. While 'Get' implies a read-only operation, the description doesn't clarify whether this returns a static or dynamic list, what fields are included (codes, symbols, names), rate limiting, or whether the data is cached.

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 appropriately brief at five words, with no redundant or wasteful language. However, it stops short of being maximally useful—a single additional phrase indicating the return format or scope would improve utility without sacrificing 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?

For a simple parameterless tool, the description covers the bare minimum. However, given the lack of an output schema, it should ideally describe what the returned list contains (e.g., currency codes, full names, symbols) and the approximate size of the dataset to set caller 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?

The input schema contains zero parameters, which establishes a baseline score of 4 per the rubric. The description appropriately doesn't invent parameters that don't exist, though it could mention that no filtering is required or supported.

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 clear verb ('Get') and resource ('list of supported currencies'), making the basic function obvious. However, it lacks specificity about what system or service these currencies are 'supported' by, and doesn't explicitly differentiate from siblings like get_countries or get_credits, though the resource name implies the distinction.

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, nor does it mention prerequisites, caching considerations, or data freshness. Given it's a parameterless lookup tool, some context about when this should be called (e.g., before currency conversion operations) would be helpful.

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, yet it fails to mention whether results are real-time or cached, pagination behavior, rate limit implications, or what data fields are returned in the response.

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, efficient sentence with no filler words. However, its extreme brevity contributes to its insufficiency—it wastes no words but fails to earn its place with substantive 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?

Given the lack of output schema and the presence of multiple similar sibling tools, the description should clarify the output format and differentiation from related functions. As written, it leaves significant gaps in the agent's understanding of the tool's complete behavior.

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 ('domain' and 'num'). The description adds no additional semantic context beyond the schema, meeting the baseline expectation when schema documentation is complete.

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

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

The description states the basic action ('Get backlinks') and resource ('domain'), but does not distinguish from sibling tools like 'get_page_backlinks' or 'get_unique_domain_backlinks', which is critical given the multiple backlink-related functions available.

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 provided on when to use this tool versus alternatives like 'get_unique_domain_backlinks' (which likely returns deduplicated referring domains) or 'get_page_backlinks' (URL-level analysis). The agent cannot determine which backlink tool is appropriate for a given use 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 provided, the description carries the full burden of behavioral disclosure but fails to deliver. It does not explain what 'ranks for' entails (position data, search volume, SERP features), data freshness, rate limits, or the structure of the returned keyword list. The only behavioral hint is the implied read-only nature of the 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?

The description is extremely concise at only six words, with no filler or redundancy. It is appropriately front-loaded with the action verb. However, it may be excessively terse given the lack of supporting annotations or output schema, though this concerns completeness rather than conciseness itself.

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 insufficiently complete. It fails to describe the return values (what data points accompany each keyword?), pagination behavior, or geographic constraints beyond the country parameter. For a tool with multiple siblings, additional context about the data source or ranking methodology would be necessary for robust agent decision-making.

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 all three parameters (domain, num, country). The description adds no additional parameter semantics beyond the schema, but given the high schema coverage, this meets the baseline expectation without penalty or credit.

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 ('keywords that a domain ranks for'), which effectively communicates the SEO research purpose. However, it does not explicitly differentiate from siblings like 'get_keyword_data' or 'get_url_keywords', relying on the tool name to convey the domain-level scope.

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' (page-level) or 'get_related_keywords'. There are no stated prerequisites, exclusions, or workflow recommendations to help the agent select this tool correctly from the extensive list of keyword-related 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 provided, so description carries full burden. Fails to disclose whether this is read-only, what specific traffic data is returned (visits, pageviews, unique visitors), or any rate limiting. Only implies a retrieval 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?

Extremely brief at five words. While efficient and front-loaded, the extreme brevity leaves significant gaps given the lack of output schema or annotations. No wasted words, but arguably undersized.

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?

Without an output schema or annotations, the description should explain what traffic metrics are returned or behavioral constraints. As is, it leaves the agent blind to the return format and data scope despite the simple 2-parameter input.

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 ('domain' and 'country'), so the schema carries the semantic weight. Description adds no parameter-specific context beyond the schema, meeting the baseline for high-coverage schemas.

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?

States the basic action ('Get') and resource ('traffic metrics for a domain'), but lacks specificity on what distinguishes this from sibling tool 'get_url_traffic' or what metrics are included. Adequate but minimal.

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

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

Provides no guidance on when to use this versus 'get_url_traffic' or other domain analysis tools like 'get_domain_keywords'. No prerequisites or conditions 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 carries the full burden. It successfully discloses what data is returned (Volume, CPC, competition), but omits operational details such as data freshness, API costs/credits consumed, rate limits, or error handling 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?

Single sentence, nine words, front-loaded with action verb 'Get'. Zero redundancy or waste. Despite brevity that impacts completeness, the structure is exemplary 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?

Lacking both output schema and annotations, the description only partially compensates by listing the three metrics returned. Missing context includes: whether metrics are estimates or exact, geographic coverage implications, and the structure/format of the returned data.

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

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

The input schema has 100% description coverage (country, currency, keywords), establishing a baseline score of 3. The description adds no parameter-specific guidance (e.g., valid country code formats, optimal keyword list size), relying entirely on the schema documentation.

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 specific metrics retrieved (Volume, CPC, competition) and the target (keywords). However, it does not explicitly distinguish this metric-retrieval tool from sibling discovery tools like 'get_related_keywords' or 'get_pasf_keywords' that may also return keyword 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 provided on when to use this tool versus alternatives. The description fails to indicate that this is for analyzing provided keywords versus discovering new ones (contrast with get_related_keywords) or analyzing domain-specific keywords (contrast with get_domain_keywords).

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 disclosure burden. It fails to describe what the categories look like (enums vs. free text), approximate volume, or whether results are cached. The read-only nature is implied by 'Get' but not confirmed.

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 sentence of 9 words is appropriately brief and front-loaded with the verb 'Get'. No redundant filler, though brevity comes at the cost of omitting the 'hooks' 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?

For a single-parameter tool with complete schema coverage and no output schema, the description is minimally viable. However, it misses the domain context that these are content 'hook' categories (angles/templates), which is essential for an agent to select this over other category-fetching 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 has 100% coverage with specific examples (twitter, instagram, linkedin, tiktok, youtube), so the description does not need to add parameter semantics. It baseline meets expectations by mentioning 'social media network'.

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

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

The description states it gets 'categories for a specific social media network' but critically omits 'hooks' (from the tool name), leaving the domain purpose ambiguous. It does not explain what these categories are used for or how they differ from the 'find-hooks' sibling tool.

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 provided on when to use this versus 'find-hooks' or other content generation tools. No prerequisites, rate limit warnings, or sequencing advice (e.g., whether to call this before finding hooks).

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 offers minimal information. It does not describe the output format, pagination behavior, data freshness, or what constitutes a 'backlink' in this context (e.g., referring domains vs. individual URLs).

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

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

The description is extremely concise at only six words with no redundant or wasted content. However, given the lack of annotations and output schema, it borders on underspecification rather than optimal 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?

For a simple two-parameter tool with complete schema coverage, the description is minimally adequate. However, with no output schema provided, the description should ideally hint at the return structure or data richness, 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?

Schema description coverage is 100%, establishing a baseline of 3. The description mentions 'specific URL' which loosely maps to the 'url' parameter, but adds no additional semantic context, examples, or format specifications 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 states a clear verb ('Get') and resource ('backlinks for a specific URL'), accurately describing the core function. However, it fails to distinguish from siblings like 'get_domain_backlinks' or 'get_unique_page_backlinks', leaving ambiguity about when to use page-level versus domain-level analysis.

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 provided on when to use this tool versus alternatives (e.g., 'get_domain_backlinks' for entire domains or 'get_unique_page_backlinks' for deduplicated results). No mention of prerequisites, rate limits, or cost considerations.

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 only implies read-only safety via the verb 'Get'. It fails to disclose rate limits, caching behavior, authentication requirements, or the structure/format of returned data.

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, efficient 9-word sentence that front-loads the action ('Get') and immediately identifies the resource. There is no redundant or wasted language.

