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

No annotations provided, and description does not disclose behavioral traits such as return type (boolean? throws on failure?), waiting behavior, or side effects. The brief description only states purpose.

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 concise sentence, front-loaded with verb and resource. No extraneous words.

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

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

With 5 parameters and no output schema, the description lacks detail on behavior (e.g., success/failure feedback, timeout behavior). It is too minimal for a tool that performs assertions.

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 each parameter has a clear description. The tool description does not add extra meaning beyond what the schema already provides, meeting baseline.

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

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

The description clearly states it asserts computed CSS property value matching expected for an element. It distinguishes from sibling assert_element (element existence) and get_computed_styles (retrieval without assertion).

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 on when to use this tool versus alternatives like get_computed_styles or assert_element. No explicit when-to-use or when-not-to-use information.

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

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

No annotations provided, and description only mentions return values. Lacks details on side effects, permissions, or whether the tool modifies state. Implies non-destructive but not explicit.

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

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

Two short sentences that convey the core function and context. No wasted words.

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

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

No output schema, so description must compensate. It mentions return values but lacks details on format or non-required parameters like tabId, apiKey. Adequate but not comprehensive.

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

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

Schema covers 100% of parameters with descriptions. Description adds no extra meaning beyond schema; baseline 3 justified.

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

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

Description clearly states it asserts a condition on an element and returns pass/fail, actual value, and message. However, it does not differentiate from sibling assert tools like assert_css_property.

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 on when to use vs alternative tools like assert_css_property or assert_network_request_made. Simply says 'essential for automated testing workflows'.

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

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

With no annotations, the description should disclose behavioral traits. It only states the action without indicating side effects, return behavior, or error handling. The agent lacks insight into whether the assertion is blocking, idempotent, or modifies state.

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

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

The description is two concise sentences with no fluff. It front-loads the core purpose and efficiently provides 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?

Despite having 5 parameters and no output schema, the description fails to explain assertion behavior (e.g., timeout, matching logic, or result interpretation). It feels incomplete for a complex tool.

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

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

Schema coverage is 100%, so the description adds no extra parameter meaning beyond what is already documented. 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 explicitly states the action ('Assert') and the resource ('network request matching a pattern'), making it clear and distinct from sibling tools like 'get_network_logs' or 'intercept_requests'.

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 use cases ('verifying analytics, API calls, or resource loading') but does not specify when to avoid this tool or mention alternatives, leaving usage guidance implicit.

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

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

No annotations provided. The description does not clarify whether the tool waits for logs or checks current state, nor what happens on failure (e.g., throws an error). Key behavioral details missing.

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

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

The description is a single clear sentence with no unnecessary words. Well-structured and 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?

No output schema, but description mentions return fields. However, it omits important context for an assertion tool, such as whether it waits or how it handles failures. Adequate but incomplete.

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

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

All 4 parameters are fully described in the schema (coverage 100%). The description adds context about return values but does not significantly enhance parameter understanding beyond the schema.

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

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

The description clearly states the tool asserts no console errors for a tab, specifies it returns error count, list, and pass/fail, and distinguishes from siblings like get_console_logs.

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 mentions filtering by level but lacks explicit guidance on when to use this tool versus get_console_logs or monitor_console_events. No alternatives or exclusions stated.

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

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

The description discloses that the tool checks network errors and returns a count, list, and pass/fail. However, it does not explain side effects (e.g., optionally clearing logs via the clear parameter) or prerequisites like authentication (apiKey parameter). With no annotations, more detail would be beneficial.

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

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

Single sentence covers purpose and outputs with no fluff. Every phrase is essential and 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?

For a simple assertion tool, the description adequately explains return values (count, list, pass/fail) and mentions the tab scope. Missing details on side effects of clear and authentication, but overall sufficient given the tool's simplicity.

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% coverage, so description adds no extra meaning beyond what each parameter already defines. Baseline 3 is appropriate since schema already handles semantics.

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

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

The description clearly states the tool asserts no failed network requests (4xx, 5xx, or failed) and returns specific outputs. It uses a specific verb-resource pair, distinguishing it from sibling tools like get_network_errors which only retrieves errors.

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 alternatives like get_network_errors or clear_network_logs. The name implies it is for assertions in tests, but no when-not-to-use or alternative conditions are mentioned.

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

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

No annotations are provided, so the description must carry full burden. It does not disclose what happens on assertion failure (error thrown, boolean return), whether it modifies browser state, or if it logs anything, leaving agent guessing about 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?

Single sentence with no fluff. Front-loads the key purpose and metric. Efficiently conveys 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 simple assertion with no output schema and few optional params, the description is adequate but incomplete. It does not specify return type or error behavior, which is notable for a tool that could break a test flow.

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

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

Schema coverage is 100% with parameter descriptions. The description adds the specific metric (loadEventEnd) not in schema, providing extra context. However, it does not clarify the behavior of optional parameters like tabId or apiKey beyond schema defaults.

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 (assert), resource (page load time), and specific metric (loadEventEnd). It distinguishes from sibling assertions like assert_css_property or assert_element by focusing on performance timing.

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 alternatives such as assert_no_network_errors or get_performance_metrics. The description implies usage for load time thresholds but lacks context on prerequisites or when not to use it.

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

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

With no annotations provided, the description must fully disclose behavioral traits, but it fails to mention side effects, failure behavior (e.g., thrown exception or return value), or prerequisites like tab existence. It only states the verification action, leaving significant gaps.

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

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

The description is extremely concise: one sentence with two clear clauses. It is front-loaded with the primary action and immediately provides context. No wasted words, every part 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?

For a simple assertion tool with only two required parameters and no output schema, the description covers the essential information: what it compares and when to use it. However, it lacks details on failure behavior and edge cases, so it is slightly incomplete.

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

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

The input schema already fully covers all three parameters with descriptions (100% coverage). The description adds value by explaining the meaning of 'state' (URL, title, DOM hash), which is not present in the schema, enriching the parameter semantics context.

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

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

The description clearly states the tool's purpose: verifying two tabs have the same state by comparing URL, title, and DOM hash. It also provides a use case (cross-tab state sync testing), distinguishing it from sibling assertion tools like assert_element or assert_css_property.

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

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

The description explicitly mentions 'cross-tab state sync testing' as the intended use case, giving clear context for when to apply the tool. However, it does not explicitly state when not to use it or list alternatives, though the context is sufficient for an experienced user.

