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A1-x-Tech

Google CrUX MCP

Phone vs desktop vs tablet

compare_form_factors
Read-onlyIdempotent

Compare real-user performance across devices (phone, desktop, tablet) for a URL or origin, showing Core Web Vitals and traffic share per device.

Instructions

Compares real-user performance across device classes for an origin or URL: one aggregated all-devices record plus phone, desktop and tablet records (4 API requests = 4 quota units of the 150/min budget). Per device: p75 + rating per metric; traffic_share gives each device's fraction of page loads (from the unfiltered form_factors metric). Devices without enough data come back as {no_data: true} — expected for tablet almost always. Default metrics: the three Core Web Vitals. Provide exactly one of origin or url.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoA specific page URL, e.g. https://example.com/pricing/. Mutually exclusive with `origin`. Pass the final post-redirect URL (the API does not follow redirects); fragments and query params are stripped by the dataset. Single pages have fewer samples and often have no data — fall back to `origin` on a no_data result.
originNoSite origin — scheme + host only, e.g. https://example.com (no path, no trailing slash). Aggregates real-user data across ALL pages of the site. Mutually exclusive with `url`. http/https and www/non-www are distinct keys; use the canonical variant.
metricsNoMetric names to return; omit for all available metrics. Timings are integer milliseconds; cumulative_layout_shift is a string-encoded double. form_factors is only returned when form_factor is NOT set.
Behavior5/5

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

Beyond the annotations, the description discloses quota cost (4 API requests = 4 quota units of 150/min), the exact number and type of records returned (all-devices + phone/desktop/tablet), per-metric p75/rating, traffic_share semantics, and no_data behavior for insufficient data. This is rich behavioral context with no contradictions.

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

Conciseness5/5

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

The description is four sentences long, front-loaded with the core purpose, then packing quota, output structure, no_data semantics, and defaults without waste. Every sentence contributes essential information.

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

Completeness5/5

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

With no output schema, the description carries the full burden of explaining return values. It does so clearly: aggregated record plus per-device records, p75+rating per metric, traffic_share, and {no_data: true} for sparse devices. The behavior is fully specified for practical use.

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

Parameters4/5

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

The schema has 100% coverage with detailed parameter descriptions, so the baseline is 3. The description adds value by specifying the default metrics ('Default metrics: the three Core Web Vitals') and reinforcing the mutual exclusivity of origin/url. It does not need to repeat schema details, but the added default behavior justifies a 4.

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

Purpose5/5

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

The description clearly states the tool 'Compares real-user performance across device classes for an origin or URL', with a specific verb ('compares') and resource ('device classes'). It distinguishes itself from siblings by focusing on phone/desktop/tablet breakdown, reinforced by the title.

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

Usage Guidelines4/5

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

The description gives clear context on what the tool does and explicitly states 'Provide exactly one of `origin` or `url`', which is a key usage constraint. It also notes that tablet often returns no_data, guiding user expectations. However, it does not explicitly name alternative tools or state when to prefer this over them, so it falls 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.

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