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 2-parameter tool with flat structure, the description adequately identifies the core function. However, given the absence of an output schema and annotations, it lacks necessary context about what data structure or fields the tool returns, leaving the agent uncertain about the output format.

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 ('Seed keyword...' and 'Number of results...'), so the description is not required to compensate. It mentions 'seed keyword' which aligns with the schema, adding no additional syntax, format examples, or semantic constraints 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 clearly states the tool retrieves 'People Also Search For' keywords using a specific SEO term (PASF) that distinguishes it from the sibling tool 'get_related_keywords'. However, it doesn't explicitly clarify when to choose this over similar keyword tools like 'get_keyword_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?

The description provides no guidance on when to use this tool versus alternatives such as 'get_related_keywords' or 'get_keyword_data'. There are no stated prerequisites, exclusions, or conditions for use.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It fails to mention what constitutes 'related' (semantic similarity, search volume correlation, etc.), return format, error handling for invalid keywords, idempotency, or rate limits.

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

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

The single sentence is efficiently structured without redundancy. However, it is under-loaded for the complexity of the tool domain, leaving significant informational gaps rather than being appropriately concise.

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 should explain what gets returned (e.g., array of strings vs. objects with metrics) and the nature of the keyword relationships. It provides neither, leaving critical gaps in the contract.

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 'keyword' and 'num' fully documented in the schema. The description mentions 'seed keyword' which aligns with the schema but adds no additional syntax guidance, examples, or clarification on the 'max 1000' constraint behavior.

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

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

The description clearly states the tool retrieves 'related keywords' using a 'seed keyword', providing specific verb and resource. However, it does not distinguish from siblings like 'get_pasf_keywords' or 'get_keyword_data' which also retrieve keyword variations, leaving ambiguity about the semantic relationship (LSI, semantic, search-based, etc.).

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 like 'get_pasf_keywords', 'get_keyword_data', or 'get_url_keywords'. There are no stated prerequisites, exclusions, or workflow positioning.

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 fails to specify the return format (string vs object), whether truncation indicators (ellipsis) are added, or if the operation is idempotent.

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 efficiently conveys the core function. It is slightly wordy with 'for previewing purposes' at the end, but generally avoids waste.

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 simple 3-parameter schema with full coverage and no output schema, the description adequately covers the primary use case. However, it should disclose the return value format and truncation behavior to be 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% description coverage with clear enums. The description provides the high-level context but does not add semantic details beyond what the schema already documents (e.g., it doesn't clarify the YouTube-specific contentType behavior).

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 resource ('text'), clearly indicating it shortens content to fit platform-specific 'before fold' limits. However, it does not explicitly differentiate from the similar sibling 'validate-content-before-fold'.

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?

While it mentions the context ('for previewing purposes'), it provides no guidance on when to use this tool versus alternatives, particularly the sibling 'validate-content-before-fold' which likely checks limits without truncating.

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 provides minimal context. It mentions the HyperFeed API source but fails to disclose rate limits, caching behavior, what 'trending' means algorithmically, time windows, or the structure/format of returned content.

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

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

The single sentence is efficient with no wasted words, and the information density is high. However, extreme brevity comes at the cost of necessary context given the complex ecosystem of sibling tools, warranting slightly less than a perfect score.

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 the presence of numerous similar social media tools, the description is insufficient. It fails to explain the return data structure, the specific value proposition of HyperFeed versus other data sources, or how trending is calculated, leaving agents under-equipped to invoke the tool effectively.

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

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

Schema description coverage is 100%, with clear descriptions for both 'limit' and 'networks' parameters including examples. The description text itself does not mention parameters, but since the schema is fully self-documenting, it meets the baseline expectation without adding additional semantic value.

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

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

The description clearly states the verb (Fetch), resource (trending social media content), and specific source (HyperFeed API). However, it fails to differentiate from numerous sibling social media tools like scrapecreators_twitter or scrapecreators_trending_feed, leaving agents uncertain when to prefer this over 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?

No guidance provided on when to use this tool versus the extensive list of sibling social media scrapers (e.g., scrapecreators_reddit, scrapecreators_twitter). No mention of prerequisites, authentication requirements, or filtering capabilities beyond the basic parameter descriptions.

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 fails to state whether this is a read-only operation, what data structure is returned, or any rate limits. While 'Get' implies reading, it does not explicitly confirm safety or idempotency.

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 brief at four words, which prevents bloat, but it is under-specified rather than appropriately concise. The single sentence fails to earn its place by adding no information beyond the tool name itself.

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 existence of similarly-named sibling tools (particularly 'get_domain_backlinks'), the description is incomplete because it fails to clarify the distinction between fetching unique domain-level backlinks versus all backlinks. Without an output schema, this omission leaves critical functionality ambiguous.

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 ('domain' and 'num'), so the baseline score applies. The description adds no additional parameter context, but the schema adequately documents requirements without further elaboration 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 'Get unique domain backlinks' is a tautology that merely restates the tool name with spaces added. It fails to distinguish this tool from the sibling 'get_domain_backlinks' or explain what constitutes a 'unique' domain backlink versus a regular backlink.

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 like 'get_domain_backlinks' or 'get_unique_page_backlinks'. There are no prerequisites, exclusions, or contextual clues for proper invocation.

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 burden but discloses no behavioral traits. It doesn't explain what 'unique' means in this context, mention pagination behavior, rate limits, data freshness, or return format. The max 1000 limit from the schema is not contextualized.

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

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

The single sentence is not wasteful, but represents under-specification rather than efficient conciseness. Given the presence of highly similar sibling tools requiring differentiation, the brevity leaves critical gaps rather than earning efficiency points.

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?

Incomplete for a tool with similar siblings and no output schema. Missing: differentiation from 'get_page_backlinks', explanation of uniqueness criteria, return value structure, and any behavioral constraints. The description meets minimum viable definition but leaves significant gaps for proper tool invocation and 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% (both 'url' and 'num' are documented in the schema). The description adds no parameter-specific guidance beyond the schema, but baseline 3 is appropriate given the schema completeness.

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

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

The description states the basic action (Get unique backlinks) and target (specific URL), but fails to distinguish from siblings like 'get_page_backlinks' and 'get_unique_domain_backlinks'. It mentions 'unique' without clarifying what constitutes uniqueness (domain-level vs URL-level deduplication), leaving ambiguity about the tool's specific value proposition.

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 provided on when to use this tool versus the similar 'get_page_backlinks' or domain-level alternatives. The agent cannot determine whether 'unique' filtering is appropriate for their use case or what trade-offs exist between these similar 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 full responsibility for behavioral disclosure but provides none. It doesn't indicate whether this is a read-only operation, mention rate limits, data freshness, or what the return structure contains. The word 'Get' implies safety but doesn't confirm it.

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?

Extremely concise at six words. No wasted language and the key verb appears first. However, given the absence of annotations and output schema, this brevity may constitute under-specification rather than efficient communication.

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?

Inadequate for a tool with no annotations and no output schema. With many similar SEO siblings (get_domain_keywords, get_url_traffic, get_keyword_data), the description fails to disambiguate use cases or hint at return value structure. Should explain what 'ranks for' means in this 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?

Input schema has 100% description coverage, documenting all three parameters (url, num, country) adequately. The description mentions 'URL' which aligns with the required parameter, but adds no additional context about parameter interactions or format 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 clearly states the action (Get keywords) and scope (that a URL ranks for), distinguishing it from sibling tools like get_domain_keywords by specifying URL-level analysis. However, it assumes the agent understands 'ranks for' implies search engine rankings without specifying the data source.

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 on when to use this tool versus siblings like get_domain_keywords or get_keyword_data. No mention of prerequisites (e.g., valid URL format) or when not to use it. The agent must infer applicability 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 provided, so description carries full burden. While 'Get' implies read-only, the description fails to specify what traffic metrics are returned (visits, pageviews, unique visitors), time range covered, or data freshness. Omits error handling for invalid URLs.

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?

Extremely concise at 6 words with no filler. However, the brevity crosses into under-specification given the lack of output schema and complex sibling ecosystem. Efficient structure but insufficient 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?

Inadequate for the tool's context. With siblings offering domain-level, keyword-level, and backlink analysis, the description should clarify URL-specific scope and hint at return value structure (since no output schema exists). Currently insufficient for confident 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 has 100% description coverage ('URL to analyze' and country code details), so the description does not need to compensate. The description adds no parameter-specific guidance, meeting the baseline for well-documented schemas.