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 must disclose behavioral traits. It only says 'find' but does not state if it's read-only, whether it modifies the page, or what happens if no issues found. Lacks detail on 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?

Single sentence of 14 words, front-loaded with action and resource types. No wasted words.

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

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

No output schema; description fails to explain what the tool returns (list of errors? counts?). Also missing context on page load requirement or how results are formatted. Insufficient for an audit tool.

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

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

Schema coverage is 100% (both tabId and apiKey described in schema). Description adds no additional meaning beyond the schema, so baseline 3 applies.

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

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

Description clearly states the tool finds broken images, stylesheets, font errors, and other resource loading problems. It uses specific verbs and resource types, distinguishing it from siblings like assert_no_network_errors or check_font_loading.

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 on when to use this tool versus alternatives. No prerequisites or when-not-to-use scenarios 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 must cover behavioral traits. It states the tool reads the accessibility tree, implying non-destructive behavior, but does not disclose any side effects, permissions, or limitations.

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

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

Two sentences efficiently convey the tool's purpose and a key use case. No unnecessary 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?

The description is adequate for a simple read tool but lacks information about output format, data fidelity, or how it differs from the sibling 'get_accessibility_tree'. Without an output schema, some explanation of return value would be helpful.

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

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

Schema coverage is 100% with both parameters described. The description adds no extra meaning beyond the schema (e.g., defaults for tabId or when apiKey is needed). Baseline score of 3 is appropriate.

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

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

The description clearly states it retrieves a text-based accessibility tree snapshot, specifying the content (ARIA roles, names, states). It distinguishes from screenshots but not from sibling tool 'get_accessibility_tree'.

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 a concrete scenario ('when you cannot see screenshots') for when to use this tool. However, it does not specify when not to use it or mention alternatives like 'get_accessibility_tree'.

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

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

No annotations are provided, so the description must disclose behavioral traits. It does not confirm the tool is read-only, mention any side effects, or explain authentication requirements. The description only states the output, missing important behavioral context.

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

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

The description is two sentences long, front-loaded with the core purpose, and contains no extraneous information. Every word adds value.

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

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

Despite no output schema, the description mentions return values. However, it does not specify the output format (e.g., JSON structure) nor provide context for optional parameters like apiKey. The tool's behavior is adequately described for simple use, but lacks depth for complex scenarios.

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 (selector, tabId, apiKey). The description adds no additional meaning beyond the schema, merely restating the return value. A score of 3 is appropriate as schema covers parameter semantics adequately.

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

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

The description clearly states the tool checks color contrast ratios against WCAG AA and AAA standards, specifying it returns contrast ratios and pass/fail status. This is a specific action on a resource, but it does not explicitly differentiate itself from sibling tools like run_accessibility_audit, which may also evaluate 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?

The description provides no guidance on when to use this tool versus alternatives, such as get_computed_styles or run_accessibility_audit. It does not mention prerequisites, limitations, or contexts where this tool is preferred.

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

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

With no annotations, the description carries full burden. It indicates a read-only verification and mentions output fields, but does not disclose what happens if fonts fail to load, or the format of the status field. For a simple check tool, this is adequate but not fully transparent.

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

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

The description is two sentences with no fluff. The first sentence states the purpose, the second lists return fields. It is front-loaded and every word earns its place.

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

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

For a simple check tool with no output schema, the description covers the basic purpose and output fields. However, it lacks details like the format of the returned data (array or object), the meaning of 'status', and any prerequisites (e.g., fonts must be requested). It is minimally complete but could be more informative.

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

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

Schema coverage is 100% with both parameters (tabId, apiKey) described. The description adds no extra parameter meaning beyond the schema, so baseline 3 is appropriate. The description does not repeat or enhance parameter semantics.

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

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

The description clearly states the tool verifies web font loading and lists the return fields (family, status, weight, style). This distinguishes it from sibling check tools like assert_css_property or check_color_contrast, which focus on other aspects. However, it could be more explicit about the context (e.g., active tab) even though tabId parameter implies it.

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. Among many sibling check tools, an agent could benefit from hints such as 'Use this after page load to verify fonts, not for checking specific CSS properties.' The description only states what it does, leaving the agent to infer usage context.

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

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

No annotations are provided, so the description bears the full burden. It adequately states the tool returns validity details per element, but does not disclose behavior for missing selectors, error handling, or whether it has side effects. A read-only hint is missing.

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

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

Two concise sentences with no unnecessary words. The first sentence defines the main action, the second elaborates on output. Ideal for quick scanning.

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 and no output schema, the description sufficiently explains return values (validity details with example properties). It lacks details on potential errors or the structure of the response, but the level of detail is adequate for most use cases.

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 covers all 4 parameters with descriptions. The description adds value by listing example validation constraints (valueMissing, typeMismatch, patternMismatch) that the schema does not enumerate, providing richer context for the return format.

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 that the tool checks HTML5 form validation state for a form or form elements, listing specific validity properties like valueMissing and typeMismatch. It uses a specific verb ('Check') and resource ('HTML5 form validation state'), distinguishing it from sibling tools that focus on CSS properties, assertions, or page navigation.

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

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

The description implies usage for verifying form validation before submission, but it does not explicitly state when to use or not use this tool relative to alternatives. However, the purpose is clear enough that an agent can infer appropriate contexts.

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 states the tool 'inspects' headers, indicating a read operation, but does not disclose whether it re-fetches the page, uses cached data, or requires network access. Additional behavioral details are missing.

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, direct sentence that lists the headers inspected. No unnecessary words, well-structured for quick understanding.

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

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

The tool has no output schema, so the description should hint at the return format or results. It only lists the headers checked but not what the output contains (e.g., pass/fail, values). This limits completeness for an agent invoking the tool.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no extra meaning beyond what the schema provides for url, tabId, and apiKey. Baseline 3 is appropriate.

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

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

The description clearly states the tool inspects security-related HTTP response headers, listing specific ones (CSP, HSTS, etc.). This is a specific verb-resource combination that distinguishes it from sibling tools like get_network_logs or get_network_request_detail.

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

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

The description implies the tool is used to check security headers of a page, but does not explicitly state when to use it versus alternatives, nor does it provide exclusions or prerequisites. Context is clear but lacking guidance on when not to use.

