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argus_audit_full

Performs deep QA audit with Lighthouse scoring, responsive layout checks across 4 viewports, memory leak detection, hover-state regression, and accessibility snapshot. Returns JSON report with findings by severity.

Instructions

Deep QA audit — extends argus_audit with Lighthouse performance/accessibility scoring, responsive layout checks across 4 viewports (320/768/1280/1920px), memory leak detection via heap snapshot, hover-state regression detection, and accessibility tree snapshot. Returns full JSON report with findings by severity, Lighthouse scores, and layout overflow details. Use when argus_audit passes clean but visual or performance regressions are suspected. Requires Chrome running with --remote-debugging-port=9222.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL to audit, including protocol and path (e.g. https://example.com/dashboard). Must be reachable by the running Chrome instance.
criticalNoWhen true, console.error calls are escalated to critical severity. Set true for business-critical routes (login, checkout, dashboard) where any error is a blocker.
Behavior4/5

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

No annotations provided, so description carries full burden. It details the tool's actions (Lighthouse, responsive, memory, hover, accessibility) and output format. However, it does not explicitly state that it is read-only or if there are side effects like resource usage.

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?

Description is a single paragraph, somewhat dense but all sentences are informative. Could be structured with bullet points for clarity, but no wasted words.

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?

Given no output schema, the description adequately explains the report contents (findings by severity, Lighthouse scores, layout overflow). It covers the complexity of the tool's features without gaps.

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?

Schema covers 100% of parameters. Description adds context: url must be reachable, critical escalates console.error to critical severity, and suggests when to set critical to true.

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 it extends argus_audit with specific additional capabilities (Lighthouse scoring, responsive checks, memory leak detection, etc.) and distinguishes itself from the sibling tool argus_audit.

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

Usage Guidelines5/5

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

Explicitly says 'Use when argus_audit passes clean but visual or performance regressions are suspected' and mentions the prerequisite 'Requires Chrome running with --remote-debugging-port=9222.'

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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