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?

States the basic action (get traffic metrics) and target (URL), but fails to differentiate from sibling tool `get_domain_traffic` or clarify URL-specific scope. Slightly better than tautology but lacks specificity expected in this tool ecosystem.

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

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

Provides no guidance on when to use this tool versus alternatives like `get_domain_traffic` or `get_url_keywords`. No mention of prerequisites, rate limits, or data availability constraints.

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 but only mentions quality characteristics ('best-in-class text rendering'). It fails to disclose operational traits: output format, rate limits, cost implications, latency, or whether generated images are persisted vs transient.

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?

Extremely concise single-sentence format with no wasted words. Key information ('AI image generation') is front-loaded. However, for a 10-parameter tool with complex capabilities, this brevity may be insufficient rather than optimally concise.

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 complex image generation tool supporting inpainting, style references, and resolution controls, the description is inadequate. It omits major capabilities visible in the schema (inpainting, style_reference_images) and provides no output format guidance despite no output schema being present.

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

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

Schema description coverage is 100%, so the schema adequately documents all 10 parameters (e.g., mask logic, seed purpose). The description adds no parameter-specific guidance, meeting the baseline expectation when schema coverage is complete.

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

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

The description clearly identifies the core function ('AI image generation') and distinguishes it from siblings (all text/data scraping tools). The 'best-in-class text rendering' phrase effectively differentiates this image tool. However, it doesn't clarify that the tool supports both generation and inpainting modes evident in the schema.

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 provided on when to use this tool versus alternatives (though none exist in siblings), nor when to use specific features like inpainting (mask+image) versus standard generation. No mention of prerequisites like image URLs for inpainting mode.

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 successfully indicates what data is returned ('names and descriptions'), but omits other behavioral traits like pagination, rate limiting, or caching behavior that would help an agent understand operational constraints.

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 consists of a single efficient sentence that front-loads the action ('Get a list') and immediately specifies the scope and return content. There is no redundant or wasted language; every word earns its place.

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

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

Given the tool's low complexity (no input parameters) and lack of output schema, the description adequately compensates by specifying the structure of returned items ('names and descriptions'). For a simple catalog listing tool, this provides sufficient context for invocation, though mentioning pagination 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 and 100% schema description coverage of those zero parameters. Per the baseline rules for parameterless tools, this earns a default score of 4, as there are no parameter semantics to clarify beyond what the empty schema already communicates.

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 specific verb 'Get a list' and resource 'voice archetypes' to clearly define the tool's function. It implicitly distinguishes from sibling 'get-archetype' by emphasizing 'all available' (bulk retrieval vs. singular), though it doesn't explicitly name the alternative.

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 (retrieving the complete catalog of archetypes) through the phrase 'all available', but lacks explicit when-to-use guidance or comparison to the singular 'get-archetype' alternative. Users must infer when to prefer this over the specific getter.

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 successfully clarifies that the tool returns both framework names and their descriptions (not just identifiers), but lacks other behavioral details such as pagination behavior, rate limits, or caching characteristics typical for a read-only list 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?

The description is a single, efficient sentence of 14 words with no redundancy. It is front-loaded with the action ('Get a list') and immediately qualifies the resource and scope, making it easy to parse quickly.

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

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

Given the tool's simplicity (single parameter, clear list operation) and lack of output schema, the description is reasonably complete. It clarifies that 'descriptions' are included in the return payload, which helps the agent understand the data richness. A minor gap remains regarding the return structure (array vs object) or quantity limits.

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 'network' parameter is fully documented with valid values). The description references 'specific social media network' which aligns with the parameter, but adds no additional semantic context (formatting rules, case sensitivity, default behavior) beyond what the schema already provides. Baseline 3 is appropriate for high 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 clearly states the tool retrieves copywriting frameworks with their descriptions for a specific network, using specific verbs ('Get a list'). However, it does not explicitly differentiate from the sibling tool 'get-copywriting-framework' (singular), which likely retrieves a specific framework versus this listing 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?

The description provides no guidance on when to use this tool versus alternatives like 'get-copywriting-framework' or other content generation tools. There are no stated prerequisites, exclusions, or workflow guidance (e.g., 'use this to browse frameworks before selecting one').

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, yet the description discloses nothing about behavioral traits: whether this performs web scraping, API calls, or database lookups; what data structure it returns; whether there are rate limits or authentication requirements; or if there are side effects. The agent has zero behavioral context 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?

While only two words long, this represents under-specification rather than efficient conciseness. As with the calibration example 'Process', brevity here indicates missing information rather than disciplined editing. Every sentence should earn its place, but this description barely constitutes a sentence and fails to earn any informational 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 complexity of the sibling ecosystem (multiple ad-related tools with overlapping names) and the lack of output schema, the description should explicitly clarify scope and return value. It fails completely to address how this tool differs from 'scrapecreators_ad_details_get' or what specific ad attributes are retrieved.

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?

With 100% schema description coverage (the single 'url' parameter is documented as 'The url of the ad'), the description is not required to compensate. The description adds no parameter-specific context, but the schema adequately defines the input, meeting the baseline expectation.

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 tautology of the tool name (scrapecreators_ad_details), merely removing the prefix and underscores. While it confirms the domain involves advertisements, it fails to specify what 'details' entails, what action is performed (scraping, fetching, analyzing), or how it differs from siblings like 'scrapecreators_get_ad' or 'scrapecreators_ad_details_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?

No guidance is provided for when to use this tool versus the numerous alternatives (scrapecreators_get_ad, scrapecreators_ad_details_get, scrapecreators_search_ads, etc.). Given the high similarity between sibling names, the absence of selection criteria creates significant ambiguity for the agent.

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 provides none. It does not specify supported ad platforms, what data is returned, rate limits, or authentication requirements, leaving the agent blind to operational characteristics.

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 brief, the two-word description constitutes underspecification rather than effective conciseness. It fails to earn its place by providing actionable information beyond the tool name itself.

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?

Completely inadequate for a data retrieval tool with no output schema. The description omits what ad details are returned, how to obtain valid URLs, expected response formats, and error conditions, providing no operational context for successful 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 100% description coverage for its single 'url' parameter, establishing baseline sufficiency. The description adds no semantic value beyond the schema, but does not need to given the complete schema documentation.

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 tautological, merely restating the tool name without adding specificity. It fails to distinguish this tool from similar siblings like 'scrapecreators_ad_details' or 'scrapecreators_get_ad', leaving the agent uncertain about which to select for specific retrieval scenarios.

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 regarding when to use this tool versus alternatives, nor are prerequisites mentioned. Given the crowded namespace with multiple ad-related tools, the absence of selection criteria forces the agent to guess based on naming conventions 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, and the description discloses nothing about behavioral traits: what data source is searched, what the return format is, whether there are rate limits, or if the operation is read-only. The description carries 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?

While brief (two words), this represents under-specification rather than efficient conciseness. The description wastes its limited space restating the tool name instead of front-loading valuable context about the tool's specific function.

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 being a single-parameter tool, the description is inadequate given the complex ecosystem of sibling scraping tools. With no output schema, no annotations, and no behavioral details, the agent lacks sufficient information to invoke this tool correctly among the many advertising-related 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 schema has 100% description coverage for the single 'query' parameter. The description adds no semantic information beyond the schema, but since the schema adequately documents the parameter, it meets the baseline expectation.

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 tautology that restates the tool name (scrapecreators_advertiser_search) without adding specificity. It fails to distinguish this from sibling ad-search tools like 'scrapecreators_search_ads', 'scrapecreators_company_ads', or 'scrapecreators_facebook_ad_library'.

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 provided on when to use this tool versus the numerous sibling advertising tools (e.g., scrapecreators_search_ads, scrapecreators_facebook_ad_library). No mention of prerequisites, query syntax, or search scope.

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, yet the description fails to disclose behavioral traits such as data source, scraping methodology, privacy implications, rate limits, or what happens when data is unavailable. The term 'scrape' in the name implies external data fetching, but the description does not confirm this or explain failure modes.