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

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

No annotations; description implies destructive action but does not emphasize irreversibility or mention that it clears only for the specified tab. Basic transparency but could be improved.

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 unnecessary words; effectively communicates core purpose.

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

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

Simple tool with no output schema; description covers action and target. Additional context (e.g., typical use case) would improve completeness but not essential.

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% for both parameters. Description adds minimal value beyond schema; 'for a tab' is already implied by the tabId 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?

Description clearly states verb 'clear', resource 'network logs', and scope 'for a tab', distinguishing it from sibling tools like get_network_logs or get_network_errors.

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 on when to use (e.g., reset state before tests) or when not to use (e.g., when logs are needed). Alternatives like get_network_logs are not 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?

The description discloses human-like simulation (Bézier curves, randomized delays, natural timing), which adds behavioral context beyond the schema. However, it does not address failure cases (e.g., element not found) or potential side effects (navigation, state changes). Still, the disclosed trait is valuable for agent planning.

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

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

Two sentences, front-loaded with the primary purpose, followed by behavioral detail. No extraneous words; every sentence adds value.

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

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

For a simple clicking tool with well-documented parameters, the description covers the main aspects: what it does, when to use it, and simulation behavior. It lacks mention of return values (no output schema) or handling of invisible elements, but is nearly complete for typical 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?

Schema coverage is 100%, so parameters are fully described in the schema. The description does not add extra meaning to parameters beyond what is already present. Baseline 3 is appropriate as the description focuses on tool behavior, not 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 clearly states the action ('Click on any element on the page') and specifies the types of elements it applies to (buttons, links, checkboxes, dropdowns, or any interactive element). This provides a specific verb-resource pairing and distinguishes it as the general click tool among siblings like double_tap or hover_element.

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 context by suggesting usage for interactive elements, but does not explicitly differentiate from alternatives like double_tap, long_press, or hover_element. It implies single clicks but lacks explicit when-not-to-use or sibling comparisons.

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 available, so description carries full burden. Discloses that closed tabs cannot be recovered, which is key behavioral info. However, does not detail immediate effects or potential side effects beyond that.

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, concise and front-loaded. Every word serves a purpose with no redundancy.

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

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

Given no output schema and simplicity of the tool, description covers purpose, usage, and critical warning. Lacks return value info but acceptable for a void-like operation.

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

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

Schema description coverage is 100%, but the description adds value by suggesting 'get this from list_tabs' for tabId, providing practical guidance 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 'Close a specific browser tab' with a specific verb and resource. It distinguishes itself from sibling tools like list_tabs, select_tab, and new_tab.

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

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

Provides explicit context: 'Use this to clean up tabs you no longer need.' Includes a caution about non-recovery, which guides correct usage. Lacks explicit alternatives but context is sufficient.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It states the tool uses pixelmatch and returns results, but omits important details: whether it modifies any state, file size limitations, or required image properties (e.g., same resolution). This leaves behavioral ambiguity.

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

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

The description is two sentences, each earning its place: first states the action and method, second lists outputs. No filler or redundancy. Highly efficient and 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 4 parameters, no output schema, and no annotations, the description partially covers usage. It explains the return values (percentage, pixel count, diff image) but lacks prerequisites (e.g., images must be same size) or format of the diff image (base64 implied but not stated). Adequate but with clear gaps.

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

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

Input schema coverage is 100% and already parametrizes beforeImage, afterImage, threshold, includeDiffImage. The description adds context (pixelmatch, return values) but does not enhance understanding of parameters beyond the schema. Baseline score of 3 is appropriate given 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 explicitly states it compares two screenshots pixel-by-pixel using pixelmatch, and lists the outputs (match percentage, mismatched pixel count, diff image). This clearly distinguishes it from sibling tools like diff_page_source (text-based) and compare_snapshots (likely different granularity).

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 on when to use this tool versus alternatives. While the name implies pixel-level comparison, the description does not explicitly address trade-offs with compare_snapshots or other visual comparison tools, nor does it state prerequisites (e.g., same image dimensions).

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, yet description fails to disclose any behavioral traits such as output format, performance implications for large snapshots, error conditions, or side effects. Only states 'return the differences' without 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?

Two concise sentences that front-load the action and purpose with no wasted words. Every sentence adds value.

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

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

Minimally adequate for a simple comparison tool with well-documented parameters, but lacks details on output format and error handling, which are not covered by schema or annotations.

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

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

Schema descriptions cover all three parameters with clear explanations (e.g., mode: 'text (line-by-line) or dom (element-level)'), so the description adds minimal extra semantic value. Baseline of 3 is appropriate due to 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?

Clearly states 'compare two page state snapshots' and 'return the differences', with explicit purpose to verify state changes after an action. Distinguishes from siblings like diff_page_source and compare_screenshots by naming the source tools (browser_snapshot, read_page_html).

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 a clear use case ('verify state changes after an action') but does not specify when not to use this tool versus alternatives like diff_page_source or compare_screenshots. No exclusions or prerequisites 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 provided, and description only states the action without behavioral details (e.g., error on invalid path, return value format, side effects). Fails to disclose any behavioral traits.

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

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

Single sentence, 14 words, front-loaded with purpose. Every word contributes to clarity; no redundancy.

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

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

No output schema, yet description does not explain return value. Does not mention optional parameters like tabId or apiKey, leaving usage context incomplete for a 4-parameter tool.

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

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

Schema coverage is 100%, but description adds no meaningful interpretation beyond the schema. The phrase 'path of host selectors' mirrors the parameter description without additional 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?

Clear verb 'Query' and resource 'element inside a deep shadow DOM tree'. Distinguishes from siblings by mentioning 'deep shadow DOM', but does not explicitly contrast with 'query_shadow_dom' or 'get_shadow_dom_tree'.

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 on when to use this tool vs alternatives. No prerequisites, limitations, or conditions for use are mentioned.

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

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

No annotations provided; description only says 'Delete', which implies mutation, but no details on authentication (apiKey parameter exists), side effects, or permission 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?

One sentence, no wasted words. However, slightly under-specified for a destructive operation.

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 annotations or output schema, the description needs to cover more context (e.g., return value, prerequisites). Current form is adequate but minimal.

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

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

Schema covers all parameters with descriptions (100%), but tool description adds no extra meaning beyond what the schema already provides.

