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Full website audit with prioritised fix plan

full_website_audit
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Runs parallel website checks for consent/tracking, speed/revenue, WCAG 2.2, domain/email health, and AI-search readiness, then merges results into one score and prioritized fix list.

Instructions

Runs the tracking & consent, speed & revenue, accessibility (WCAG 2.2), domain/email health and AI-search readiness checks IN PARALLEL on one website, then merges them into an overall score, an executive summary and a single fix list ranked by severity, legal/revenue impact and effort. Best first call for "audit my website" or "what should I fix first". Partial results are returned if one check fails. Starts one Apify run per check on the caller's Apify account (pay-per-event).

Input Schema

NameRequiredDescriptionDefault
urlYesPublic website URL, e.g. "https://example.com" (https:// is added if missing). Private/internal addresses are rejected.
checksNoWhich checks to run (default: all five). domain_email uses the URL's domain.
deviceNoEmulated device for the speed and UX checks; Google ranks on mobile.mobile
maxPagesNoPages per crawler-based check (keeps cost and time down).
waitSecsNoHow long to wait for results before returning status "running" with a runId (the scan keeps going; use get_audit_results). Default 240.
maxCostUsdNoTotal spend cap across all runs on YOUR Apify account (split evenly per check). Default: $2 per check.

Output Schema

NameRequiredDescriptionDefault
gradeYes
domainYes
dryRunYes
targetYes
fixPlanYes
sectionsYes
overallScoreYes
totalCostUsdNo
severityCountsYes
executiveSummaryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.5/5.0
Behavior5/5

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

Goes well beyond the annotations: discloses that checks run in parallel, that partial results are returned if one check fails, that it starts one Apify run per check on the caller's own Apify account (pay-per-event), and that the scan keeps running when waitSecs expires. These are the operational facts an agent needs before spending money or deciding to poll.

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?

Three sentences, front-loaded with what it does, then the routing hint, then failure-mode and billing behavior. No filler and no repetition of schema content.

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?

Output schema covers return shape, and the description supplies the remaining essentials: auth/billing model (caller's Apify account, pay-per-event), partial-failure semantics, and the async handoff to get_audit_results. Nothing an agent needs to call it 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 every parameter (url, checks, device, maxPages, waitSecs, maxCostUsd) is already documented in the schema, including defaults, enums and caps. The description adds only indirect context about the cost cap being spread across runs per check; baseline 3 is appropriate.

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?

States a specific verb+resource (runs five named audit checks in parallel on one website) plus the merged output: overall score, executive summary, severity-ranked fix list. This clearly distinguishes it from the sibling single-check tools (audit_tracking_consent, scan_speed_and_revenue, etc.) and from get_audit_results.

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?

Explicitly routes the agent: 'Best first call for "audit my website" or "what should I fix first"', and points to get_audit_results when waitSecs elapses with status 'running'. It doesn't state when to prefer the individual sibling checks instead of this aggregate, which is the only missing piece.

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