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 two-word description is brief, it represents under-specification rather than efficient communication, failing to earn its place by providing actionable guidance. The extreme brevity leaves critical gaps in understanding rather than delivering high signal density.

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 the complex domain of social media scraping, the description is grossly incomplete. It omits expected return value structure, data availability limitations, and supported platform coverage necessary for safe 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 100% description coverage for its single `url` parameter, which is adequately documented as 'URL to users social profile'. The description adds no additional semantic context, meeting the baseline expectation when the schema is self-documenting.

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 static noun phrase that restates the concept embedded in the tool name without specifying the action (scraping, retrieving, inferring) or target resource. It fails to differentiate from siblings like `scrapecreators_basic_profile` or `scrapecreators_users_audience_demographics` which may also return demographic 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?

The description provides no guidance on when to use this tool versus alternatives such as `scrapecreators_basic_profile` or `scrapecreators_users_audience_demographics`. There are no stated prerequisites, constraints, or conditions for invocation.

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 bears the full burden of behavioral disclosure, yet it reveals nothing about side effects, rate limits, return format, or authentication requirements. The agent cannot determine if this is a safe read-only operation or what data structure to expect from the scrape.

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 brief at only two words, the description represents under-specification rather than efficient conciseness. It fails to front-load any actionable information about the tool's functionality, expected return values, or usage constraints.

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

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

Despite having only one parameter, the tool description lacks any explanation of what data is extracted from Amazon Shop pages or how it differs from product-specific siblings. Without an output schema, the description should characterize the expected return values, which it completely omits.

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 achieves 100% description coverage for its single 'url' parameter, documenting that it expects a URL to an Amazon Shop page. The description adds no additional semantic context (such as URL format examples or validation rules), but the complete schema coverage meets the baseline requirement.

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' merely restates the tool name (minus the 'scrapecreators_' prefix) without specifying what action is performed (scraping, retrieving, validating) or what data is returned. It fails to distinguish this tool from siblings like 'scrapecreators_tiktok_shop' or 'scrapecreators_shop_products'.

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 'scrapecreators_product_details' or 'scrapecreators_shop_products'. No prerequisites, exclusions, or selection criteria are mentioned to aid the agent in 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?

No annotations are provided, and the description carries none of the behavioral burden. It does not disclose whether the operation is read-only, if there are rate limits, caching behavior, or what data fields are returned (e.g., bio, follower count).

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 brief, the description is inappropriately sized—two words cannot adequately describe a tool among 80+ siblings. This is under-specification rather than efficient conciseness; no sentences exist to earn their place.

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

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

Given the rich ecosystem of sibling scraping tools and lack of output schema or annotations, the description is completely inadequate. It fails to define the scope of 'basic' profile data or distinguish this tool's utility within the complex scrapecreators suite.

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 (userId: 'Instagram user id'), establishing a baseline of 3. The description itself adds no semantic value about the parameter, but does not need to compensate given the complete schema documentation.

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' is essentially a tautology of the tool name (scrapecreators_basic_profile) converted to title case. It fails to specify the action (retrieve/fetch/scrape), the platform (Instagram), or what 'basic' entails compared to other profile 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 provided on when to use this tool versus sibling alternatives like scrapecreators_profile_posts, scrapecreators_profile_photos, or scrapecreators_instagram. The description does not indicate prerequisites or filtering capabilities.

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, yet it states nothing about whether the operation is read-only or destructive, what data structure is returned, or any rate limiting considerations. The agent cannot determine if this retrieves public profiles, requires authentication, or performs writes.

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 brief, the single-word description represents under-specification rather than efficient conciseness, as it fails to front-load any actionable information about the tool's function. Every sentence must earn its place by conveying essential operational context, which this placeholder word does not accomplish.

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 simple single-parameter structure but lack of output schema or annotations, the description should explain what Bluesky data is retrieved (profile info, posts, metrics), but it provides no such context. This leaves critical gaps in the agent's understanding of the tool's utility and return values.

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 a single required parameter 'handle' described as 'Bluesky handle', so the description does not need to compensate for schema gaps per the baseline rules. However, the description adds no semantic context beyond the schema, such as expected handle format (with or without @) or validation rules.

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 consists solely of the word 'Bluesky', which merely restates the platform component of the tool name without specifying the action (scrape, retrieve, search) or the resource (profile, posts, etc.). It fails to distinguish this tool from siblings like scrapecreators_twitter or scrapecreators_instagram, leaving the agent uncertain about what data it actually retrieves from Bluesky.

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 select this tool versus alternative social media scraping tools in the scrapecreators_* family. It lacks any mention of prerequisites, required permissions, or specific use cases where this tool is preferred over other platform-specific scrapers.

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 provides none. It does not indicate whether this is a read-only operation, what data is returned, rate limits, or pagination behavior beyond the bare existence of a cursor parameter.

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 single word is concise, it is inappropriately sized for the tool's complexity and represents under-specification rather than efficient communication. It lacks sentence structure and fails to front-load any 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?

For a tool with 3 parameters including pagination (cursor) and a sibling namespace suggesting Pinterest functionality, the description is completely inadequate. With no output schema provided, the description should explain return values but provides no context whatsoever.

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 (url, trim, cursor are all documented), establishing a baseline score of 3. The description 'Board' adds no additional semantic context, examples, or format guidance 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 'Board' is a tautology that restates the resource type without a verb or action. It fails to specify what the tool does (scrapes? retrieves? lists?) and does not distinguish this tool from the sibling 'scrapecreators_user_boards'.

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_user_boards' or 'scrapecreators_pin'. There are no prerequisites, constraints, 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, yet it states nothing about read-only status, rate limiting, data freshness, or the specific platform (YouTube implied by 'Shorts' but not explicit). The pagination behavior implied by continuationToken is undocumented.

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 brief (two words), this represents under-specification rather than efficient conciseness. The description is front-loaded with the resource type but lacks the necessary explanatory content to be useful, failing the 'every sentence should earn its place' standard.

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 4-parameter tool with no output schema and no annotations, the description is completely inadequate. It omits the platform (YouTube), return value structure, authentication requirements, and differentiation from similar scraping tools in the extensive 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?

With 100% schema description coverage, the parameters are adequately documented in the schema itself (sort options, handle/channelId interchangeability, continuation token usage). The description adds no parameter semantics, but the high schema coverage establishes a baseline score of 3.

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

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

The description 'Channel Shorts' is a tautology that restates the tool name without the 'scrapecreators_' prefix. It fails to specify the action (scrape? retrieve? list?) or distinguish 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 provided on when to use this tool versus alternatives (e.g., when to use handle vs channelId, or when to prefer this over the general channel_videos tool). No mention of pagination workflow despite the continuationToken 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 but discloses nothing about read-only status, rate limits, response time implications (mentioned only in schema), or what data structure is returned.

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

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

Two words is insufficient for a tool with 5 parameters and pagination logic. It lacks a front-loaded verb and fails to earn its place as a useful specification.

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

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

Given 5 parameters (none required, implying complex combinations), pagination support, and no output schema, the description is completely inadequate. No guidance on parameter combinations or return values.

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%, documenting all 5 parameters including sort options and continuation tokens. The description adds no parameter context, meeting the baseline for well-documented schemas.

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 that restates the resource without specifying the action (scrape, fetch, list) or platform (YouTube). It fails to distinguish from siblings like scrapecreators_channel_shorts or scrapecreators_youtube.

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

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

No guidance provided on when to use this tool versus alternatives, or how to choose between the handle and channelId parameters (both optional). No mention of pagination workflow despite continuationToken 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 disclosing behavioral traits, yet 'Clip' reveals nothing about whether this is a read-only operation, what data it returns, or any side effects. It fails to specify that it interacts with Twitch clips despite the parameter schema indicating this.

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 not verbose, it suffers from under-specification rather than genuine conciseness. A single word is insufficient to convey the tool's purpose, making it inappropriately sized for the information required.

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?

Even with only one parameter and high schema coverage, the description fails to explain what the tool returns or accomplishes. Without an output schema or annotations, the description needed to compensate but provided no behavioral context whatsoever.

