Scrapy MCP Server

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 mentions 'ethical scraping' and 'crawling rules,' which imply read-only and non-destructive behavior, but it doesn't explicitly state whether this is a read operation, what permissions or rate limits apply, or what happens on errors (e.g., if the robots.txt file is missing). For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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

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

The description is appropriately sized and front-loaded: the first sentence states the core purpose, and the second adds value by explaining the ethical context. There's no wasted text, and every sentence contributes meaningfully to understanding the tool's use.

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 (one parameter) and the presence of an output schema (which likely covers return values), the description is reasonably complete. It explains what the tool does and why to use it, though it could improve by addressing behavioral aspects like error handling or rate limits. The output schema reduces the need to describe return values in the description.

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

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

The input schema has one parameter ('url') with 0% schema description coverage (no title or description in the schema). The description doesn't add any parameter-specific details beyond implying the 'url' should be a domain for checking robots.txt. Since schema coverage is low, the description doesn't fully compensate by explaining the parameter's format or constraints, but it does provide some context through the tool's purpose.

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

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

The description clearly states the tool's purpose: 'Check the robots.txt file for a domain to understand crawling permissions.' It specifies the verb ('check'), resource ('robots.txt file'), and goal ('understand crawling permissions'). However, it doesn't explicitly differentiate this from sibling tools like 'get_page_info' or 'scrape_webpage' that might also retrieve web content, though the focus on robots.txt is specific.

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

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

The description provides implied usage context: 'This tool helps ensure ethical scraping by checking the robots.txt file...' This suggests it should be used before scraping to comply with rules, but it doesn't explicitly state when to use this tool versus alternatives (e.g., 'scrape_webpage' for general content) or when not to use it (e.g., for non-web domains). The guidance is helpful but not comprehensive.

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. It discloses the destructive nature ('removes all cached scraping results') and the behavioral consequence ('forcing fresh requests'), but doesn't mention potential side effects like performance impact, permission requirements, or rate limits. It adequately describes the core behavior but lacks comprehensive operational context.

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

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

The description is perfectly front-loaded with the core purpose in the first sentence, followed by a clarifying second sentence about consequences. Both sentences earn their place with no wasted words, making it highly efficient and well-structured.

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

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

Given the tool's simple nature (0 parameters, no annotations, but has output schema), the description is reasonably complete. It explains what the tool does and the immediate effect, though it could benefit from mentioning what the output schema returns. The presence of an output schema reduces the need to describe return values, but some indication of what to expect would enhance 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 with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, maintaining focus on the tool's purpose and 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 specific action ('Clear') and target resource ('scraping results cache'), distinguishing it from sibling tools that perform scraping, extraction, or monitoring operations. It precisely defines what the tool does without restating the name.

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

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

The description provides clear context for when to use this tool ('forcing fresh requests for all subsequent scraping operations'), but doesn't explicitly state when not to use it or mention alternatives. It implies usage in cache management scenarios but lacks explicit exclusions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions filtering capabilities but doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, error handling, or what the output looks like (though an output schema exists). For a web scraping tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is appropriately sized with two sentences: the first states the core purpose, and the second adds specialized capabilities. Every sentence earns its place by providing essential information without redundancy, making it front-loaded and efficient.

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

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

Given the tool's moderate complexity (link extraction with filtering), no annotations, and an output schema (which reduces the need to describe return values), the description is somewhat complete but has gaps. It covers the purpose and basic capabilities but lacks behavioral details like error conditions or performance characteristics, making it adequate but not fully comprehensive for informed tool selection.

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

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

The description adds some semantic context by mentioning filtering by domain, internal links, and domain exclusion, which aligns with the parameters in the schema. However, with 0% schema description coverage, the schema provides no parameter descriptions, so the description only partially compensates. It doesn't explain the 'url' parameter or provide examples of domain formats, leaving room for improvement given the coverage gap.

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

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

The description clearly states the tool's purpose as 'Extract all links from a webpage' with a specific verb ('extract') and resource ('links from a webpage'). It distinguishes itself from siblings like 'scrape_webpage' or 'extract_structured_data' by focusing solely on link extraction, but doesn't explicitly contrast with these alternatives.

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

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

The description implies usage context by mentioning filtering capabilities ('filter links by domain, extract only internal links, or exclude specific domains'), suggesting when to use it for specialized link extraction. However, it lacks explicit guidance on when to choose this tool over siblings like 'scrape_webpage' (which might also extract links) or 'extract_structured_data', and doesn't mention any prerequisites or exclusions.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'advanced techniques' but doesn't explain what these entail (e.g., rate limits, authentication needs, potential for blocking, or how it handles dynamic content). For a web extraction tool with no annotations, this leaves significant gaps in understanding operational behavior and risks.

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 sized and front-loaded, starting with the core purpose. The bulleted list efficiently details extractable data types, and the final sentence clarifies the data_type parameter. There's minimal waste, though the structure could be slightly improved by integrating the data_type explanation more seamlessly.

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

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

Given the tool's moderate complexity (web extraction with 2 parameters), no annotations, and an output schema present, the description is partially complete. It covers the purpose and parameter semantics to some extent but lacks behavioral details and usage guidelines. The output schema likely handles return values, so that gap is mitigated, but overall completeness is limited for effective agent use.