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

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

Description clearly states verb 'Delete' and resource 'a specific cookie', directly distinguishing it from sibling tools like set_cookie and get_cookies.

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 on when to use this tool versus cookie-related siblings (e.g., set_cookie, get_cookies). Agent must infer 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?

No annotations provided, so description carries full burden. It states the tool detects banners and returns text/button labels, which is honest but lacks details like whether it modifies the page, rate limits, or performance impact. Adequate but not rich.

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

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

Two sentences with no filler. First sentence defines purpose, second describes output. All content 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 simple functionality and full schema coverage, the description provides sufficient context for a detection tool. It explains return value structure (banners with text and button labels). Missing context on scope (entire page? iframes?) but acceptable for this complexity.

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

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

Schema description coverage is 100% with clear parameter descriptions. The tool description adds minimal extra meaning for parameters beyond the schema (only mentions return format). Baseline score appropriate.

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

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

The description clearly states the specific action (detect) and resource (cookie consent banners and CMP UI patterns), and distinguishes this tool from other sibling tools that focus on assertions or element properties. It provides a concise, unique purpose.

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

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

No guidance on when to use this tool versus alternatives. The description does not mention scenarios where this tool should be avoided or prerequisites (e.g., page must be loaded). Implied usage only.

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 fully disclose behavior. It fails to state whether the tool modifies the page, requires special permissions, or returns a result. The lack of mention of return value or side effects 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?

Single sentence with 12 words, focused and front-loaded. Every word contributes to understanding the tool's core 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?

With no output schema, the description should clarify what the tool returns (e.g., a list of issues, boolean). It also omits prerequisites like page load state. For a detection tool, this is incomplete.

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

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

Schema coverage is 100%, so baseline is 3. The description does not add any additional meaning about the two optional parameters (tabId, apiKey) beyond what the schema 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 'detect' and resource 'layout problems', listing concrete examples (overflow, overlap, clipping, z-index issues). This clearly distinguishes it from sibling tools, which focus on other aspects like CSS properties or 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 implies it is for layout issue detection, but it does not provide explicit when-to-use or when-not-to-use guidance, nor mention alternatives among the many sibling tools.

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

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

No annotations are provided, so the description carries the full burden. It describes the types of differences returned but does not discuss performance, limits, or behavior for edge cases (e.g., malformed HTML). It does not contradict any annotations.

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: first defines the action and output, second gives usage context. No unnecessary words, every sentence earns its place.

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

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

No output schema exists, so the description partially covers return structure by listing types of differences. However, it lacks details on optional parameters (tabId, apiKey) and does not discuss potential constraints like size limits or performance implications for large HTML strings.

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

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

Schema coverage is 100%, with each parameter having a description. The description adds the context of structural comparison but does not provide additional meaning beyond the schema for the parameters themselves. Baseline score of 3 is appropriate.

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

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

The description clearly states the verb 'compare', the resource 'HTML strings', and the output 'differences (added nodes, removed nodes, attribute changes, text changes)'. It distinguishes from sibling tools like compare_screenshots by focusing on structural HTML comparison.

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

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

The description explicitly says 'Use this to detect DOM changes after an action', providing clear context. However, it does not mention when not to use it or contrast with similar tools like compare_snapshots, but the use case is well-defined.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It states the action (simulate double-tap) and the interval between taps, but does not explain if it triggers events, requires mobile emulation, or has side effects. Adequate but not highly transparent.

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

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

Two concise, front-loaded sentences. No redundancy, every word adds value.

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

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

Given moderate complexity (4 params, nested object) and no output schema, the description is nearly complete. It explains the action, targets, and typical use cases. Lacks mention of return value or success confirmation, but effect is user-visible.

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 parameters are already well-documented. The description adds context about use cases but no additional parameter-specific semantics beyond the schema.

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

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

The description clearly states it simulates a double-tap at coordinates or on an element, and lists concrete use cases (double-tap-to-zoom, double-tap-to-edit). This distinguishes it from sibling tools like click_element or long_press.

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 usage context ('useful for testing...') but does not explicitly say when not to use this tool or mention alternatives like swipe or pinch. No guidance on choosing between coordinates and element targets.

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?

The description adds 'Simulates realistic human drag speed,' which provides a behavioral trait beyond the schema. However, it lacks details on what happens on failure, whether the tool waits for drop, or any 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 two sentences, front-loaded with the primary action and examples, with no redundant information. Every sentence adds value.

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

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

Given no output schema, the description should ideally mention the return value or success indicator. It does not, so it is slightly incomplete. It adequately covers usage but not the outcome.

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

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

The input schema already has 100% coverage with descriptions for all parameters. The description does not add any additional meaning or clarifications beyond what is in the schema, so it meets the baseline.

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

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

The description clearly states the action ('drag an element from one location to another') and provides specific use cases (sliders, sortable lists, file upload drop zones), effectively distinguishing it from sibling tools like click_element or hover_element.

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?

It explicitly says 'Use this for...' which gives clear context on when to use the tool. However, it does not mention when not to use it or provide alternatives, but since it's the only drag tool, this is acceptable.

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 behavioral burden. It discloses that viewport, DPR, user agent, and touch are set automatically, but does not mention persistence, reversal, or side effects across tabs.

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: first states the core action, second explains the effects. Every word is relevant and there is no redundancy. Highly 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 no annotations or output schema, the description adequately covers purpose and effects. However, it lacks details on how to reset emulation, whether it persists, and any limitations, leaving some gaps for a state-modifying tool.

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

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

Schema coverage is 100%, so baseline is 3. The description adds context by listing device presets and stating the effects of emulation, but does not elaborate on tabId or apiKey parameters beyond what the schema 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?

Description clearly states it emulates device presets and lists examples (iPhone 14, etc.). It specifically mentions setting viewport, DPR, user agent, and touch emulation, distinguishing it from sibling tools like resize_viewport or emulate_network_conditions.

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

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

The description implies usage for responsive testing but lacks explicit guidance on when to use this tool versus alternatives like resize_viewport or reset_viewport. No when-not-to-use or alternative tool suggestions are provided.

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

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

Without annotations, the description bears full responsibility for disclosing behavioral traits. It mentions simulation and reset but omits important details such as whether the conditions persist across tabs, affect other tabs, require any permissions, or have side effects like clearing cache or cookies. The description fails to convey the scope and lifetime of the simulated conditions.