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 (the 'url' parameter is documented as 'Twitch clip URL'), establishing a baseline of 3. The description 'Clip' adds no additional parameter context, syntax details, or usage examples 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 simply 'Clip', which is a tautology that restates the tool name (scrapecreators_clip) without specifying what the tool actually does (e.g., retrieve metadata, download content, or extract data from Twitch clips).

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 provided on when to use this tool versus the numerous sibling tools (e.g., scrapecreators_twitch, scrapecreators_video_info, scrapecreators_transcript). There is no mention of 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 disclosure, yet it states nothing about read-only vs destructive behavior, rate limits, authentication requirements, or pagination behavior (though the cursor parameter implies pagination).

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 brief, the single-word description represents under-specification rather than effective conciseness. No useful information is conveyed in the limited space.

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 similarly-named sibling tools and 100% schema coverage, the description should differentiate this tool's specific function and expected return format, but provides neither.

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 clear descriptions for both 'url' and 'cursor' parameters. The description adds no semantic value beyond the schema, meeting the baseline for high-coverage schemas.

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 'Comments' is a tautology that restates part of the tool name without specifying the action (retrieve, post, analyze?), target platform, or scope. It fails to distinguish from siblings 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 provided on when to use this tool versus alternatives (e.g., scrapecreators_comments_get, scrapecreators_post_comments), prerequisites, or platform 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 provided, the description carries the full burden of behavioral disclosure but provides none. It does not indicate this is a read operation, fails to explain pagination behavior (despite the continuationToken parameter), and omits any mention of rate limits, data limits, or return structure.

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 single-word description is brief, this represents under-specification rather than effective conciseness. The word 'Comments' fails to earn its place by providing actionable information, forcing agents to rely entirely on the tool name and schema inference.

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 3 parameters, pagination support, and no output schema or annotations, the description is completely inadequate. It lacks essential context about the data source (YouTube), return format, and relationship to sibling comment-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?

Schema description coverage is 100%, so the baseline is 3. The schema adequately documents the url and continuationToken parameters. The description adds no additional semantic value beyond what the schema already provides, nor does it clarify the acceptable values for the 'order' parameter.

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 'Comments' is a tautology that restates the tool's subject matter without specifying the action. It fails to indicate whether the tool retrieves, creates, or analyzes comments, and does not distinguish this getter variant from sibling tools like 'scrapecreators_comments' 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 provided on when to use this tool versus alternatives. Given the existence of similarly named siblings (scrapecreators_comments, scrapecreators_post_comments), the lack of differentiation or prerequisites makes selection impossible based on the description 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?

With no annotations provided, the description carries the full burden of behavioral disclosure, yet it states nothing about whether this is a read/write operation, what data structure it returns, rate limits, or authentication requirements. The agent has no information about side effects or resource costs.

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 consists of a single word, which constitutes under-specification rather than effective conciseness. It lacks any sentences that could earn their place through information delivery, failing to meet the standard for appropriately sized descriptions.

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 singular purpose (fetching data about a community) and the existence of related sibling tools, the description provides insufficient context to distinguish its specific utility. The absence of an output schema and annotations further amplifies the description's failure to communicate what the tool actually retrieves.

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?

While the description adds no parameter-specific context, the input schema has 100% description coverage (the single 'url' parameter is documented as 'Community URL'). Per the scoring guidelines, high schema coverage establishes a baseline of 3 even when the description lacks parameter details.

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' is a tautology that restates the final segment of the tool name (scrapecreators_community). It fails to specify what action the tool performs (scrape? fetch? analyze?) or what 'community' refers to in this context (e.g., YouTube Community tab, Facebook Group, etc.).

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 sibling alternatives like scrapecreators_community_post_details or scrapecreators_community_tweets. There are no prerequisites, exclusions, or workflow context 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 present, and the description discloses no behavioral traits. It does not indicate what data structure is returned, whether the operation is read-only, rate limits, or if the tool requires authentication.

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 brief (3 words), the description is under-specified rather than efficiently concise. It front-loads no actionable information, fails to earn its place with useful context, and reads as a placeholder rather than a distilled 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 single-parameter tool without an output schema, the description is still insufficient. It fails to identify the target platform (YouTube), specify what constitutes 'details' (content, engagement metrics, media), or explain the expected return format.

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?

With 100% schema description coverage (the single 'url' parameter is fully documented as 'The URL of the YouTube community post to get'), the description is not required to compensate. However, the description adds no semantic value beyond what the schema already provides, warranting the baseline 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 'Community Post Details' is a tautology that restates the tool name without adding specificity. It omits the action verb (get/retrieve) and fails to distinguish whether this targets YouTube, Reddit, or other platforms despite the schema revealing it is for YouTube.

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

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

No guidance provided on when to use this tool versus siblings like 'scrapecreators_community' (likely a list operation) or 'scrapecreators_post'. No mention of prerequisites such as needing a valid YouTube community post URL versus a standard video URL.

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 zero behavioral context. It does not disclose whether this is read-only, what tweet data is returned (recent vs popular), pagination behavior, rate limits, or what format the 'Community URL' should take. For a data retrieval tool with no annotation coverage, this is 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 two-word description suffers from under-specification rather than efficient conciseness. No information is front-loaded because no actionable information exists. Every sentence (or fragment) fails to earn its place by providing actionable guidance to 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?

Despite having only one parameter and no output schema, the description is inadequate. It fails to explain what constitutes a 'Community' in this context, what data is returned, or how this differs from the 60+ sibling scraping tools. Even for a simple tool, the description lacks minimum viable 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?

With 100% schema description coverage ('Community URL'), the baseline score applies. The description adds no parameter-specific semantics, but the schema sufficiently documents the single required parameter. No additional context about URL format or validation rules is provided in the description.

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' essentially restates the tool name (scrapecreators_community_tweets) without adding specificity. While it identifies the resource type (tweets) and context (community), it fails to distinguish from siblings like 'scrapecreators_community', 'scrapecreators_user_tweets', or clarify what 'Community' means (Twitter/X Communities feature vs general community content).

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

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

No guidance provided on when to use this tool versus alternatives. Given the extensive list of sibling tools (including scrapecreators_twitter, scrapecreators_user_tweets, scrapecreators_community, scrapecreators_tweet_details), the absence of differentiating criteria forces the agent to guess which tool retrieves community-specific tweets versus user timelines or general search.

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 description fails to indicate whether this is a read-only operation, what data source is queried, rate limits, pagination behavior (despite the cursor parameter), or the response structure.

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 brief (two words), the description is inappropriately sized for a 10-parameter filtering tool. It represents under-specification rather than efficient conciseness, failing to front-load any actionable information about the tool's capabilities.

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 10 filter parameters, no output schema, and no annotations, the description is completely inadequate. It lacks explanation of return values, pagination mechanics, or the relationship between companyName, pageId, and other filters.

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 with clear descriptions for all 10 parameters (e.g., 'End date (YYYY-MM-DD)', 'Facebook page ID'). The description adds no semantic value beyond the schema, but the baseline score is 3 given the comprehensive schema documentation.

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 tautology that merely restates the tool name (scrapecreators_company_ads) without specifying the action (retrieve, list, search) or the resource scope. It fails to distinguish this tool from siblings like scrapecreators_company_ads_get or scrapecreators_search_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?

No guidance provided on when to use this tool versus alternatives such as scrapecreators_company_ads_get, scrapecreators_advertiser_search, or scrapecreators_facebook_ad_library. No prerequisites or conditions for use are mentioned despite having 10 optional filter parameters.

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 fails to mention credit consumption (noted in schema parameter 'get_ad_details'), pagination behavior, rate limits, or what data is returned. The description adds zero behavioral context 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?

While brief at only two words, this is under-specification rather than effective conciseness. The fragment 'Company Ads' does not earn its place because it communicates no actionable information about the tool's function or return values.

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 parameters, no output schema, and no annotations, the description is completely inadequate. It omits expected return format, credit costs, the relationship between 'domain' and 'advertiser_id' parameters, and pagination behavior, leaving critical gaps in the agent's understanding.

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?

With 100% schema description coverage across all 8 parameters, the schema itself documents the parameters adequately. The description adds no additional parameter semantics, but the baseline score of 3 is appropriate 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 'Company Ads' is a noun phrase that restates the tool name without a clear action verb. It does not specify whether the tool retrieves, searches, or analyzes ads, nor does it differentiate from the sibling tool 'scrapecreators_company_ads' (without _get suffix).

