Lighthouse MCP
Lighthouse MCP Server
Ein Model Context Protocol (MCP)-Server, der umfassende Web-Performance-Audits und Analysefunktionen mithilfe von Google Lighthouse bereitstellt. Dieser Server ermöglicht LLMs und KI-Agenten, detaillierte Website-Leistungsbewertungen, Barrierefreiheits-Audits, SEO-Analysen, Sicherheitsprüfungen und Core-Web-Vitals-Überwachung durchzuführen.
🌟 Hauptfunktionen
🚀 Leistungsanalyse: Vollständige Lighthouse-Audits mit Core Web Vitals, Leistungswerten und Optimierungsempfehlungen
♿ Barrierefreiheits-Audits: WCAG-Konformitätsprüfung und Analyse des Barrierefreiheits-Scores
🔍 SEO-Analyse: Suchmaschinenoptimierungs-Audits und Empfehlungen zu Best Practices
🔒 Sicherheitsbewertung: HTTPS-, CSP- und Sicherheitslücken-Scans
📊 Ressourcenanalyse: Optimierungsmöglichkeiten für JavaScript, CSS, Bilder und Schriftarten
📱 Mobil vs. Desktop: Vergleichende Analyse über Geräte hinweg mit Drosselungsoptionen
⚡ Core Web Vitals: LCP-, INP-, CLS-Überwachung mit Schwellenwertprüfung
🎯 Leistungsbudgets: Benutzerdefinierte Leistungsschwellenwerte und Budgetüberwachung
🤖 Agenten-Browsing: Lighthouse-13-Audits zur Bewertung, wie gut eine Seite KI-Agenten bedient (WebMCP-Tools, Agenten-Barrierefreiheitsbaum, llms.txt)
🧩 Strukturierte Ausgabe: Jedes Tool deklariert ein
outputSchemaund gibt validiertesstructuredContentzurück, sodass Clients typisierte Daten erhalten, anstatt einen JSON-String parsen zu müssen📚 Referenzressourcen: Integrierte Richtlinien und Best Practices für Web-Performance, Barrierefreiheit, SEO und Sicherheit
Related MCP server: mcp-seo
🛠️ Voraussetzungen
Node.js 22.0.0 oder neuer
Chrome/Chromium-Browser (wird automatisch von Lighthouse verwaltet)
VS Code, Cursor, Windsurf, Claude Desktop oder ein anderer MCP-Client
🚀 Erste Schritte
Installieren Sie den Lighthouse MCP server mit Ihrem bevorzugten Client mithilfe einer der folgenden Konfigurationen:
{
"mcpServers": {
"lighthouse": {
"command": "npx",
"args": ["@danielsogl/lighthouse-mcp@latest"]
}
}
}Persistente Chrome-Profile (Anmeldesitzungen)
Wenn Sie authentifizierte Sitzungen benötigen, starten Sie mit einem persistenten Chrome-Profil und führen Sie den Browser im sichtbaren Modus aus:
{
"mcpServers": {
"lighthouse": {
"command": "npx",
"args": [
"@danielsogl/lighthouse-mcp@latest",
"--profile-path",
"<profile-path>",
"--no-headless"
]
}
}
}Sie können zusätzliche Chrome-Flags mit --chrome-flag übergeben, z. B. --chrome-flag=--disable-gpu. Wenn der Flag-Wert mit -- beginnt und mit einem bekannten Optionsnamen übereinstimmt, bevorzugen Sie --chrome-flag=..., um zu vermeiden, dass er als Top-Level-Option geparst wird. Der Profilmodus deaktiviert das Zurücksetzen des Speichers durch Lighthouse, sodass Cookies und lokaler Speicher zwischen den Läufen erhalten bleiben. Wenn --user-data-dir auf ein fehlendes Verzeichnis verweist, wird es erstellt und als frisches Profil behandelt. Setzen Sie --profile-path auf den Profilpfad, der in chrome://version angezeigt wird (z. B. .../Default). Hinweis: Das Remote-Debugging von Chrome erfordert ein nicht standardmäßiges Benutzerdatenverzeichnis. Verwenden Sie daher ein dediziertes Profilverzeichnis anstelle des Systemstandards. Sie können --user-data-dir und --profile-directory auch separat übergeben, wenn Sie das bevorzugen. Das Anhängen mit --chrome-port allein erhält den Speicher nicht; fügen Sie ein Profil-Flag hinzu, um Sitzungen zu behalten.