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

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

The description is three sentences long, front-loads the core purpose, and provides a key usage tip. Every sentence earns its place without redundancy or unnecessary detail.

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

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

The tool has 7 parameters, including optional tabId and apiKey, but the description does not explain how they affect behavior, default scoping, or what to expect when combining parameters. With no output schema and no annotations, the description should cover more details about the tool's behavior and limitations 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% coverage with decent descriptions for each parameter. The description adds value by specifically highlighting the reset parameter to restore normal conditions, which is not obvious from the schema alone. This enhances the agent's understanding of how to use the tool effectively.

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 simulates slow or offline network conditions for testing page behavior on poor connections. This distinguishes it from sibling tools like emulate_device (which focuses on device emulation) and network logging tools, but it does not explicitly differentiate from other network-related tools such as intercept_requests.

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 advises using the tool to test poor connections and mentions the reset parameter to restore normal conditions. However, it provides no guidance on when not to use it (e.g., for persistent network simulation across tests) or alternatives (e.g., intercept_requests for custom network manipulation).

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

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

Describes full access to page APIs, which is a key behavioral trait. However, without annotations, it should also disclose potential risks (e.g., page crashes, mutation side effects) and return behavior. The description is honest but not exhaustive.

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

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

Two concise sentences. First sentence defines the core action, second sentence frames its role and gives examples. Highly efficient and 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?

No output schema, so the description should explain return values. It does not mention that the return result of the JavaScript expression is returned. Also lacks error handling or promise resolution behavior. Given the tool's simplicity, this is a notable gap.

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 covers 100% of parameters with descriptions. The description adds no extra meaning beyond what the schema already provides for each parameter. Baseline score 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?

Clearly states it executes JavaScript in the page, positions itself as an escape hatch, and provides concrete examples (extract data, modify page, trigger events, check values). Distinguishes from sibling tools that are more 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?

Explicitly frames the tool as an escape hatch for tasks other tools cannot do, implying use when other tools are insufficient. Lacks explicit 'when not to use' or alternative suggestions, but the sibling list provides 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?

The description explains that role matching supports both explicit ARIA roles and semantic HTML, and that CSS/XPath bypass other filters. This adds behavioral context beyond the schema. However, it does not describe error handling or what happens if no element is found.

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

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

The description is three sentences, each serving a clear purpose: stating the function, providing usage guidance, and detailing behavioral nuances. There is no fluff, and key information is 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 8 parameters, no output schema, and no annotations, the description covers the core purpose, key behaviors, and parameter interactions. It could mention the return format or that the returned selector can be used with other tools, but it is largely complete.

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

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

Schema coverage is 100%, so the schema already describes parameters. The description adds significant value by explaining the semantic HTML fallback for role and the bypass behavior for css/xpath, which is not in the schema.

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

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

The description clearly states the tool finds an element by various methods (visible text, ARIA role, etc.) and returns a unique CSS selector and details. It distinguishes itself from sibling tools like click_element or hover_element that use the found element.

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

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

The description explicitly says 'Use this when you need to locate an element but don't know its exact selector.' It also explains AND logic for multiple filters. However, it does not mention when to prefer other tools like CSS/XPath alone or query_shadow_dom.

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

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

With no annotations, the description carries full burden. It discloses that search targets page HTML and loaded scripts, and describes return structure. However, it does not explicitly state that the operation is read-only or behavior when no matches found.

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 short sentences, no redundant words. First sentence states action, second states output. Efficient and front-loaded with core purpose.

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

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

Adequately describes what the tool does and returns, but lacks context on defaults for optional parameters (tabId, contextLines) and authentication requirement (apiKey). No output schema, but return structure is described. Could be more complete for a tool with 4 params and no annotations.

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 for all 4 parameters. The description adds no additional meaning beyond schema, e.g., it mentions 'context lines' but schema already documents contextLines. 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?

Description clearly states it searches for regex patterns in page HTML and loaded scripts, and specifies return values (file URL, line number, context). It distinguishes from sibling tools like read_page_html or read_scripts which don't offer regex search across both combined.

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?

Description implies when to use (to find a regex pattern in page source) but does not explicitly state when not to use or suggest alternatives. No exclusions or prerequisite conditions provided.

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

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

No annotations are provided, so the description carries the full burden. It explains the core behavior (forcing a state and reading styles) but lacks details on side effects (e.g., whether the state is temporary, if it affects other elements, or cleanup). The apiKey parameter suggests authentication needs, but this is not addressed.

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: the first states the action and resources, the second states the use case. Every word serves a purpose, and the most important information is front-loaded. No redundant or vague phrasing.

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

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

The description covers the core action well but does not specify the return value format or structure (no output schema). It also does not explain the optional parameters (tabId, apiKey) or their defaults. For a tool that returns computed styles, additional context about the output would be helpful.

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

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

The input schema has 100% description coverage for all parameters. The description adds overall purpose but does not elaborate on individual parameters beyond what the schema provides. Baseline 3 is appropriate as the schema already documents each 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 clearly states it forces a CSS pseudo-state and reads computed styles. It lists specific pseudo-states and the use case for testing state styles without interaction, distinguishing it from siblings like hover_element and get_computed_styles.

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

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

The description implies when to use the tool ('testing CSS state styles without actual interaction'), providing clear context. However, it does not explicitly mention when not to use it or alternatives, though the sibling tools make these evident.

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

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

With no annotations, the description only says the tool returns a JSON representation. It does not disclose whether it is read-only, what happens if the selector is invalid, or any side effects. Minimal behavioral context is provided beyond the output format.

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

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

Two sentences with no unnecessary words. The purpose is front-loaded, and the companion mention is concise. Every sentence adds value.

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

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

Given the complexity of an accessibility tree and the lack of an output schema, the description is too brief. It does not explain the structure of the returned JSON, performance implications, or behavior when no selector matches. More details are needed for full 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 coverage is 100% with descriptions for all three parameters. The description adds that a selector can filter a subtree, but does not elaborate on default behavior or error cases. Since the schema already describes the parameters, the baseline of 3 is appropriate.

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

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

The description clearly states the tool retrieves the raw accessibility tree as structured JSON, distinguishing it from the sibling tool 'browser_snapshot' which returns formatted text. It also mentions optional subtree filtering, providing a specific verb and resource.

