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PageSpeed analysis

analyze_page_speed
Read-only

Run PageSpeed Insights for a landing page to measure Lighthouse and real-user Core Web Vitals, then identify fixes that can reduce wasted ad clicks.

Instructions

Run PageSpeed Insights for a landing page — Lighthouse + real-user data.

Returns the performance score (0-100), lab Core Web Vitals (LCP, CLS, TBT, FCP), CrUX field data from real Chrome users where available (p75 LCP/INP/CLS/FCP/TTFB + FAST/AVERAGE/SLOW ratings), and the top improvement opportunities with estimated savings. When the page itself has too little traffic for field data, the origin-wide field data is returned instead, marked field.scope="origin".

Typical input is an ad final_url: slow landing pages depress Quality Score and waste paid clicks. Takes 10-30s; that is normal for a Lighthouse run.

PageSpeed Insights API: https://developers.google.com/speed/docs/insights/v5/about

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL of the page to analyze, e.g. an ad's final_url ("https://example.com/landing").
strategyNo"mobile" (default — most paid traffic) or "desktop".mobile

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.27.1
    • addedInput schema / properties / strategy / description
      Added value: +"\"mobile\" (default — most paid traffic) or \"desktop\"."
    • addedInput schema / properties / url / description
      Added value: +"Full URL of the page to analyze, e.g. an ad's final_url\n(\"https://example.com/landing\")."
  2. Addedv0.13.2
  3. Removedv0.13.0
  4. Addedv0.12.0

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the readOnly/openWorld annotations, the description discloses material behavior: the 10-30s latency, and the important fallback that origin-wide field data is substituted when the page lacks traffic, marked field.scope="origin". That fallback semantics is exactly the kind of non-obvious trait annotations cannot convey.

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

Conciseness4/5

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

Front-loaded with the core action and return payload, then usage context, then the API reference link. Every sentence carries information, though the multi-clause return enumeration is dense.

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?

Though an output schema exists, the description still orients the agent on what comes back and the origin-scope caveat. Combined with the latency note and input guidance, nothing needed to invoke this correctly is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents both url and strategy (including the mobile default and the paid-traffic rationale). The description's mention of ad final_url adds no meaning beyond the schema's own example.

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

Purpose4/5

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

The description names a specific verb+resource (run PageSpeed Insights for a landing page) and enumerates what it returns — score, lab CWV, CrUX field data, opportunities. However, it never distinguishes itself from the sibling tool landing_page_analysis, which an agent could easily confuse it with.

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?

It gives a clear context for use (typical input is an ad final_url, slow pages hurt Quality Score and waste clicks) and discloses expected runtime of 10-30s. It stops short of stating when NOT to use it or naming an alternative over landing_page_analysis.

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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