CLI-Optionen
Unterstützte Laufzeit-Flags für den MCP-Server:
--profile-path <path>: Verwenden Sie den Profilpfad auschrome://version(leitet Benutzerdatenverzeichnis + Profilnamen automatisch ab)--user-data-dir <path>: Wiederverwenden eines Chrome-Profilverzeichnisses für persistente Sitzungen--profile-directory <name>: Auswählen eines Profils innerhalb des Benutzerdatenverzeichnisses--chrome-path <path>: Expliziter Pfad zur Chrome/Chromium-Ausführungsdatei (überschreibt die automatische Erkennung; berücksichtigt auch die UmgebungsvariableCHROME_PATH)--chrome-flag <flag>oder--chrome-flag=<flag>: Durchreichen zusätzlicher Chrome-Flags (wiederholbar)--chrome-port <port>oder--remote-debugging-port <port>: An eine vorhandene Chrome-Instanz anhängen, die mit aktiviertem Remote-Debugging gestartet wurde--headless: Headless-Modus erzwingen--no-headless: Headed-Modus erzwingen
Protokollierung
Lighthouse protokolliert nach stderr. Der Server belässt dies auf error, damit die Protokolle Ihres MCP-Clients nicht überflutet werden; setzen Sie LIGHTHOUSE_LOG_LEVEL beim Debuggen auf silent, info oder verbose (z. B. wenn Chrome nicht gestartet werden kann).
LIGHTHOUSE_LOG_LEVEL=verbose npx @danielsogl/lighthouse-mcp@latestWSL2 / Benutzerdefinierter Chrome-Pfad
Wenn die falsche Chrome-Binärdatei verwendet wird (z. B. Windows-Chrome anstelle der Linux-Binärdatei unter WSL2), legen Sie den Pfad explizit fest:
# Via CLI flag
npx @danielsogl/lighthouse-mcp@latest --chrome-path /usr/bin/google-chrome
# Via environment variable
CHROME_PATH=/usr/bin/google-chrome npx @danielsogl/lighthouse-mcp@latestIn Ihrer MCP-Konfiguration:
{
"mcpServers": {
"lighthouse": {
"command": "npx",
"args": ["@danielsogl/lighthouse-mcp@latest", "--chrome-path", "/usr/bin/google-chrome"]
}
}
}E2E-Smoke-Test (Profil)
Führen Sie ein echtes Audit mit einem persistenten Profil aus (verwenden Sie ein vorhandenes Profilverzeichnis und melden Sie sich bei Bedarf einmal an):
npm run smoke:profile -- --url https://example.com \
--profile-path "<profile-path>" \
--no-headlessE2E-Smoke-Test (An vorhandenes Chrome anhängen)
Starten Sie Chrome mit aktiviertem Remote-Debugging:
/path/to/GoogleChromeExecutable \
--remote-debugging-port=9222 \
--user-data-dir /path/to/chrome-profileErsetzen Sie /path/to/GoogleChromeExecutable durch den Chrome/Chromium-Binärpfad Ihrer Plattform.
Hängen Sie dann Lighthouse an diese Instanz an:
npm run smoke:profile -- --url https://example.com --chrome-port 9222Um den Speicher beim Anhängen zu erhalten, übergeben Sie den Profilpfad, damit Lighthouse Cookies/lokalen Speicher behält:
npm run smoke:profile -- --url https://example.com \
--chrome-port 9222 \
--profile-path "<profile-path>"Installation in VS Code
Sie können den Lighthouse MCP server auch über die VS-Code-CLI installieren:
# For VS Code
code --add-mcp '{"name":"lighthouse","command":"npx","args":["-y","@danielsogl/lighthouse-mcp@latest"]}'
# For VS Code Insiders
code-insiders --add-mcp '{"name":"lighthouse","command":"npx","args":["-y","@danielsogl/lighthouse-mcp@latest"]}'Nach der Installation ist der Lighthouse MCP server für die Verwendung mit Ihrem GitHub-Copilot-Agenten in VS Code verfügbar.