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 like 'scrapecreators_company_ads', 'scrapecreators_ad_details', or 'scrapecreators_search_ads'. There is no mention of prerequisites, credit costs (referenced in the schema), or filtering strategies.

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 reveals nothing about whether this performs a live scrape or cached lookup, rate limits, authentication requirements, or what data structure is returned.

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

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

While brief at only two words, the description is informationally empty and fails to front-load critical context (the LinkedIn platform) that appears only in the parameter schema. It wastes the agent's attention without delivering 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 tool's simple single-parameter input and lack of output schema, minimal description is needed, but the omission of 'LinkedIn'—which is crucial for distinguishing this from other platform company pages—leaves a significant gap in context.

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

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

The input schema has 100% description coverage for its single 'url' parameter, which explicitly identifies it as a 'LinkedIn company page' URL. The description adds no additional parameter context, meeting the baseline for high 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 Page' is essentially a tautology that restates the tool name without specifying the action (scrape/retrieve) or the platform (LinkedIn). It fails to distinguish this tool from siblings like 'scrapecreators_company_ads' or 'scrapecreators_linkedin'.

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_for_companies' or 'scrapecreators_linkedin'. There are no prerequisites, exclusions, or conditional usage instructions.

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

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It fails to mention whether this performs a network request, what format the returned HTML takes, whether it includes scripts/iframes, caching behavior, or any side effects. The description adds zero behavioral context 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?

While brief (2 words), this is severe under-specification rather than effective conciseness. The description is front-loaded with ambiguity and lacks the necessary detail to help an agent understand the tool's utility. Every sentence must earn its place, but this description fails to earn its existence.

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

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

Given the tool has no annotations, no output schema, and belongs to a large family of similar scraping tools (80+ siblings), the description provides completely inadequate context. It does not explain what the HTML embedding is for, what content it retrieves, or how to interpret 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 has 100% description coverage (the 'handle' parameter is documented as 'Instagram handle'), so the baseline is 3. The description 'Embed HTML' adds no additional context about the parameter syntax, validation rules, or whether the handle should include or exclude the '@' symbol.

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' is a tautology that restates the action implied by the tool name without specifying what resource is being embedded, what platform it targets (despite the Instagram handle parameter), or what the output represents. It fails to distinguish this from sibling tools like scrapecreators_instagram or scrapecreators_profile_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?

No guidance provided on when to use this tool versus alternatives (e.g., scrapecreators_instagram, scrapecreators_basic_profile), nor any mention of prerequisites, rate limits, or authentication requirements despite being a data retrieval 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 of behavioral disclosure but provides none. It does not indicate what data is returned (profile info, posts, business hours), whether the operation is read-only, rate limits, or privacy considerations. The description 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?

While extremely brief (one word), this represents under-specification rather than efficient conciseness. The word 'Facebook' is redundant given the tool name and fails to earn its place by providing actionable information about functionality.

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 2 parameters and no output schema or annotations, the description is woefully incomplete. It fails to explain what profile data is extracted, the format of results, error handling for invalid URLs, or how the optional business hours parameter affects output.

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 'Facebook profile URL' and 'Set to true to get business hours' adequately documenting the parameters. The description 'Facebook' adds no semantic value beyond the schema, but baseline 3 is appropriate given the schema's completeness.

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' only identifies the target platform without stating what the tool actually does (scraping profile data). While not completely missing, it functions as a near-tautology given the tool name 'scrapecreators_facebook' and fails to specify the action or resource scope.

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 provided on when to use this tool versus the many sibling scraping tools (scrapecreators_instagram, scrapecreators_linkedin, etc.) or other Facebook-related tools like scrapecreators_facebook_group_posts. No prerequisites, limitations, or alternatives 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, yet the description discloses no behavioral traits. It fails to state what data is returned (ad creative, metadata, spend data), whether the operation is read-only, rate limits, or authentication requirements. The full burden of behavioral disclosure is ignored.

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 three-word description is not verbose, it represents under-specification rather than efficient conciseness. No information is front-loaded because no actionable information is present. The single 'sentence' fails to earn its place by providing zero utility.

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 4 parameters targeting a specific external API (Facebook Ad Library), the description is inadequate. Without an output schema, the description should explain return values, yet it provides no context about what data structure or fields to expect from the scraped ad library content.

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?

With 100% schema description coverage across all 4 parameters, the schema itself adequately documents inputs. The tool description adds no additional semantic context, syntax examples, or explanations of what constitutes a 'trimmed response' beyond the parameter descriptions. Baseline score applies since schema carries the full load.

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' is a tautology that restates the tool name without specifying the action (scrape, fetch, or search). It identifies the resource but lacks a verb to clarify what operation is performed. It fails to distinguish from siblings like 'scrapecreators_company_ads' or 'scrapecreators_advertiser_search'.

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

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

No guidance provided on when to use this tool versus alternatives. With numerous sibling scraping tools available (including 'scrapecreators_company_ads' and 'scrapecreators_get_ad'), the description offers no criteria for selecting this specific endpoint or prerequisites like requiring an Ad ID versus a company name.

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 disclosure, yet it mentions nothing about authentication requirements, rate limits, privacy implications of scraping, or whether the operation is read-only. It fails to describe the return format or what happens when accessing private groups.

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 not verbose, it is inappropriately sized at only three words for a complex tool with four parameters and pagination functionality. The extreme brevity renders it insufficient rather than efficiently concise, failing to front-load any actionable guidance.

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

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

Given the tool's complexity—Facebook group scraping with pagination and four input parameters—the description is fundamentally inadequate. With no output schema provided, the description should explain the return format, yet it offers no information about what post data is retrieved or how to handle errors.

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 its four parameters, establishing a baseline where the description need not repeat these definitions. However, the description adds no additional semantic context, such as whether 'url' and 'group_id' are mutually exclusive options or required alternatives.

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 tautology that restates the tool name without the 'scrapecreators_' prefix, failing to specify the action performed (e.g., scrape, retrieve, list). It does not differentiate this tool from siblings like 'scrapecreators_facebook' or 'scrapecreators_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?

The description provides no guidance on when to use this tool versus alternatives such as 'scrapecreators_facebook'. It does not clarify the relationship between the 'url' and 'group_id' parameters, nor does it explain pagination workflows using the 'cursor' parameter despite having zero required parameters.

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 behavioral traits. It fails to indicate this is a read-only operation, omits rate limit warnings, does not explain the trimmed vs. full response difference, and gives no hints about pagination or return structure.

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 brief at a single word, this is under-specification rather than effective conciseness. The solitary word 'Followers' earns no informational value; it wastes the opportunity to front-load critical context about the tool's function.

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 4-parameter tool with no output schema and no annotations, the description is grossly incomplete. It omits the TikTok platform context, pagination behavior, authentication requirements, and the mutual exclusivity logic between 'handle' and 'user_id' parameters.

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?

With 100% schema description coverage, the parameter definitions in the schema are complete (e.g., 'TikTok handle', 'Used to paginate'). The description adds no semantic value beyond the schema, but meets the baseline since the schema adequately documents all 4 parameters.

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 'Followers'—a tautology that restates part of the tool name without specifying the action (retrieve? list? scrape?), the target platform (TikTok, inferred only from schema), or scope. It fails to distinguish from sibling tool 'scrapecreators_following' (followers vs. 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?

Provides no guidance on when to use this tool versus alternatives like 'scrapecreators_following' or 'scrapecreators_basic_profile'. Does not clarify when to use 'handle' versus 'user_id' for lookup, nor explain the pagination mechanism implied by 'min_time'.

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 carries full disclosure burden. It fails to mention read-only status, pagination behavior (despite the min_time parameter implying it), rate limits, or what data structure is returned.

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

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

Single word description represents under-specification rather than effective conciseness. No information is front-loaded because no operational details are provided.

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 numerous sibling tools with similar names (followers, profile, search), the lack of output schema, and the mutation-implied name 'scrape', the description provides insufficient context to distinguish this tool's function or output format.

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%, providing documentation for handle, trim, and min_time. The description adds no parameter context, but the baseline score of 3 applies since the schema adequately documents all three parameters including the pagination semantics of min_time.