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

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

The description provides context by naming the companion tool 'browser_snapshot' and hints at filtering, but it does not explicitly state when to use this tool versus other accessibility-related siblings like 'run_accessibility_audit' or 'get_shadow_dom_tree'. There are no exclusions or when-not-to-use 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 provided, and the description does not disclose read-only nature, output format, or any side effects. It is unclear whether the tool affects the page or requires permissions.

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

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

One sentence, front-loaded with the core purpose. No unnecessary words or redundancy.

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

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

For a tool with 3 optional parameters and no output schema, the description is too brief. It does not mention the return format, that breakpoints have defaults, or if it operates on the active tab's viewport.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema, such as explaining the breakpoints default behavior or apiKey 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 uses specific verb 'check' and resource 'CSS media queries' and 'breakpoints', clearly distinguishing from sibling tools that deal with computed styles or element states.

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 on when to use this tool versus alternatives like get_computed_styles or when not to use it. The description fails to provide context for appropriate usage.

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

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

No annotations provided, so description carries full burden. It discloses that resource inspection requires CDP debugger and may be skipped if Chrome DevTools is open. However, it does not mention the destructive potential of the 'clearAfter' 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?

Three sentences, each adding value: purpose, use case, and behavioral detail. Front-loaded and no wasted words.

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

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

Covers overall purpose and key behavioral nuance (CDP requirement). Missing mention of return value format and the clearAfter effect, but sufficient for a quick health check tool.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds context about the categories and CDP condition, but does not significantly enhance understanding of individual parameters 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 it is a unified diagnostic tool returning console errors, network errors, and broken resources. It distinguishes from sibling tools by naming alternatives for deeper inspection.

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

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

Explicitly says 'Use this for a quick health check' and provides when-not-to-use: for deeper inspection of a specific category, use the individual tools. This gives clear 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 present, so the description alone must inform the agent of behavioral traits. It does indicate a read operation, but fails to mention error handling (e.g., missing selector), authentication, or side effects. The agent has insufficient information to anticipate failures or 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 is a single, front-loaded sentence with no redundant information. Every word contributes to the core purpose, making it highly efficient for an agent to parse.

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 5 parameters and no output schema, the description should provide more context on return values or behavior. It does not specify the format of the returned computed styles (e.g., a map of property-value pairs), nor does it address error cases. This leaves significant gaps in understanding the tool's full 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, so each parameter is already documented. The description adds marginal value by summarizing the optional filtering and pseudo-element querying, but repeats what the schema conveys. Thus, baseline score of 3 is appropriate.

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

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

The description clearly states the tool retrieves computed CSS styles for an element, using a specific verb and resource. It mentions optional filtering and pseudo-elements, which helps differentiate from related tools like assert_css_property or get_element_state, though it does not explicitly contrast with siblings.

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 assert_css_property or modify_css. The description simply states what it does, without context on prerequisites, limitations, or conditions where another tool would be more 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, the description bears full transparency burden. It correctly indicates the tool gets console messages but does not disclose whether reading is destructive or if logs persist. The 'clear' parameter hints at one behavior, but the description itself is minimal on 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 two sentences with zero wasted words. The first sentence states the core functionality, the second provides usage context. Front-loading is optimal.

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

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

For a simple retrieval tool with well-documented schema and no output schema, the description is largely complete. It explains what is retrieved and common use cases. Minor gap: it does not specify the return format (e.g., array of objects with fields), but this is acceptable.

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% coverage with detailed descriptions for all parameters. The description adds no new meaning beyond the schema, e.g., it does not elaborate on the 'level' enum values or 'clear' behavior. Baseline 3 is appropriate given 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 console messages, using specific verbs and resource. It distinguishes from sibling tools like get_network_logs and assert_no_console_errors by focusing on console messages.

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 lists several use cases (debugging JS errors, seeing logs, verifying code) but does not explicitly mention when not to use this tool or provide alternatives. However, the context is clear enough for an agent to infer typical usage.

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

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

No annotations are present, so the description must carry the full burden. It does not disclose behavioral traits such as authentication needs (apiKey is in schema but not mentioned), side effects, or 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 sentence of 11 words with no extraneous information. It front-loads the action and resource, making it 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?

For a simple retrieval tool with no output schema, the description is adequate but lacks mention of return format, error conditions, or behavior when no cookies exist. It could be more helpful with typical usage examples.

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

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

Schema coverage is 100% with descriptions for all parameters. The description adds minimal extra value by clarifying that the url parameter defaults to the current page URL. This is sufficient for 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 clearly states the action ('get cookies') and the resource ('current page or a specific URL'). It distinguishes the tool from siblings like 'set_cookie' and 'delete_cookie' by specifying retrieval only.

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 (e.g., 'set_cookie', 'delete_cookie') or when not to use it. No context about prerequisites or limitations.

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

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

With no annotations, the description partially covers behavior by listing returned properties, but it does not disclose potential side effects, performance implications, whether it works on dynamic content, or if it requires page to be fully loaded. The default return behavior when no parameters are provided (likely returns for all visible) is implied but not explicit.

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

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

The description is two sentences, front-loaded with the primary purpose, and contains no redundant information. Every word contributes to understanding.

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

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

The description covers the basic purpose and return values, but given no output schema, it lacks details on the structure of the return (e.g., an array of objects or single object) and whether results are live or static. It also does not address edge cases like invisible elements or missing elements.

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

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

All 4 parameters have descriptions in the schema (100% coverage). The description adds context by explaining the purpose of selector and includeAll in relation to 'specific element or all visible', and lists the returned properties, which helps the agent understand parameter usage 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), resource (layout information), and scope (specific element or all visible elements). It specifies the returned values (bounding rectangles, etc.), which distinguishes it from sibling tools like get_computed_styles or get_element_state.

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_computed_styles or get_element_state. No when-not or prerequisite conditions are mentioned, leaving the agent to infer usage context.

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

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

Without annotations, the description carries the burden of disclosing behavioral traits. It states it gets state but does not clarify if it returns a single object, waits for elements, or throws on failure. Side effects are implied non-existent 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?

Two sentences with no wasted words. The purpose is front-loaded, and examples of state attributes are listed efficiently. Every sentence adds value.