Installation in Cursor
Gehen Sie zu Cursor Settings → MCP → Add new MCP Server. Nennen Sie ihn „lighthouse", verwenden Sie den Typ command mit dem Befehl npx @danielsogl/lighthouse-mcp@latest:
{
"mcpServers": {
"lighthouse": {
"command": "npx",
"args": ["@danielsogl/lighthouse-mcp@latest"]
}
}
}Installation in Windsurf
Befolgen Sie die Dokumentation zu Windsurf MCP. Verwenden Sie die folgende Konfiguration:
{
"mcpServers": {
"lighthouse": {
"command": "npx",
"args": ["@danielsogl/lighthouse-mcp@latest"]
}
}
}Installation in Claude Desktop
Befolgen Sie die Anleitung zur MCP-Installation und verwenden Sie die folgende Konfiguration:
{
"mcpServers": {
"lighthouse": {
"command": "npx",
"args": ["@danielsogl/lighthouse-mcp@latest"]
}
}
}🔧 Verfügbare Tools
Der Lighthouse MCP server stellt die folgenden Tools für eine umfassende Webanalyse bereit:
🏁 Audit-Tools
Tool | Beschreibung | Parameter |
| Ein umfassendes Lighthouse-Audit durchführen |
|
| Barrierefreiheits-Score und Empfehlungen abrufen |
|
| SEO-Analyse und Empfehlungen abrufen |
|
⚡ Performance-Tools
Tool | Beschreibung | Parameter |
| Gesamt-Performance-Score abrufen |
|
| Metriken für Core Web Vitals abrufen |
|
| Performance über Geräte hinweg vergleichen |
|
| Gegen Leistungsbudgets prüfen |
|
| LCP-Optimierungsmöglichkeiten finden |
|
🔍 Analyse-Tools
Tool | Beschreibung | Parameter |
| Nicht verwendeten JavaScript-Code finden |
|
| Alle Website-Ressourcen analysieren |
|
🔒 Sicherheits-Tools
Tool | Beschreibung | Parameter |
| Umfassendes Sicherheitsaudit durchführen |
|
💬 Verfügbare Prompts
Der Lighthouse MCP server enthält wiederverwendbare Prompts, die LLMs dabei helfen, strukturierte Analysen und Empfehlungen bereitzustellen:
📊 Analyse-Prompts
Prompt | Beschreibung | Parameter |
| Lighthouse-Auditergebnisse analysieren |
|
| Vorher/Nachher-Auditergebnisse vergleichen |
|
| Optimierungsempfehlungen für Core Web Vitals abrufen |
|
| Empfehlungen zur Ressourcenoptimierung abrufen |
|
📚 Verfügbare Ressourcen
Der Lighthouse MCP server bietet integrierte Referenzressourcen mit wichtigen Richtlinien und Best Practices:
Resource | Description | URI |
| Leistungsschwellenwerte für Core Web Vitals |
|
| Leistungsoptimierungstechniken und Auswirkungen |
|
| WCAG-2.1-Barrierefreiheitsrichtlinien und -probleme |
|
| SEO-Best-Practices und Optimierungsmöglichkeiten |
|
| Best Practices für Websicherheit und Schwachstellen |
|
| Empfehlungen für Leistungsbudgets nach Website-Typ |
|
| Lighthouse-Auditkategorien und Bewertungsmethoden |
|
| Framework-spezifische Optimierungsleitfäden |
|
🎯 Strategie-Prompts
Prompt | Description | Parameters |
| Umfassenden Plan zur Leistungsverbesserung erstellen |
|
| Benutzerdefinierte Empfehlungen für Leistungsbudgets erstellen |
|
| Empfehlungen zur SEO-Verbesserung generieren |
|
| Leitfaden zur Verbesserung der Barrierefreiheit erstellen |
|
🔧 Details zu Prompt-Parametern
auditResults: JSON-Auditergebnisse von Lighthouse-ToolsfocusArea: Bestimmte Kategorie, auf die fokussiert werden soll ("performance","accessibility","seo","best-practices","agentic-browsing")beforeAudit/afterAudit: Lighthouse-Auditergebnisse vor und nach ÄnderungenchangesImplemented: Beschreibung der zwischen Audits vorgenommenen ÄnderungencurrentMetrics: Aktuelle Leistungskennzahlen aus AuditstargetGoals: Spezifische Leistungsziele oder Geschäftszieletimeframe: Zeitplan für die Umsetzung von Verbesserungenframework: Frontend-Framework oder Technologie-Stackconstraints: Technische oder geschäftliche EinschränkungenwebsiteType: Art der Website (z. B. E-Commerce, Blog, Unternehmen)targetAudience: Zielgruppe oder MarktinformationencomplianceLevel: WCAG-Konformitätsstufe ("AA"oder"AAA")userGroups: Bestimmte Benutzergruppen, die für die Barrierefreiheit zu berücksichtigen sind
📋 Parameterdetails
Allgemeine Parameter
url(erforderlich): Die zu analysierende Website-URLdevice: Zielgerät ("desktop"oder"mobile", Standard:"desktop")includeDetails: Detaillierte Auditinformationen einschließen (Standard:false)throttling: Netzwerk-/CPU-Drosselung aktivieren (Standard:false)
