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

With no annotations, the description carries the full behavioral burden. It usefully discloses the input dependency (it consumes results from already-run tests) and the output format (Markdown), but never says whether the report is returned inline, written to disk, or requires specific permissions, nor whether existing reports are overwritten.

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?

Front-loaded with the core action and a scannable bullet list of capabilities, then the routing guidance. Minor redundancy: 'Generate a comprehensive Markdown report' is restated as 'Formats results in a readable Markdown report,' costing a little space.

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

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

With no output schema and no annotations, the description does explain the aggregation inputs, scoring/status calculation, prioritization, and format, which is most of what an agent needs. The remaining gap is the delivery mechanism of the report (returned content vs. file artifact) and whether prior results must be persisted. Still largely complete for this tool's complexity.

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

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

Schema description coverage is 100% and both parameters (url, title) are documented in the schema, which already notes title is optional and custom. The description adds no format, default, or validation detail beyond the schema, so the 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?

States a specific verb and resource ('Generate a comprehensive Markdown report from test results') and enumerates exactly what it aggregates: visual, functional, performance, accessibility, and SEO results. It is clearly distinguishable from the run_* siblings, which produce test results rather than a consolidated report.

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?

Gives an explicit when-to-use rule ('Use this tool after running individual tests to create a final report') and names the alternative path with its selection condition ('Call run_full_test to automatically run all tests and generate a report in one step'). Nothing is left to inference.

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 the description carries the full burden. It discloses a meaningful dependency (chrome-devtools-mcp must be running for DOM/accessibility tree inspection), which is valuable. However, it doesn't describe read-only vs. mutating behavior, runtime cost, or what the results look like despite no output schema.

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?

Front-loaded purpose followed by a scannable bullet list of analyzed aspects, then usage and prerequisites. Slightly verbose with the six-bullet enumeration, but each bullet adds concrete scope. Efficient overall.

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

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

For a tool with no annotations and no output schema, this captures purpose, scope, and a key runtime prerequisite, but omits result format, whether it mutates anything, and how to interpret findings vs. sibling tools. Adequate but incomplete for a multi-faceted analysis 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 url, wcagLevel, and includeWarnings with defaults. The description's mention of WCAG 2.1 at Level A, AA, or AAA loosely reinforces the wcagLevel parameter but adds no syntax or format detail beyond the schema. Baseline 3 is correct.

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

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

States a specific verb (perform) and resource (accessibility testing on a web application), then enumerates exactly what it analyzes (WCAG compliance, contrast, ARIA, keyboard nav, forms, alt text). This clearly distinguishes it from siblings like run_visual_test and run_seo_test.

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?

Says 'Use this tool when you need to evaluate a website's accessibility for users with disabilities,' which implies usage but doesn't explicitly contrast against alternatives like run_full_test or run_visual_test, which likely also touch accessibility. A prerequisite is given (chrome-devtools-mcp must be running), which helps, but no 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 are provided, so the description carries the full behavioral burden. It says tests are run and a report is generated but discloses nothing about duration/cost of an all-tests run, side effects (browser sessions, network traffic against the target URL), auth requirements, or failure handling when one category fails.

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

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

A single front-loaded sentence with no filler: the action, the scope (all test categories enumerated), the target, and the outcome (comprehensive report) all land in one pass.

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 one fully documented parameter and no output schema, the description covers the basic call contract. However, for a potentially long-running aggregate operation with no annotations, it omits what the report contains and how it relates to generate_report, leaving the agent with an incomplete behavioral picture.

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

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

There is a single parameter (url) with 100% schema description coverage, so the schema already fully documents it. The description adds no format, validation, or environment nuance (e.g., localhost vs public URL) beyond what the schema states, 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?

The description gives a specific verb (run) and resource (all available tests on a web application) and enumerates exactly which test categories are covered: visual, functional, performance, accessibility, SEO. This implicitly separates it from the single-category siblings, but it never explicitly says it is the aggregate alternative to run_visual_test/run_functional_test/etc., so it stops short of full sibling differentiation.

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

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

No when-to-use guidance is given. Nothing tells the agent to prefer this over running the individual sibling tools, nor when a narrower single test (e.g., run_visual_test) would be more appropriate, nor whether it is meant to be paired with generate_report or already includes report generation.

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 behavioral burden, and it does add one genuinely useful non-obvious fact: the tool requires chrome-devtools-mcp to be running. It omits other behavioral traits an agent needs, such as expected runtime, whether it navigates away from or mutates page state, and handling of failures or timeouts.

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

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

Front-loads the purpose followed by a scannable bulleted list of analyzed element types, and closes with usage plus the dependency note. The bullets are slightly padded but every line is informative and there is no 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?

For a browser-automation test tool with no output schema and no annotations, the description should say what comes back (per-area findings, pass/fail, error list). It never describes the result shape, and the chrome-devtools-mcp dependency is mentioned but not elaborated on (install, config, failure 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?