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

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

While input schema is complete, the description lacks details about return format (e.g., whether it returns a boolean per attribute or a structure) and error handling (e.g., behavior when element not found). Could be more informative for a tool with no output schema.

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% (all parameters described), but the description adds value by enumerating the state attributes, giving insight into the output. This helps agents understand what the tool returns, partially compensating for the missing output 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 'Get the state of an element' and lists specific attributes (exists, visible, enabled, etc.), making the tool's purpose precise and distinct from sibling tools like assert_element or get_computed_styles.

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 says 'Essential for verifying element conditions during testing,' which implies a use case but does not explicitly distinguish when to use this tool versus alternatives like assert_element (which asserts conditions) or other get_* tools.

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

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

No annotations are present, so the description bears full responsibility for behavioral disclosure. It only states the basic read operation without discussing side effects, permissions, or limitations (e.g., storage is per-origin, authentication needed via apiKey).

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

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

The description is a single concise sentence that communicates the core purpose immediately. However, it is perhaps too brief; adding a few more details would improve completeness 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?

Given the lack of annotations and output schema, the description is insufficiently complete. It does not explain how tabId or apiKey affect behavior, nor any constraints or return format, leaving gaps for the agent.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no additional meaning beyond what is in the schema, resulting in a neutral 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 clearly states the verb 'Read' and resource 'localStorage entries', and specifies the scope ('for the current page'). However, it could be more precise by indicating that the operation can target a specific tab via the tabId parameter, which adds minor ambiguity.

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

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

No guidelines are provided about when to use this tool versus siblings like get_session_storage or set_local_storage. The description does not mention any context for appropriate usage, requiring the agent to infer from the name alone.

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

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

No annotations are present, so the description carries the full burden. It accurately states the tool retrieves only errored requests, but does not mention the 'clear' parameter's effect of clearing logs after retrieval, nor authentication requirements. Adequate but could disclose more 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?

Two clear, well-structured sentences with front-loaded purpose and no extraneous words. Every sentence adds value.

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

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

The tool is simple with three parameters fully described in the schema and no output schema. The description covers the core purpose and usage context, but could mention the return format or behavior of the 'clear' parameter explicitly.

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 already documents all parameters. The description adds no additional meaning beyond what the schema provides, earning 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 clearly states it retrieves only failed/errored network requests, using specific verb 'Get' and resource 'network requests', and distinguishes from sibling tools like 'get_network_logs' which likely return all requests.

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

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

The description explicitly says 'Useful for debugging resource loading issues', providing clear context for when to use. It does not mention when not to use or alternatives, but the purpose implies that for successful requests one would use a different 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, the description carries the full burden. It notes logs are collected since attachment, a key behavioral detail, but omits potential side effects (e.g., logs preserved across calls?), permissions, or limitations. Adequate but minimal.

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

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

Two sentences with no waste. The first sentence conveys the core action and scope, the second lists key filter options. Information is front-loaded and efficiently packaged.

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

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

The description provides enough context for a retrieval tool: sources (logs since attached) and filtering options. Missing output format details, but siblings like get_network_errors also lack output schemas, suggesting a consistent pattern. Slightly incomplete for a new agent.

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

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

Schema coverage is 100% with clear parameter descriptions. The description mentions filter fields (URL pattern, method, status code, resource type), which maps to the filter object, but adds no new meaning beyond what the schema already provides. Baseline of 3 is appropriate.

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

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

The description clearly states the tool retrieves network request/response logs collected since the debugger attached, with optional filters. It distinguishes from siblings like get_network_errors (errors only) and get_network_request_detail (single request detail).

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

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

The description implies usage for debugging network activity but does not explicitly state when to use this tool versus alternatives like get_network_errors or clear_network_logs. No exclusion criteria or context provided.

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

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

Description adds that the tool returns headers and optionally the response body, but does not disclose important behavioral traits such as authentication requirement (apiKey), potential volatility of network requests, or whether the tab must be active. Given no annotations, more transparency would be beneficial.

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

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

Single concise sentence of 15 words, front-loaded with key information. No redundancy or filler.

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

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

With 4 parameters, no output schema, and no annotations, the description is adequate but incomplete. It mentions headers and body but omits other potential return fields (status, timing). Also does not address required apiKey or tabId, leaving gaps for agent 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?

Schema coverage is 100% with all parameters described. The description adds no additional parameter meaning beyond the schema, mentioning 'headers' and 'response body' which correspond to the requestId and includeBody parameters, but no new semantics.

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

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

Description clearly states the verb 'Get' and resource 'detailed information about a specific network request', including headers and optionally response body. It effectively distinguishes from siblings like 'get_network_logs' (lists all requests) and 'assert_network_request_made' (checks existence).

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 or when not to use this tool compared to alternatives. For instance, it does not contrast with 'get_network_logs' or 'get_network_errors'. The description implies its use but lacks direct usage context.

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

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

No annotations provided, so description carries full burden. It lists returned metrics but does not disclose side effects, prerequisites (e.g., page must be loaded), or whether calling it affects performance. Basic but acceptable.

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

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

Single sentence, front-loaded with the action and key metrics. No redundant information; every word adds value. Excellent 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?

While it lists metrics, it lacks context on return format or interpretation. With no output schema, more detail on how results are structured would be helpful. Also, sibling tools are not differentiated, but overall adequate for a simple retrieval tool.

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

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

Schema coverage is 100% with clear descriptions for both 'tabId' and 'apiKey'. The description adds no extra meaning beyond the schema, so 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 explicitly states 'Get page load performance metrics' and lists specific metrics (FCP, LCP, CLS, FID, memory usage), clearly distinguishing it from assertion tools like 'assert_page_load_time' by focusing on data retrieval.

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_network_logs' or 'assert_page_load_time'. Usage is only implied through the description of what it returns, missing context on when it's 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?

Description implies read-only, non-destructive operation, but does not disclose authentication requirements or side effects. With no annotations, description carries the burden but is minimal.

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, no unnecessary words, front-loaded with verb and resource.

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

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

No output schema, and description does not explain return format (e.g., object with keys/values). For a read tool, return value documentation is important.

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 schema already documents parameters. Description adds no extra meaning beyond the schema descriptions.

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

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

Description clearly states verb 'Read', resource 'sessionStorage entries', and scope 'for the current page'. Distinguishes from sibling tools like set_session_storage and remove_session_storage.