Spezifische Parameter
categories: Zu prüfende Lighthouse-Kategorien (["performance", "accessibility", "best-practices", "seo", "agentic-browsing"])threshold: Benutzerdefinierte Schwellenwerte für Kennzahlen (z. B.{"lcp": 2.5, "inp": 200, "cls": 0.1})budget: Leistungsbudget-Grenzwerte (z. B.{"performanceScore": 90, "largestContentfulPaint": 2500})resourceTypes: Zu analysierende Ressourcentypen (["images", "javascript", "css", "fonts", "other"])minBytes: Mindestdateigrößen-Schwellenwert für die Analyse (Standard:2048)checks: Durchzuführende Sicherheitsprüfungen (["https", "csp", "hsts", "origin-isolation", "clickjacking", "trusted-types", "third-party-cookies", "deprecations"])
💡 Anwendungsbeispiele
Grundlegendes Leistungsaudit
// Get overall performance score
{
"tool": "get_performance_score",
"arguments": {
"url": "https://example.com",
"device": "mobile"
}
}Core-Web-Vitals-Analyse
// Check Core Web Vitals with custom thresholds
{
"tool": "get_core_web_vitals",
"arguments": {
"url": "https://example.com",
"device": "mobile",
"includeDetails": true,
"threshold": {
"lcp": 2.5,
"inp": 200,
"cls": 0.1
}
}
}Sicherheitsbewertung
// Comprehensive security audit
{
"tool": "get_security_audit",
"arguments": {
"url": "https://example.com",
"checks": ["https", "csp", "hsts"]
}
}Ressourcenoptimierung
// Find optimization opportunities
{
"tool": "analyze_resources",
"arguments": {
"url": "https://example.com",
"resourceTypes": ["images", "javascript"],
"minSize": 1024
}
}Verwendung von Referenzressourcen
Auf integrierte Richtlinien und Best Practices zugreifen:
// Get Core Web Vitals thresholds
{
"resource": {
"uri": "lighthouse://performance/core-web-vitals-thresholds"
}
}
// Access WCAG accessibility guidelines
{
"resource": {
"uri": "lighthouse://accessibility/wcag-guidelines"
}
}
// Get framework-specific optimization guides
{
"resource": {
"uri": "lighthouse://frameworks/optimization-guides"
}
}Verwendung von Prompts für die Analyse
// Analyze audit results with focused recommendations
{
"prompt": "analyze-audit-results",
"arguments": {
"auditResults": "{...lighthouse audit json...}",
"focusArea": "performance"
}
}
// Create a performance improvement plan
{
"prompt": "create-performance-plan",
"arguments": {
"currentMetrics": "{...current performance metrics...}",
"targetGoals": "Achieve 90+ performance score and sub-2s LCP",
"timeframe": "3 months"
}
}
// Compare before/after audit results
{
"prompt": "compare-audits",
"arguments": {
"beforeAudit": "{...before audit results...}",
"afterAudit": "{...after audit results...}",
"changesImplemented": "Implemented lazy loading and image optimization"
}
}🎯 Anwendungsfälle
Leistungsüberwachung: Automatisierte Leistungsverfolgung und Core-Web-Vitals-Überwachung
Barrierefreiheitskonformität: WCAG-2.1-Konformitätsprüfung und Anleitung zur Behebung
SEO-Optimierung: Technische SEO-Audits und Empfehlungen zur Suchmaschinenoptimierung
Sicherheitsbewertung: Schwachstellenscanning und Validierung von Sicherheits-Best-Practices
Ressourcenoptimierung: Bundle-Analyse und Identifizierung von Optimierungsmöglichkeiten
Leistungsbudgets: Automatisierte Leistungsbudget-Überwachung und -Benachrichtigung
CI/CD-Integration: Automatisierte Qualitätskontrollen und Erkennung von Leistungsregressionen
🏗️ Architektur
Der Server basiert auf:
Model Context Protocol SDK: Für die MCP-Server-Implementierung
Google Lighthouse: Für Web-Performance-Audits
Chrome Launcher: Für die Browser-Automatisierung
TypeScript: Für Typsicherheit und bessere Entwicklererfahrung
Zod: Für die Laufzeit-Schemavalidierung
🧪 Tests
npm run test:run # unit tests
npm run test:coverage # unit tests with coverage
npm run test:e2e # end-to-end testsDie End-to-End-Suite erstellt den Server, startet ihn über stdio mit einem echten MCP-Client und führt echte Lighthouse-Audits gegen eine Testseite durch, die über Loopback bereitgestellt wird. Dafür muss Chrome installiert sein; setzen Sie CHROME_PATH, wenn es sich an einem nicht standardmäßigen Ort befindet.