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

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

The description adds meaning for the 'data_type' parameter by listing its possible values (all, contact, social, etc.) and examples of what each extracts, which is valuable since schema description coverage is 0%. However, it doesn't explain the 'url' parameter beyond what the schema title implies. With 2 parameters and low schema coverage, this partial compensation results in a baseline adequate 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 clearly states the verb 'extract' and resource 'structured data from a webpage', specifying what the tool does. It lists concrete examples of data types (contact info, social media links, etc.), making the purpose specific. However, it doesn't explicitly distinguish this tool from sibling tools like 'scrape_webpage' or 'extract_links', which might have overlapping functionality.

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

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

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'scrape_webpage', 'extract_links', and 'scrape_with_stealth' available, there's no indication of scenarios where this tool is preferred, prerequisites, or exclusions. Usage is implied only through the data_type parameter, but not contextualized against other tools.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the tool can handle various form elements and optional submission, it lacks critical details such as required permissions, potential side effects (e.g., data submission consequences), error handling, or performance considerations like timeouts. This is inadequate for a tool that interacts with webpages and submits 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 appropriately sized and front-loaded, starting with the core purpose in the first sentence, followed by a bulleted list of capabilities and a concise usage note. Every sentence earns its place without redundancy, making it efficient and easy to scan.

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 (web form interaction with potential data submission), no annotations, and an output schema that likely handles return values, the description is incomplete. It covers purpose and basic usage but lacks behavioral transparency and detailed parameter guidance, which are critical for safe and effective use. The presence of an output schema mitigates some gaps, but overall completeness is moderate.

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 0%, but the description adds some value by listing form element types (text inputs, checkboxes, etc.) and use cases, which helps infer the purpose of 'form_data'. However, it does not explain other parameters like 'method', 'submit_button_selector', or 'wait_for_element', leaving significant gaps. With 1 parameter (a nested object with 6 sub-parameters), the description partially compensates but not fully.

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

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

The description clearly states the tool's purpose with specific verbs ('fill and optionally submit a form on a webpage') and distinguishes it from siblings like 'scrape_webpage' or 'extract_links' by focusing on form interaction rather than data extraction or navigation. It explicitly mentions the resource (form) and scope (webpage).

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

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

The description provides clear context for when to use this tool ('useful for interacting with search forms, contact forms, login forms, etc.'), which helps differentiate it from general scraping tools. However, it does not explicitly state when not to use it or name specific alternatives among siblings, such as when to prefer 'scrape_webpage' for non-form interactions.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool is 'lightweight' and for 'quickly checking,' which hints at performance characteristics, but doesn't detail behavioral traits like rate limits, authentication needs, error handling, or what 'status' specifically means (e.g., HTTP status codes). It adds some context but lacks comprehensive behavioral disclosure.

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

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

The description is appropriately sized and front-loaded: the first sentence states the core purpose, and the second adds usage context. Every sentence earns its place by clarifying the tool's scope and when to use it, with zero wasted words.

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

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

Given the tool's low complexity (1 parameter) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers purpose and usage guidelines well. However, with no annotations and low schema coverage, it could benefit from more behavioral details, but the output schema mitigates some 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 1 parameter (url) with 0% description coverage, meaning the schema provides no semantic details. The description doesn't add any parameter-specific information beyond what's implied by the tool's purpose (e.g., it doesn't specify URL format requirements or validation). With low schema coverage, the description doesn't compensate adequately, but since there's only one parameter, the baseline is slightly higher.

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

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

The description clearly states the tool's purpose: 'Get basic information about a webpage (title, description, status).' It specifies the verb 'get' and the resource 'webpage' with concrete examples of what information is retrieved. However, it doesn't explicitly differentiate from sibling tools like 'scrape_webpage' or 'extract_structured_data' beyond mentioning it's 'lightweight' and for 'quickly checking page accessibility.'

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

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

The description provides clear context for when to use this tool: 'for quickly checking page accessibility and getting basic metadata without full content extraction.' This implies it's suitable for lightweight checks versus more intensive extraction tools. However, it doesn't explicitly name alternatives or state when not to use it, such as for detailed content analysis.

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 it lists the categories of metrics returned, it doesn't address critical behavioral aspects like whether this requires authentication, if it's a read-only operation, what time range the metrics cover, or if there are rate limits. The description is insufficient for a mutation-free tool with zero annotation coverage.

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 efficiently structured with a clear purpose statement followed by a bulleted list of return categories. Every sentence earns its place, though the bulleted list could be slightly more concise by integrating it into the flow rather than as a separate section.

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

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

Given that there's an output schema (which handles return value documentation), zero parameters, and no annotations, the description is reasonably complete for its core purpose. However, it lacks important context about when to use it versus siblings and behavioral constraints, making it only minimally adequate.

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

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

The tool has zero parameters, and schema description coverage is 100%, so there's no parameter documentation burden. The description appropriately doesn't waste space discussing non-existent parameters, earning a high score for correctly handling this edge case.