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 on when to use this tool versus alternatives like get_local_storage or set_session_storage. No context on 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 provided, so description must disclose behavior. It only states return type and operation, not what happens on missing element, multiple matches, or authentication requirements. Lacks depth.

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

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

Single sentence, front-loaded with purpose. Concise but could benefit from a bit more detail. No wasted words.

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

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

No output schema; description does not describe the return structure or format. Does not differentiate from sibling tools or cover edge cases. Incomplete for a 4-parameter tool.

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

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

Input schema has 100% description coverage, so baseline is 3. The description adds no extra meaning beyond the schema, e.g., explaining default maxDepth or tabId fallback.

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 returns the full shadow DOM tree as JSON for a given host element, using specific verbs and resource. It distinguishes from siblings like query_shadow_dom by specifying 'full' and 'JSON'.

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 on when to use this tool versus alternatives such as query_shadow_dom or deep_query_shadow_dom. No prerequisites or exclusions mentioned.

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

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

No annotations provided, so description carries full burden. It indicates the tool returns a static list, but does not disclose potential side effects (none expected) or error conditions. Adequate but could be more explicit about read-only nature and scope of elements.

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

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

Two sentences, front-loaded with purpose, then usage guidance. No extraneous 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?

No output schema, but description adequately explains what the tool returns (list of elements with CSS selectors and visibility flags). Sufficient for a simple retrieval tool without annotations.

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%; both parameters (tabId, apiKey) are described in the schema. Description adds no extra meaning beyond what the schema already provides.

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

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

The description clearly states the tool retrieves a static list of focusable elements with CSS selectors and visibility flags, and explicitly distinguishes it from the sibling tool 'record_focus_path'.

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

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

Provides explicit 'when to use' (one-time snapshot) and 'when not to use' (for interactive recording, use record_focus_path instead).

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

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

With no annotations, the description carries the burden of disclosing behavior. It states what is captured but does not explicitly state it is read-only or that it requires a valid tab. The lack of side-effect or permission info is acceptable for a simple read operation but could be more explicit.

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

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

Two sentences, no wasted words. The first sentence states functionality, the second provides context. Efficient and easy to parse.

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 and lack of output schema, the description adequately covers what the tool does. It could benefit from mentioning the return format or structure, but overall it is sufficient for an agent to understand its purpose and relationship to 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?

Schema coverage is 100% with clear parameter descriptions. The description adds no additional parameter meaning beyond the schema. Baseline score of 3 is appropriate as the schema already provides sufficient semantic detail.

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

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

Description clearly states the tool captures URL, title, and DOM hash for tab state comparison. It also specifies the use case of verifying cross-tab state sync, which distinguishes it from sibling tools like get_element_state or snapshot_page_state.

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 a clear usage context (verifying cross-tab state sync) and implies when to use. However, it does not explicitly mention when not to use or suggest alternative tools, leaving room for improvement.

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 checks multiple tooltip sources (title, aria, CSS, custom), which adds some transparency. However, it does not specify the return format (e.g., string, null), error handling, or potential side effects like triggering events or modifying the page. The disclosure is partial.

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

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

The description is a single sentence that efficiently conveys the core action and the list of tooltip sources. It avoids unnecessary words and is front-loaded with the verb 'Hover over an element and extract any tooltip text.' However, it could be slightly more structured (e.g., listing sources in a bullet) without being verbose, but overall it is well-optimized.

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

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

The tool has moderate complexity (4 parameters, nested target object, no output schema). The description covers the hover action and sources, but it does not explain the return value (e.g., does it return a string or null?), error cases (e.g., if no tooltip found), or edge cases like overlapping tooltips. Given no output schema, the description should provide more context on what the agent receives.

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

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

Schema description coverage is 100%, with all parameters already described in the input schema. The tool description adds no additional parameter semantics beyond what the schema provides. For example, waitForTooltip's schema already explains the timeout purpose. The description does not clarify parameter behavior or constraints further, so baseline score of 3 applies.

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

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

The description clearly states the tool's action (hover and extract tooltip text) and the specific sources it checks (title attribute, aria-describedby, aria-labelledby, CSS tooltips, custom components). This distinguishes it from sibling tools like hover_element, which only hovers without extraction, and get_element_state, which may not extract tooltip content.

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

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

The description implies usage when tooltip text extraction is needed after hovering, but it does not explicitly state when to use this tool versus alternatives like hover_element or find_element. No exclusions or alternative recommendations are provided, leaving the agent to infer context from sibling tool names.

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 responsibility for behavioral disclosure. It only indicates a read operation, but does not mention permissions, side effects, or constraints beyond 'get'.

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

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

Single sentence, no redundant words, efficiently conveys the tool's purpose without fluff.

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 0 required parameters, no output schema, and moderate complexity (multiple data points), the description lists outputs but omits the response structure. Adequate but not fully complete.

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

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

Schema coverage is 100%, with both parameters described in the schema. The description adds no additional meaning beyond listing outputs, meeting the baseline for high 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 verb 'Get' and the resource 'current viewport dimensions, device pixel ratio, viewport meta tag, screen info, and user agent', distinguishing it from sibling tools like get_element_layout or get_performance_metrics.

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

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

No guidance is provided on when to use this tool versus alternatives (e.g., resize_viewport, emulate_device, get_active_media_queries). The description lacks context for selection.

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

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

The description discloses that the tool performs a hover and then captures changes, but it does not detail potential side effects, timing, or authentication requirements. With no annotations, more behavioral context would be beneficial.

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

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

Two sentences, highly concise, and front-loaded with the main purpose. Every sentence adds value without redundancy.

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

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

The description gives the overall purpose and usage examples, but does not explain what format the captured changes are returned in. Since there is no output schema, more detail on the return value would improve completeness.

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

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

The input schema has 100% description coverage, so the description adds little extra parameter meaning beyond the schema. The usage examples provide some context for the target parameter, but not enough to raise the score.

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

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

The description clearly states the action ('Hover over an element and capture any resulting DOM or style changes') and the specific use cases, distinguishing it from sibling tools like hover_element that only hover without capturing changes.

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?

It provides concrete usage scenarios ('testing dropdown menus, tooltips, and hover effects'), guiding when to use the tool. It does not explicitly mention when not to use it, but the context is clear enough.

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