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 'Following' is a tautology that merely restates the tool name without the prefix. It fails to specify whether this retrieves who a user follows (vs. scrapecreators_followers which retrieves their followers), what platform (TikTok per the schema), or what the output contains.

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 provided on when to use this tool versus siblings like scrapecreators_followers, scrapecreators_basic_profile, or scrapecreators_search_users. No mention of prerequisites like needing a valid TikTok handle format.

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 the full burden of behavioral disclosure. It fails to indicate whether this is a safe read operation, if there are rate limits, what format the data returns in, or what 'Ad' specifically refers to in this context. No auth requirements or side effects are mentioned.

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 brief at only two words, this represents under-specification rather than effective conciseness. The description fails to earn its place by providing actionable information beyond the function name, leaving the agent without necessary context to select this tool correctly.

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 only one parameter and no output schema (which lowers the complexity bar), the description is inadequate given the rich ecosystem of sibling tools. It fails to clarify the tool's specific role in the scrapecreators suite or what distinguishes it from the multiple other ad-retrieval functions available.

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 (the 'id' parameter is described as 'Ad id'), establishing a baseline score of 3. The description adds no additional context about the ID format, whether it is a platform-specific identifier, or how to obtain 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 'Get Ad' is essentially a tautology of the tool name 'scrapecreators_get_ad', merely removing the prefix and adding a space. While it confirms the tool retrieves an ad, it fails to specify the platform (likely social media given the sibling tools), the data source, or distinguish from siblings 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?

No guidance is provided for when to use this tool versus the numerous sibling ad-related functions (scrapecreators_ad_details, scrapecreators_company_ads, scrapecreators_search_ads, etc.). The agent cannot determine if this is for getting a single ad by ID versus searching or listing company ads.

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 provides zero behavioral context. It does not disclose what constitutes 'popular,' whether results are cached or real-time, pagination limits, rate limits, or what data structure is returned.

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

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

While the three-word description contains no fluff, this represents under-specification rather than effective conciseness. The extreme brevity renders it insufficient for tool selection, though the words themselves are essential.

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

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

Given 5 parameters, zero annotations, no output schema, and a crowded sibling namespace with similar creator-retrieval tools, the description is grossly inadequate. It fails to explain the return format, platform scope, or popularity metrics.

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?

With 100% schema description coverage, the parameters (page, sortBy, followerCount, etc.) are adequately documented in the schema itself. The description adds no additional parameter semantics, meeting the baseline for high-coverage schemas.

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 that restates the tool name without adding specificity. It fails to distinguish this tool from sibling search tools like scrapecreators_search_users or clarify which platform's creators are being retrieved.

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 provided on when to use this tool versus alternatives such as scrapecreators_search, scrapecreators_search_users, or the other get_popular_* variants. No mention of prerequisites or filtering best practices.

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 fails to mention whether this is a read-only operation, what data structure is returned, pagination behavior, or authentication requirements. The description adds no behavioral context 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 extremely brief at three words, which prevents verbosity, but it is under-specified rather than efficiently informative. While not rambling, it fails to front-load valuable context that would help an agent select the 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?

For a tool with four parameters and no output schema, the description is inadequate. It does not explain the return format, what defines 'popular', platform-specific constraints, or how the pagination system works. The high schema coverage for inputs does not compensate for the lack of behavioral and output documentation.

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?

With 100% schema description coverage, the parameters are fully documented in the schema itself (page, period, newOnBoard, countryCode). The description adds no additional semantic context for parameters, but the baseline score of 3 is appropriate since the schema adequately covers the four parameters.

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' is essentially a tautology of the tool name 'scrapecreators_get_popular_hashtags', restating the verb and resource without adding specificity. It fails to distinguish from sibling tools like 'scrapecreators_search_by_hashtag' or clarify what platform these hashtags originate from.

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 provided on when to use this tool versus alternatives such as 'scrapecreators_search_by_hashtag' or 'scrapecreators_get_trending_content'. No mention of prerequisites, rate limits, or optimal 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, yet the description discloses no behavioral traits. It fails to mention what data structure is returned, pagination limits (despite having a 'page' parameter), rate limiting, whether 'popular' refers to TikTok/Instagram trends, or what 'surging' means in the rankType parameter 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?

While the three-word description is not verbose, it is conciseness achieved through under-specification rather than efficiency. With no sentences providing actual value, nothing is 'front-loaded' with useful information. The description is incomplete rather than appropriately 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?

Given 6 filtering parameters (including commercial licensing flags, time periods, and country codes), zero annotations, and no output schema, the description is grossly incomplete. It fails to explain the domain (music charts from short-form video platforms), return value structure, or how the filter parameters interact (e.g., can timePeriod and newOnBoard be combined?).

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?

With 100% schema description coverage, the baseline score is 3. The description adds no semantic meaning beyond what the schema already provides (e.g., it doesn't explain valid values for timePeriod, that countryCode likely follows ISO standards, or clarify the boolean logic for newOnBoard). However, since the schema adequately documents parameters, the description isn't required to compensate.

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' is essentially a tautology of the tool name 'scrapecreators_get_popular_songs', merely removing the prefix and underscores. While it confirms the action, it fails to specify the platform (likely TikTok/short-form video given sibling tools like scrapecreators_tiktoks_using_song) or distinguish from similar 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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention when to prefer this over scrapecreators_get_song_details (for specific song metadata) or scrapecreators_reels_using_song (for content using specific songs), nor does it mention prerequisites like requiring specific country codes or time period formats.

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 disclosure. It fails to mention rate limits, pagination behavior, what data is returned, authentication requirements, or whether this aggregates across platforms or targets a specific one.

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 brief at only three words, this constitutes underspecification rather than efficient conciseness. Given the tool's ambiguity relative to 20+ sibling video-related tools, the description wastes its single sentence by failing to establish unique scope.

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?

Lacking annotations, output schema, and with only a tautological description, this tool definition provides insufficient context for an agent to select it correctly from among the extensive list of video-related siblings (scrapecreators_reels, scrapecreators_channel_videos, etc.).

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?

With 100% schema description coverage, the structured data already documents all four parameters adequately. The description adds no parameter-specific context, syntax details, or usage examples beyond what the schema provides, meriting the baseline 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 'Get popular videos' is essentially a tautology that restates the tool name without specifying the platform (TikTok, YouTube, Instagram, etc.) or distinguishing from siblings like scrapecreators_channel_videos, scrapecreators_trending_shorts, or scrapecreators_get_popular_creators. It provides only a generic verb and object.

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 numerous alternatives (scrapecreators_search, scrapecreators_trending_shorts, scrapecreators_channel_videos, etc.), no mention of prerequisites, and no indication of what 'popular' specifically means in this 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 but provides almost nothing. It does not clarify if this is a read-only operation (though 'Get' implies it), what happens if the clipId is invalid, rate limits, or the response format. The schema's parameter description adds some transparency about the clipId/songId distinction, but the main description field itself adds no 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?

While the three-word description is technically concise, it suffers from under-specification rather than efficient information delivery. Every sentence (here, just one) fails to earn its place by providing actionable context, making it wasteful in its brevity rather than appropriately front-loaded.

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

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

Given the lack of output schema and annotations, the description should explain what song details are returned (metadata, audio URL, usage statistics?), specify the platform context, and clarify the clipId concept. It provides none of these, leaving significant gaps in contextual 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 the clipId parameter documented in the schema explaining the confusing naming convention. The description 'Get Song Details' adds no additional parameter semantics, but with high schema coverage, the baseline score of 3 is appropriate as the schema carries the load.

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 tautology that restates the tool name (scrapecreators_get_song_details) in title case. It fails to specify what song details are returned, what platform this targets (TikTok, Instagram, etc.), or how it differs from siblings like scrapecreators_get_popular_songs or scrapecreators_tiktoks_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?

No guidance provided on when to use this tool versus alternatives such as scrapecreators_reels_using_song or scrapecreators_get_popular_songs. There is no mention of prerequisites (e.g., how to obtain a clipId) or conditions where this tool should not be used.

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 the full burden of disclosing behavioral traits (read-only vs destructive, authentication requirements, return format, rate limits). It provides zero behavioral context beyond the platform 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?