🤝 Beitragen
Beiträge sind willkommen! Bitte lesen Sie unseren Beitragsleitfaden für Details zu:
Codestil und Standards
Testanforderungen
Pull-Request-Prozess
Entwicklungseinrichtung
📜 Lizenz
Dieses Projekt ist unter der MIT-Lizenz lizenziert – siehe die Datei LICENSE für Details.
🔒 Sicherheit
Bei Sicherheitsproblemen lesen Sie bitte unsere Sicherheitsrichtlinie.
📞 Support
🐛 Fehlerberichte: GitHub Issues
💬 Diskussionen: GitHub Discussions
📧 E-Mail: security@codingrules.ai
🙏 Danksagungen
Dem Google-Lighthouse-Team für die hervorragende Audit-Engine
Anthropic für die Model-Context-Protocol-Spezifikation
Der Open-Source-Community für kontinuierliche Inspiration und Beiträge
Erstellt mit ❤️ von Daniel Sogl
Available Tools
11 toolsanalyze_resourcesAnalyze Page ResourcesARead-only
Analyze website resources (images, JS, CSS, fonts) for optimization opportunities
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| device | No | Device to emulate (default: desktop) | desktop |
| minSize | No | Minimum resource size in KB to include | |
| resourceTypes | No | Types of resources to analyze |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| device | Yes | |
| filters | Yes | |
| summary | Yes | |
| resources | Yes | |
| timestamp | Yes | |
| optimization | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows this is a safe, read-only operation that may access external URLs. The description adds the focus on optimization opportunities but does not disclose details like whether it fetches live pages, handles redirects, or has rate limits. With annotations covering the safety profile, a 3 is appropriate – it adds some context but not rich behavioral detail.
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?
A single, clear sentence that front-loads the resource types and purpose. No waste, though it could be slightly more specific about the output or usage context. Efficient and to the point.
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 output schema exists and annotations cover safety, the description is adequate for a resource analysis tool. It doesn't explain return values (covered by output schema) or edge cases, but for a read-only analysis tool with 4 parameters, it is reasonably complete. Could benefit from mentioning that it analyzes a single URL or that it's for optimization, but these are minor gaps.
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 all four parameters are documented in the schema. The description adds the overall purpose but does not add syntax or format details beyond what the schema provides. Baseline 3 is correct when schema does the heavy lifting.
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 states a specific verb ('Analyze') and resource ('website resources') with a clear scope (images, JS, CSS, fonts) and purpose (optimization opportunities). It distinguishes from siblings like get_performance_score or get_seo_analysis by focusing on resource-level analysis, though it doesn't explicitly name a sibling it is not.
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?
The description implies usage for optimization analysis but does not explicitly state when to use this tool versus alternatives like find_unused_javascript or get_lcp_opportunities. The sibling list suggests related tools, but no exclusions or conditions are provided. The context is clear enough for a general audit, but lacks explicit routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_performance_budgetCheck Performance BudgetBRead-only
Check if website performance meets specified budget thresholds
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| budget | Yes | ||
| device | No | Device to emulate (default: desktop) | desktop |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| summary | Yes | |
| recommendations | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint: true and openWorldHint: true, indicating a read-only operation that may access external resources. The description adds no extra behavioral context—it does not mention that the tool will perform a live audit, make network requests, or have rate limits. While there is no contradiction, the description fails to disclose the operation's networked nature, which is a meaningful behavioral trait beyond the annotations.
