Enhanced Web Scraper MCP Server

by JMRMEDEV

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The tools have some clear distinctions, such as between scraping, inspecting, and testing functions, but there is significant overlap and ambiguity. For example, 'inspect_element' and 'inspect_react_app' both involve inspection, and 'execute_in_react_context' could be confused with 'test_react_app' or 'wait_for_react_state', making tool selection potentially confusing for an agent.
Naming Consistency3/5
The naming follows a mostly readable verb_noun pattern, but there are inconsistencies in verb usage and specificity. Tools like 'scrape_page' and 'get_page_info' use different verbs for similar actions, and 'test_dropdown_with_error_capture' includes additional descriptors, deviating from the simpler naming of others like 'wait_for_element'.
Tool Count4/5
With 10 tools, the count is reasonable for a web scraper server that covers scraping, inspection, testing, and waiting functions. It's well-scoped for the domain, though it might be slightly heavy, as some tools could be consolidated to reduce overlap without losing functionality.
Completeness4/5
The tool set covers core web scraping and testing workflows, including page scraping, element inspection, React app analysis, and interaction testing. Minor gaps exist, such as the lack of tools for handling authentication or advanced data extraction, but agents can likely work around these with the provided tools for most common tasks.
Average 3/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions checking server status but doesn't describe what 'running' means (e.g., HTTP response codes, timeout behavior), what 'app status' includes (e.g., bundle status, connected devices), error handling, or network requirements. This leaves significant gaps for a tool that interacts with external services.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every element ('check if... running and get... status') directly contributes to understanding the tool's function, with zero redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that checks external service status. It doesn't explain what constitutes 'running' (success criteria), what 'app status' returns, error conditions, or network dependencies. For a tool with 2 parameters and potential complexity in interpreting server responses, this leaves the agent with insufficient context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters (host and port) with clear descriptions and defaults. The description adds no additional parameter semantics beyond what's in the schema, but doesn't need to compensate for gaps. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('check' and 'get') and identifies the target resource ('Expo development server' and 'app status'). It distinguishes itself from sibling tools by focusing on server status checking rather than UI interaction or testing. However, it doesn't explicitly differentiate from potential non-sibling alternatives like general network checking tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., when Expo dev server should be running), exclusions (e.g., not for production servers), or compare with sibling tools that might overlap in functionality. The agent must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 executing JavaScript in a browser context but does not cover critical aspects such as security implications, performance impact, error handling, or what happens if React is not available (beyond the 'waitForReact' parameter). For a tool that interacts with external systems and executes arbitrary code, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Execute JavaScript in React context') and follows with the purpose. There is no wasted verbiage, and every word contributes to understanding the tool's function, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of executing JavaScript in a browser with React, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., side effects, error responses), does not explain the return values or output format, and fails to address security or performance considerations. This makes it inadequate for safe and effective use by an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description does not add any semantic details beyond what the schema provides (e.g., it does not explain the significance of 'React context' for the script or how the browser choice affects execution). Baseline score of 3 is appropriate as the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('execute JavaScript') and the resource ('in React context'), and specifies the purpose ('to inspect components, state, or trigger actions'). It distinguishes from generic JavaScript execution tools by specifying the React context, but does not explicitly differentiate from sibling tools like 'inspect_react_app' or 'test_react_app', which may 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.
Usage Guidelines2/5
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 sibling tools, prerequisites, or specific scenarios where this tool is preferred over others like 'inspect_react_app' or 'test_react_app'. The lack of usage context leaves the agent without clear direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 what information is retrieved, it doesn't describe how the tool behaves—such as whether it loads the page in a browser, potential timeouts, error handling, or any side effects. This is a significant gap for a tool that likely involves network operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose and lists key outputs without any wasted words. It's appropriately sized for the tool's complexity and provides essential information concisely.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like how the tool operates, potential errors, or output format details. For a tool that likely involves web scraping or analysis, more context on performance implications or limitations would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as explaining the relationship between 'includePerformance' and the output or typical values for 'url'. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Get') and resource ('web page'), and lists the types of information retrieved (title, meta tags, performance metrics). However, it doesn't explicitly differentiate this tool from sibling tools like 'scrape_page', 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.