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

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

The description clearly states the tool's purpose with the verb 'Get' and resource 'server performance metrics and statistics', making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_page_info' or 'scrape_webpage' which might also provide performance-related data in different contexts, preventing a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_page_info' that might overlap in providing server-related data, there's no indication of when this specific metrics tool is preferred or what contexts it's designed for.

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

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

No annotations are provided, so the description carries the full burden. It mentions concurrency and speed but lacks critical behavioral details such as rate limits, error handling (e.g., if some URLs fail), authentication needs, or what 'processed concurrently' entails (e.g., thread count, timeouts). For a tool with potential complexity and no annotation coverage, this is a significant gap.

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

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

The description is appropriately sized and front-loaded: the first sentence states the core purpose, and the following sentences add useful context about concurrency and speed. Every sentence earns its place with no wasted words, making it easy to scan and understand 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 complexity (concurrent web scraping with configurable methods), no annotations, 0% schema description coverage, but an output schema exists, the description is incomplete. It covers the high-level purpose and benefit but misses details on parameters, behavioral traits, and error handling. The output schema reduces the need to explain return values, but other gaps remain significant.

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 0%, so the description must compensate for undocumented parameters. It mentions 'URLs' but doesn't explain the 'extract_config' or 'method' parameters beyond what the schema provides (e.g., what 'auto' means, how configuration works). With 1 parameter (a nested object with 3 sub-parameters) and no schema descriptions, the description adds minimal value over the bare schema.

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

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

The description clearly states the tool's purpose: 'Scrape multiple webpages concurrently.' It specifies the verb (scrape) and resource (multiple webpages) with the key feature of concurrency. However, it doesn't explicitly differentiate from sibling tools like 'scrape_webpage' (singular) or 'scrape_with_stealth' (stealth-focused), missing full sibling differentiation.

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 by stating it's 'much faster than scraping them one by one,' suggesting it should be used for batch scraping. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'scrape_webpage' for single URLs or 'scrape_with_stealth' for stealth needs, nor does it mention any exclusions or prerequisites.

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

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

No annotations are provided, so the description carries full burden. It mentions scraping methods and extraction rules but doesn't disclose critical behavioral traits like rate limits, authentication needs, potential for blocking, error handling, or what 'extract its content' entails. For a web scraping tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and risks.

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 sized and front-loaded: the first sentence states the core purpose, followed by bullet points for methods and a final sentence on extraction rules. Every sentence earns its place with no wasted words, making it easy to scan and understand 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 complexity (web scraping with multiple methods) and no annotations, the description is moderately complete but has gaps. It covers purpose and methods well, and an output schema exists (reducing need to explain returns), but it lacks details on behavioral aspects like limitations or errors. For a tool with siblings like 'scrape_with_stealth', more context on trade-offs 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?

Schema description coverage is 0%, so the description must compensate. It adds meaningful context beyond the schema by explaining the four scraping methods (auto, simple, scrapy, selenium) and mentioning extraction rules, which helps interpret the 'extract_config' and 'method' parameters. However, it doesn't detail the 'wait_for_element' parameter or provide examples for extraction rules, leaving some semantic gaps.

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

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

The description clearly states the tool's purpose with a specific verb ('scrape') and resource ('single webpage'), and distinguishes it from siblings like 'scrape_multiple_webpages' by specifying 'single'. It also mentions content extraction, which differentiates it from tools like 'extract_links' or 'get_page_info'.

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

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

The description provides clear context on when to use different scraping methods (auto, simple, scrapy, selenium) based on needs like speed or JavaScript support, but doesn't explicitly state when NOT to use this tool or name alternatives among siblings. It implies usage scenarios but lacks explicit exclusions or comparisons to tools like 'scrape_with_stealth'.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does describe key behavioral traits: 'advanced stealth techniques,' 'anti-detection methods,' and lists specific techniques like undetected browser automation and randomized patterns. However, it lacks details about potential risks, rate limits, authentication needs, or what happens when detection occurs.

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 sized with clear front-loading of the main purpose. The bullet-point list of techniques is organized and adds value. However, the final usage guideline sentence could be more integrated with the opening statement for better flow.

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 stealth web scraping (which involves evasion techniques and potential ethical/legal considerations), the description is moderately complete. It covers the 'why' (anti-bot protection) and 'how' (stealth techniques) but lacks details about parameters, output format (though output schema exists), error conditions, and limitations. The presence of an output schema helps but doesn't compensate for missing behavioral context.

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

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. The description mentions 'stealth techniques' and 'anti-detection methods' but provides no information about the actual parameters (url, method, scroll_page, wait_for_element, extract_config). It doesn't explain what these parameters mean or how they relate to the stealth functionality.

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

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

The description clearly states the tool's purpose as 'Scrape a webpage using advanced stealth techniques to avoid detection,' which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'scrape_webpage' or 'scrape_multiple_webpages' beyond mentioning stealth techniques for anti-bot protection.

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

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

The description provides clear context for when to use this tool: 'Use this for websites with strong anti-bot protection.' This gives practical guidance about the target scenario. However, it doesn't explicitly state when NOT to use it or mention specific alternatives among the sibling tools.

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