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 filler. It conveys the purpose immediately and contains no redundant information. It earns a high score for being appropriately sized and front-loaded.
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's moderate complexity (nested budget object, optional device, output schema present), the description is minimal. It does not explain when to use it compared to siblings, nor does it clarify the semantics of the budget fields beyond what the schema provides. The output schema exists, so return values are covered, but the lack of usage guidance leaves the description somewhat incomplete for guiding an agent toward correct invocation in context.
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 67%: url and device have descriptions, but the budget object itself lacks a description at the top level. The inner properties are described, so the schema partially covers the main parameter. The description adds no additional meaning about how to structure the budget or interpret thresholds, leaving the agent to rely on the schema's inner property descriptions, which are adequate but not enriched.
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 tool's function: checking website performance against budget thresholds. It uses a specific verb ('check') and resource ('website performance'), and the notion of 'budget thresholds' distinguishes it from sibling tools that return raw scores or metrics. However, it does not explicitly name an alternative or contrast with similar tools like get_performance_score, so it is clear but not strongly differentiated.
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?
There is no guidance on when to use this tool instead of siblings such as run_audit, get_performance_score, or get_core_web_vitals. The description only states what it does, leaving the agent to infer appropriate use. No exclusions, alternatives, or preconditions are provided, so usage context is entirely absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_mobile_desktopCompare Mobile vs DesktopARead-only
Compare website performance between mobile and desktop devices
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| categories | No | ||
| throttling | No | Whether to throttle the audit (default: false) | |
| includeDetails | No | Include detailed metrics and recommendations |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| summary | Yes | |
| recommendations | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the description does not need to restate safety. However, it adds no extra behavioral context such as how the comparison is structured, whether it returns a single report or dual reports, or any throttling implications. With annotations covering the read-only nature, the description provides marginal added value.
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?
A single, front-loaded sentence with zero filler. It delivers the core purpose immediately and does not elaborate unnecessarily.
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?
The tool is simple, annotations cover safety, and an output schema exists so return format details are not required. However, the description lacks usage guidance and does not mention any special considerations (e.g., throttling, category selection) that an agent might need to know for effective invocation. It is minimally sufficient but not comprehensive.
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 75% (high), and all parameters have descriptive names and default values in the schema. The description adds no parameter-specific meaning beyond what the schema already provides. The baseline of 3 is appropriate.
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 states a specific action (compare) on a defined resource (website performance) between mobile and desktop devices. It clearly distinguishes itself from sibling audit tools like run_audit or get_performance_score, which focus on single-device audits or individual metric categories.
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 explicit guidance is given on when to use this tool versus alternatives. It does not mention that it is the preferred tool when a mobile/desktop comparison is needed, nor does it exclude cases where a single-device audit would suffice. The usage context is only implied by the tool's name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_unused_javascriptFind Unused JavaScriptBRead-only
Find unused JavaScript code to reduce bundle size
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| device | No | Device to emulate (default: desktop) | desktop |
| minBytes | No | Minimum unused bytes to report (default: 2048) |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| device | Yes | |
| summary | Yes | |
| timestamp | Yes | |
| unusedFiles | Yes | |
| thresholdBytes | No | |
| recommendations | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already carry readOnlyHint=true and openWorldHint=true, so the tool's non-destructive and open-world behavior is covered, and the description does not contradict the annotations. The description adds little beyond the generic 'find' behavior—no mention of how the scan is performed, what resources are fetched, or what output to expect—so it stays at the baseline for annotation-covered tools.
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 that immediately states the tool's core function. It avoids filler and front-loads the verb and resource, making it easy for an agent to parse at a glance.
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?
The tool is simple, and the schema, annotations, and output schema fill in a lot. However, the description does not mention the need for a URL or clarify how this audit relates to the many other audit siblings, leaving the agent without enough context to confidently choose and invoke it among the broader toolset.
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 coverage of the input parameters is 100%, so the baseline is 3. The description mentions bundle size, which loosely relates to minBytes, but it does not add detail about how url, device, or minBytes interplay; the schema carries the burden.