Usage Guidelines2/5
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 'scrape_page' or other sibling tools. It lacks context about prerequisites, typical use cases, or any explicit when/when-not instructions, leaving the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the tool inspects and returns data, but doesn't cover critical aspects like whether it navigates to the URL, handles errors (e.g., if selector not found), requires page loading, or has performance implications. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and output. Every word earns its place with no redundancy or fluff, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool with 4 parameters and behavioral complexity. It lacks details on error handling, return format (e.g., structure of attributes/text/styles), dependencies (e.g., page state), and how it interacts with sibling tools. This leaves the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 75% (3 of 4 parameters have descriptions), so the baseline is 3. The description adds some value by implying the 'selector' and 'url' parameters are used for inspection, but doesn't elaborate on 'properties' (CSS properties) or 'browser' beyond what the schema provides. It compensates minimally for the 25% gap in schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Inspect a DOM element by selector and return its attributes, text, and computed styles.' It specifies the verb ('inspect'), resource ('DOM element'), and output details. However, it doesn't explicitly differentiate from siblings like 'get_page_info' or 'scrape_page', which might also involve element inspection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a loaded page), exclusions, or comparisons to sibling tools like 'wait_for_element' or 'inspect_react_app'. Usage is implied by the action but not explicitly contextualized.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 analysis of 'component tree, props, and state', it doesn't describe what the tool actually does behaviorally: Does it launch a browser? Does it require React DevTools? Is it read-only or does it modify the app? What's the output format? The description is too vague about the tool's operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point: 'Inspect React Native web app with component tree, props, and state analysis.' There's no wasted verbiage, and it's appropriately sized for the tool's complexity. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain what the tool actually produces as output, how it interacts with the app, or what behavioral constraints exist. For an inspection tool that presumably launches browsers and analyzes React applications, more context about the operation and results is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. It mentions 'component tree, props, and state analysis' which loosely maps to 'includeComponentTree' and 'includeState' parameters, but doesn't provide additional semantic context. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Inspect React Native web app with component tree, props, and state analysis.' It specifies the verb ('inspect'), resource ('React Native web app'), and scope of analysis. However, it doesn't explicitly differentiate from sibling tools like 'test_react_app' or 'inspect_element', which could 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.
Usage Guidelines2/5
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 siblings like 'test_react_app', 'inspect_element', and 'check_expo_dev_server', there's no indication of when this inspection-focused tool is preferred over testing or other inspection tools. The description lacks any 'when-to-use' or 'when-not-to-use' context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the implementation (Playwright) and target page types, but lacks critical details: it doesn't specify what 'scrape content' entails (e.g., returns HTML, text, structured data), potential side effects (e.g., network requests, JavaScript execution), error handling, or performance implications like rate limits or timeouts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and includes relevant technical context (Playwright, page types) without unnecessary elaboration. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a web scraping tool with 7 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on return values (critical since there's no output schema), error cases, behavioral constraints, and differentiation from siblings. This leaves significant gaps for an AI agent to understand the tool fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 7 parameters. The description adds no additional parameter semantics beyond what's in the schema, such as explaining interactions between parameters (e.g., how 'device' and 'mobileViewport' relate) or usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('scrape') and resource ('content from any web page'), specifying the target scope (regular websites, React apps, React Native web apps) and implementation method (Playwright). However, it doesn't explicitly differentiate from sibling tools like 'get_page_info' or 'inspect_element', which might have overlapping purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions target page types but doesn't specify scenarios where this tool is preferred over siblings like 'get_page_info' or 'inspect_element', nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'comprehensive console error capture and page state monitoring,' which hints at monitoring behavior, but lacks critical details: what specific errors are captured, how page state is monitored, whether this is a read-only or destructive operation, authentication requirements, or rate limits. For a testing tool with no annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose: 'Test dropdown interactions with comprehensive console error capture and page state monitoring.' Every word earns its place, with no redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a testing tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, error handling, output format, and how it differs from sibling tools. The high schema coverage helps with parameters, but overall context for effective use is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds no additional meaning beyond what's in the schema—it doesn't explain parameter interactions, default behaviors, or usage examples. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Test dropdown interactions with comprehensive console error capture and page state monitoring.' It specifies the action (test dropdown interactions) and key features (error capture, state monitoring). However, it doesn't distinguish this from sibling tools like 'test_react_app' or 'inspect_react_app', 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.