Schema description coverage is 100%, so all four parameters including their default values are already documented in the schema. The description's list of analyzed categories loosely maps to the checkForms/checkLinks/checkInteractions flags but adds no new syntax, constraints, or interaction semantics, so the 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?

States a specific verb and resource ('Perform functional testing on a web application') and enumerates the four areas of analysis, which lets an agent distinguish it from run_visual_test or run_performance_test. However, it never names its closest siblings, and its inclusion of 'accessibility' and 'broken link detection' overlaps run_accessibility_test and run_seo_test, leaving boundaries ambiguous.

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

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

'Use this tool when you need to verify that a website's features work correctly' is a stated use case but is generic enough to cover almost any sibling test tool. There is no when-not guidance, no mention of run_full_test or other alternatives, and no ordering or prerequisite workflow advice.

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 usefully discloses the runtime dependency on chrome-devtools-mcp, but says nothing about whether the test is non-destructive, how long multi-run averaging takes, or any rate/资源 constraints — meaningful gaps for a tool that launches a browser and traces a live page.

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?

Front-loaded with a clear purpose sentence, then a scannable bullet list of measured metrics, then the usage cue and prerequisite. The list is long but each item defines real output scope; slightly bulky but no filler sentences.

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, and the description partially compensates by enumerating the metric categories returned. Combined with the stated dependency, an agent has enough to call it correctly, though return format (raw JSON vs. report), runtime expectations, and error behavior remain unstated.

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 url, runs, and throttle (including the throttle enum). The description adds no detail on parameters — no guidance on choosing runs for stable averages or when 3g/4g throttling is appropriate — so the 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?

The description gives a specific verb (perform performance testing) and resource (web application) and enumerates the exact metric families it produces (Core Web Vitals, load timing, resource sizes, third-party impact). That detail implicitly separates it from siblings like run_visual_test or run_seo_test, though no sibling is named explicitly.

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

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

"Use this tool when you need to evaluate a website's loading performance and identify bottlenecks" states the selection condition clearly, and the final sentence adds a concrete prerequisite (chrome-devtools-mcp must be running). It does not discuss when to prefer run_full_test over this, or note exclusions, so it stops short of a 5.

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

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

With no annotations, the description must carry behavioral disclosure. It usefully discloses an environmental dependency ('requires chrome-devtools-mcp to be running for DOM inspection'), which is real context beyond the schema. It does not state whether the operation is read-only, whether it hits the live site, or any rate/timeout 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?

Front-loaded purpose, scannable bulleted breakdown of analysis areas, then usage guidance and the prerequisite. Every element earns its place; only a small amount of redundancy between the bullet list and the summary line.

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

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

For a single-URL read-analysis tool with a fully described 3-parameter schema and no output schema, the description is nearly sufficient: it conveys scope, when to use it, and the runtime dependency. It lacks any hint of the result shape or how findings are returned, but that is a minor 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?

Schema description coverage is 100%, so all three parameters (url, checkSocialTags, checkStructuredData) are already documented in the schema, including defaults. The description adds no parameter-level syntax or format guidance, 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?

States a specific verb+resource ('Perform SEO analysis on a web application') and enumerates exactly what domains are covered (meta tags, headings, content, technical SEO). This clearly separates it from run_visual_test/run_functional_test/run_performance_test/run_accessibility_test, though it never addresses overlap with run_full_test.

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?

'Use this tool when you need to evaluate a website's search engine optimization' gives a clear usage trigger, and the required chrome-devtools-mcp prerequisite is stated. However, there are no exclusions or explicit routing against the sibling tools (e.g. run_full_test), which likely also performs SEO checks.

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

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

No annotations are provided, so the description carries the full burden. It does add genuinely useful behavioral context – the external dependency on chrome-devtools-mcp and the viewport sweep – but says nothing about execution cost, timeouts, whether it is safe/non-destructive, or how results are surfaced.

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?

Front-loaded with the core action, followed by a tight bullet list of what is analyzed and a clear usage sentence plus prerequisite. The bullets each earn their place, though the list format is slightly heavier than needed for a three-parameter tool.

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

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

With no output schema, the description should ideally hint at what comes back (screenshots, pass/fail, report artifact), but it stops at what is analyzed. The prerequisite and analysis breakdown cover the input side adequately, leaving the result side underspecified.

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 url, fullPage, and viewports are already documented in the schema. The description's mention of mobile/tablet/desktop viewports loosely reinforces the viewports parameter but adds no syntax or default semantics beyond what the schema states.

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

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

States a specific verb ('Perform visual testing') and resource ('web application'), then enumerates the exact artifacts analyzed (screenshots, layout consistency, responsive design, alignment/spacing). The 'visual' scope implicitly separates it from the functional/performance/accessibility/SEO siblings, though it never names them explicitly.

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

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

"Use this tool when you need to evaluate the visual appearance and responsiveness of a website" gives a clear usage context, and the prerequisite (chrome-devtools-mcp running) is stated. However, it offers no explicit exclusions or routing to siblings like run_full_test or run_accessibility_test.

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