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 uses a specific verb ('Find') and a concrete resource ('unused JavaScript code'), and adds the motivating goal of reducing bundle size. It is clear enough to be distinguished from performance scoring tools, but it does not explicitly differentiate it from a sibling like analyze_resources, so it misses the 5 criterion.
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 given on when to use this tool versus alternatives such as get_performance_score, analyze_resources, or run_audit. There are no conditions, prerequisites, or exclusion criteria—only a one-line purpose statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_accessibility_scoreGet Accessibility ScoreBRead-only
Get the accessibility score and recommendations for a website
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| device | No | Device to emulate (default: desktop) | desktop |
| includeDetails | No | Include detailed metrics and recommendations |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| summary | Yes | |
| recommendations | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only restates the purpose and adds no behavioral traits beyond the annotations. Annotations declare readOnlyHint and openWorldHint, but the description does not disclose what an audit entails (e.g., live network request, duration, caching). Since annotations are present, the burden is lower, but the description adds no value.
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?
A single, clear sentence with no redundancy. The primary action and outcome are front-loaded. Perfectly concise.
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?
The tool is simple, has an output schema (though not shown), and full schema coverage. The description is adequate but omits context about how the audit is performed (live vs. cached) and what 'recommendations' entail. Given the complexity level, this is a minimum-viable description.
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% for all parameters, including device enum and includeDetails. The description does not elaborate on parameters, but the schema carries the full burden. Baseline 3 is appropriate.
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 verb 'Get' and the resource 'accessibility score and recommendations for a website'. It distinguishes itself from performance, SEO, and security siblings by naming the accessibility domain, but does not explicitly reference alternatives.
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 given on when to use this tool versus alternatives. It does not mention prerequisites, use cases, or exclusions. An agent would have to infer from the name that it is for accessibility audits only.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_core_web_vitalsGet Core Web VitalsARead-only
Get Core Web Vitals metrics for a website
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| device | No | Device to emulate (default: desktop) | desktop |
| threshold | No | ||
| includeDetails | No | Include detailed metrics and recommendations |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| summary | Yes | |
| recommendations | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and openWorldHint=true, meaning the tool performs a safe, read-only operation. The description adds no new behavioral information beyond the name, but given the annotations already cover the safety and non-mutating nature, the description's transparency is adequate. It does not contradict annotations, and the openWorldHint suggests the tool may reach external websites, which is not disclosed in the description but is implied by the term 'website'. The absence of details about rate limits or external dependencies is minor since the tool is read-only.
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, concise sentence that directly states the tool's purpose. Every word is meaningful; there is no fluff or repetition. It is appropriately front-loaded, with the verb 'Get' immediately clarifying the action. This is a model of conciseness.
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's complexity (4 parameters, nested threshold object, output schema present), the description is relatively sparse, but the robust input schema and presence of an output schema reduce the need for extensive description. The description covers the 'what' but not the 'how' or nuances like how thresholds affect evaluation or what 'detailed metrics' entails. With the output schema handling return values and the schema handling parameters, the description is sufficient for a read-only tool, so it slightly exceeds the minimum viable.
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?
The input schema already describes all parameters with reasonable detail (url, device, threshold object with fields, includeDetails). The schema description coverage is 75%, so most parameters are documented. The description does not add any additional meaning beyond what the schema provides; for example, it doesn't explain how thresholds are used or how includeDetails alters the output. With high coverage, the baseline is 3, and the description contributes minimal value.
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 'Get Core Web Vitals metrics for a website' clearly identifies the specific metrics (Core Web Vitals) and the resource (a website), using a precise verb. It is specific enough to distinguish it from generic measures like 'get_performance_score', though it could name a specific competitor (e.g., get_performance_score) to further differentiate. The title and description are aligned, with the description adding 'metrics' to clarify the resource.
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?
The description gives no explicit guidance on when to use this tool versus siblings such as 'get_performance_score' or 'compare_mobile_desktop'. However, the purpose is clear enough that an agent can infer it is for Core Web Vitals (LCP, INP, CLS) specifically, which is a subset of performance. There are no exclusions or alternatives mentioned, so the usage context is implied rather than explicit, warranting a mid-range score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_lcp_opportunitiesGet LCP OpportunitiesBRead-only
Get LCP optimization opportunities for a website
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| device | No | Device to emulate (default: desktop) | desktop |
| threshold | No | LCP threshold in seconds (default: 2.5) | |
| includeDetails | No | Include detailed metrics and recommendations |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| summary | Yes | |
| recommendations | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description itself adds little behavioral context, such as whether the tool performs a live network audit or how results are ordered, but it does not contradict the annotations.