Usage Guidelines2/5
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 'test_react_app', 'inspect_react_app', and 'check_expo_dev_server', there's no indication of when this specific dropdown testing tool is preferred or what scenarios 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.
Behavior2/5
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 'enhanced interactions and mobile gestures,' which adds some context beyond basic testing, but fails to cover critical aspects like whether this is a read-only or destructive operation, performance implications, error handling, or output format. For a complex testing tool with multiple parameters, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It uses parentheses for clarification and avoids redundancy, making it appropriately sized for its informational value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, no output schema, no annotations), the description is incomplete. It lacks details on behavioral traits, output expectations, error conditions, and how it differs from siblings. Without annotations or output schema, the description should compensate more to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no specific parameter semantics beyond what the input schema provides. Since schema description coverage is 100%, the baseline score is 3. The description does not elaborate on parameter usage, relationships, or examples, such as how 'actions' interact with 'device' emulation or 'waitForHydration' timing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Test any React app (regular React or React Native web) with enhanced interactions and mobile gestures.' It specifies the verb ('test'), resource ('React app'), and scope ('regular React or React Native web'), though it doesn't explicitly differentiate from sibling tools like 'test_dropdown_with_error_capture' or 'inspect_react_app'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance on when to use this tool. It mentions 'enhanced interactions and mobile gestures,' which hints at its capabilities, but offers no explicit when-to-use or when-not-to-use advice compared to alternatives like 'scrape_page' or 'execute_in_react_context.' No prerequisites or exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 waiting for conditions but doesn't describe what happens on success/failure, error handling, or side effects. For a tool with 5 parameters and no annotations, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality, making it easy to understand at a glance while being appropriately sized for its complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, no annotations, and no output schema, the description is minimal but covers the basic purpose. It doesn't address behavioral aspects like return values or error conditions, which are important given the lack of structured data. It's adequate but has clear gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as explaining how conditions interact or providing examples. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 waiting for React component state changes, data loading, or navigation, which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'wait_for_element' or 'test_react_app', which might have overlapping functionality in a React testing context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'wait_for_element' and 'test_react_app' present, there's no indication of scenarios where this tool is preferred or when other tools might be more appropriate, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 waiting for dynamic React content but doesn't describe what happens on success/failure, whether it polls continuously, what error conditions exist, or what permissions/browser state is required. The description is too minimal for a tool that interacts with browser automation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just one sentence containing 11 words. Every word earns its place: 'Wait for an element to appear on the page' states the core purpose, and '(useful for dynamic React content)' adds valuable context. No wasted words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a browser automation tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, what happens when the element doesn't appear, or how it interacts with the browser context. The React mention is helpful but insufficient for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline of 3 is appropriate since the schema does the heavy lifting, though the description doesn't compensate with additional context about parameter interactions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Wait for an element to appear on the page' with the specific verb 'wait' and resource 'element'. It distinguishes from some siblings like 'scrape_page' or 'get_page_info' by focusing on waiting rather than retrieving information, though it doesn't explicitly differentiate from all siblings like 'wait_for_react_state'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance with '(useful for dynamic React content)', suggesting it's for React-based pages. However, it doesn't explicitly state when to use this tool versus alternatives like 'wait_for_react_state' or 'inspect_element', nor does it provide clear exclusions or prerequisites for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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