While brief, 'Google' is inappropriately sized—this is under-specification rather than efficient conciseness. It fails to front-load any actionable information, consisting of a single noun that assumes the agent already understands the tool's function.

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 complexity of scraping Google data (potential for various result types, SERP features, knowledge panels) and the absence of an output schema or annotations, the description is completely inadequate. It fails to explain what data structure is returned or what specific Google content is retrieved.

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 (query and region are well-documented in the schema itself). The description adds no parameter details, but with complete schema coverage, 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 'Google' is essentially a tautology that restates the platform name from the tool name (scrapecreators_google) without explaining the action (scrape/search), the specific resource being accessed, or how it differs from sibling search tools like tavily_search or web_search_exa.

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 provided on when to use this tool versus alternatives (tavily_search, web_search_exa, scrapecreators_search), nor any prerequisites, rate limits, or best practices for the region 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?

No annotations are provided, and the description discloses no behavioral traits. It does not indicate whether this is a read-only operation, what data source is queried, rate limits, authentication requirements, or what format the returned highlight details take.

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 brief at two words, this represents under-specification rather than efficient conciseness. Every sentence should earn its place, but this description fails to provide the essential context expected for a tool in a complex social-media scraping ecosystem.

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 exists within a large suite of social media scraping functions (100+ siblings), the description is inadequate. It lacks platform specification, output structure details, and relationship context to similar tools like 'scrapecreators_story_highlights', leaving critical gaps for agent decision-making.

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?

With 100% schema description coverage (the 'id' parameter is documented as 'The ID of the highlight to get details for'), the schema carries the full semantic load. The description adds no additional parameter context (such as ID format or source), warranting the baseline score for high-coverage schemas.

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 tautology that restates the tool name ('scrapecreators_highlights_details') without adding specificity. It fails to specify what platform's highlights (Instagram, TikTok, etc.) or what 'details' encompasses, and does not distinguish from sibling tools like 'scrapecreators_story_highlights'.

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. Given the presence of siblings like 'scrapecreators_story_highlights' and 'scrapecreators_profile_posts', the absence of differentiation criteria leaves agents unable to select the correct tool for retrieving highlight 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?

With no annotations provided, the description fails to disclose any behavioral traits such as whether the operation is read-only or destructive, rate limiting concerns, or the structure of returned data. The term 'scrape' in the tool name hints at data retrieval, but the description itself provides no confirmation of safety profiles 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 a single word that is severely under-specified rather than appropriately concise; it fails to meet the minimum viable length for a tool with multiple parameters and no output schema. While it contains no wasted words, the extreme brevity renders it functionally useless for decision-making.

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 two parameters, lack of output schema, absence of annotations, and the tool's position among dozens of similar scraping utilities, the single-word description is completely inadequate. The agent lacks necessary context regarding what specific Instagram data is retrieved (profile, posts, metadata) and how this tool differs from specialized siblings.

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?

While the input schema has 100% description coverage for its two parameters ('Instagram handle' and trim option), the description adds no semantic value beyond what the schema already provides. The baseline score applies since the schema adequately documents parameters without requiring additional descriptive context.

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

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

The description consists solely of the word 'Instagram,' which fails to specify what action the tool performs or what resource it retrieves. It provides no verb indicating functionality (e.g., retrieve, scrape, search) and does not distinguish this tool from the numerous sibling scraper tools like `scrapecreators_basic_profile` or platform-specific variants.

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 no guidance on when to use this tool versus the many available alternatives, including other Instagram-specific tools like `scrapecreators_profile_posts` or cross-platform options. There are no stated prerequisites, conditions, or exclusion criteria to inform agent 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 provided, the description carries the full burden of disclosing behavioral traits but fails completely. It does not indicate what data is returned (metadata, transcripts, media files), whether the operation is read-only or destructive, or if there are rate limiting concerns.

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 brief (one word), this represents under-specification rather than effective conciseness. The single word fails to earn its place by providing actionable information about tool functionality, resulting in an inappropriately sized 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 output schema and annotations, the description is completely inadequate even for a single-parameter tool. It does not explain what information is extracted from the Kick clip URL, the structure of returned data, or any error conditions.

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 its single 'url' parameter ('Kick clip URL'), establishing a baseline score of 3. The description 'Kick' adds no additional semantic context, examples, or formatting guidance 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 'Kick' merely identifies the target platform, functioning as a tautology that restates the platform suffix from the tool name 'scrapecreators_kick'. It fails to specify what action the tool performs (e.g., scraping clip metadata, downloading content) or distinguish its purpose from sibling tools like 'scrapecreators_twitch' or 'scrapecreators_youtube'.

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

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

No guidance is provided regarding when to use this tool versus alternatives, what prerequisites are needed (e.g., valid Kick clip URL format), or specific use cases. The description offers zero contextual clues for proper 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 provided, the description carries the full burden of behavioral disclosure but completely fails to indicate whether this is a read-only operation, what data is scraped, rate limits, or authentication requirements. The single word reveals nothing about the tool's behavior beyond what the name implies.

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 consists of only a single word, this represents under-specification rather than effective conciseness. No information is front-loaded because no actionable information is present; the description wastes the opportunity to orient the user.

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 web scraping tool with no output schema and no annotations, the description is completely inadequate. It fails to explain what data is returned, what 'Komi' refers to (a specific creator platform), or how the scraped data is structured, leaving critical gaps in the agent's understanding.

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 (the 'url' parameter is documented as 'URL to Komi page'), establishing a baseline score of 3. The description 'Komi' adds no additional semantic value regarding parameter usage, formats, or examples 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 'Komi' is a tautology that merely restates the platform name from the tool identifier without explaining what the tool actually does (presumably scraping data from Komi creator pages). It fails to provide a specific verb or resource description to distinguish its function from the 80+ sibling scraping 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 the numerous alternative platform-specific scrapers (scrapecreators_instagram, scrapecreators_tiktok, etc.). There are no prerequisites, conditions, or exclusion criteria 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 carries the full burden of behavioral disclosure, yet it provides zero information about side effects, return data, rate limits, or authentication requirements. The agent cannot determine if this is a read operation or what data structure it returns.

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 brief (single word), this represents under-specification rather than efficient conciseness. The description contains no actionable information for an agent, failing the standard that 'every sentence should 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?

For a tool with no output schema and no annotations, the description provides no context about what data is retrieved from Linkbio pages or how the results are structured. It is completely inadequate for an agent to understand the tool's utility.

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 (the 'url' parameter is documented as 'URL to Linkbio (lnk.bio) page'). Since the schema fully documents the single parameter, the description does not need to compensate, warranting the baseline score of 3.

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

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

The description 'Linkbio' is a tautology that restates the tool name (scrapecreators_linkbio) without explaining what the tool actually does. It lacks a specific verb (e.g., 'scrape,' 'extract,' 'retrieve') and fails to distinguish this tool from similar siblings like scrapecreators_linktree or scrapecreators_linkme.

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. Given the presence of similar tools (scrapecreators_linktree, scrapecreators_linkme), the description should specify that this targets lnk.bio specifically, but it provides no such differentiation.

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, yet it fails to mention that this performs web scraping, what data fields are returned, rate limits, authentication requirements, or whether the operation is read-only vs. potentially restricted by LinkedIn's robots.txt.

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 single word is not verbose, it represents under-specification rather than earned brevity. As with the calibration example 'Process', minimal length without information density warrants a low score.

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 only one parameter with complete schema coverage, the tool performs an external scraping operation where behavior matters significantly. The absence of any mention of output format, data extracted (e.g., name, title, company), or error conditions (private profiles, invalid URLs) leaves critical 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 input schema has 100% description coverage (the 'url' parameter is documented as 'LinkedIn profile URL'), establishing a baseline score of 3. The description adds no additional parameter semantics, but does not detract from the schema's clarity.

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 'LinkedIn' is tautological, merely restating the platform suffix from the tool name 'scrapecreators_linkedin'. It fails to specify the action (scrape/fetch), the target resource (profiles, posts, company pages), or the scope, leaving the agent to guess the tool's actual 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 provided on when to use this tool versus siblings like 'scrapecreators_basic_profile' or 'scrapecreators_company_page', or prerequisites such as requiring a public profile URL. The description is completely 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.