Run a Lighthouse audit on any URL to measure performance, accessibility, best-practices, and SEO. Choose device and categories to uncover optimization opportunities.
Run a Lighthouse audit on a URL
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| device | No | Device to emulate (defaults to mobile) | |
| categories | No | Categories to audit (defaults to all) | |
| throttling | No | Whether to apply network throttling (defaults to true) |
Changes observed during successful MCP inspections.
v0.1.17Input schema / properties / categories / items / enumPrevious value: -[
- "performance",
- "accessibility",
- "best-practices",
- "seo",
- "pwa"
-]New value: +[
+ "performance",
+ "accessibility",
+ "best-practices",
+ "seo"
+]v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only says 'Run a Lighthouse audit'. It does not mention what the audit produces (e.g., scores, report), whether it is time-consuming, if it requires network access, or any side effects. The agent gets no behavioral context beyond the obvious mutation-like action.
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, efficient sentence with no wasted words. It is appropriately short, though it could be improved by front-loading key behavior. It earns a 4 because conciseness is good, but it sacrifices necessary detail for brevity.
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 has 4 parameters, no annotations, and no output schema, the description is far from complete. It does not explain what the audit returns, how to interpret results, or any edge cases. An agent would not know what to do with the output or how the audit behaves. This is a significant gap for a tool with 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%, so each parameter has its own description in the schema (e.g., device, categories, throttling). The tool description adds no additional parameter meaning, but per the baseline rule, high schema coverage warrants a score of 3. The description does not compensate with extra context but also doesn't need to.
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 ('Run a Lighthouse audit') and the target ('on a URL'). It is a specific verb+resource combination, but it does not differentiate from the sibling tool get_performance_score, which likely also deals with Lighthouse scores. So it's clear but lacks sibling distinction.
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 get_performance_score. The description does not mention any prerequisites, constraints, or alternative scenarios. It simply states what it does, leaving the agent to guess when this is the appropriate choice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.