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 front-loaded sentence with no filler or repetition. It states the essential purpose efficiently, and nothing extraneous is included.
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?
Output schema and complete parameter documentation reduce the need for the description to explain return values or parameters. However, the lack of usage guidance relative to sibling tools and the absence of operational caveats leave the overall context only adequate, not fully complete.
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%, and each parameter is documented with types, defaults, enums, and constraints. The description adds no additional parameter-level meaning beyond what the schema already provides, so the baseline of 3 is appropriate.
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 identifies the verb ('Get') and resource ('LCP optimization opportunities for a website'), so an agent understands the tool's core purpose. It does not explicitly distinguish itself from sibling tools such as get_core_web_vitals or get_performance_score, but the LCP-specific focus provides reasonable differentiation.
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 about when to use this tool versus alternatives like get_core_web_vitals, get_performance_score, or run_audit. There are no stated exclusions, prerequisites, or context cues, leaving the agent to infer selection based solely on the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_performance_scoreGet Performance ScoreCRead-only
Get the performance score for a website
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| device | No | Device to emulate (default: desktop) | desktop |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| summary | Yes | |
| recommendations | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds no behavioral information beyond the annotations. It does not state that the tool fetches a live URL, runs a Lighthouse audit, or that it may take time or require network access. With readOnlyHint and openWorldHint already provided, the description contributes nothing extra.
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 concise for the tool's simplicity, though it is not front-loaded with any additional context because there is none.
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?
For a simple two-parameter tool with an output schema, the description is minimally adequate but lacks key contextual details such as what constitutes a 'performance score' (e.g., Lighthouse metric), prerequisites like URL accessibility, or any potential variability. Given the existence of siblings, it is not sufficiently complete to guide correct selection.
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 coverage is 100% as both 'url' and 'device' are described in the input schema. The description adds no additional meaning about the parameters or their usage, so the baseline of 3 is appropriate.
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 uses a specific verb ('get') and resource ('performance score for a website'), making the intent clear. However, it does not differentiate from nearby siblings like get_core_web_vitals or get_lcp_opportunities, which also relate to performance metrics, so there is a mild ambiguity.
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?
There is no guidance on when to use this tool versus alternatives such as get_core_web_vitals or analyze_resources. No exclusions or recommended contexts are provided, leaving an agent to infer the appropriate choice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_security_auditGet Security AuditARead-only
Perform security audit checking HTTPS, CSP, and other security measures
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| checks | No | Specific security checks to perform | |
| device | No | Device to emulate (default: desktop) | desktop |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| summary | Yes | |
| recommendations | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered; the description adds that it checks HTTPS/CSP and 'other security measures', which is useful but thin. It does not mention network behavior toward the target URL or response characteristics, though openWorldHint partially implies external access. No contradiction with annotations.
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?
A single sentence that front-loads the action ('Perform security audit') and gives concrete examples of check types. The tail 'and other security measures' is slightly vague but functions as a pointer to the schema's enum without bloating the text.
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?
With an output schema present, full parameter documentation in the schema, and annotations covering the read-only/open-world safety profile, the description is largely sufficient for correct invocation. The notable gap is the missing relationship to 'run_audit', which is the one sibling that could genuinely confuse tool selection.
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% — url, checks, and device are all documented in the input schema, so the description carries no required burden. The mention of 'HTTPS, CSP' marginally reinforces the enum values in the 'checks' parameter, but adds little beyond the schema's own descriptions.
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 names a specific verb+resource ('security audit') and concrete focus areas (HTTPS, CSP), which cleanly separates it from the nine accessibility/SEO/performance siblings. However, it does not distinguish itself from the overlapping sibling 'run_audit', whose scope is left undefined, so an agent cannot fully tell them apart.
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?
Usage is implied by the security focus and the 'checking HTTPS, CSP' phrasing, which suggests this is the tool for security-related audits. There is no explicit statement of when to prefer it over 'run_audit' or when not to use it, leaving the selection logic to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_seo_analysisGet SEO AnalysisCRead-only
Get SEO analysis and recommendations for a website
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| device | No | Device to emulate (default: desktop) | desktop |
| includeDetails | No | Include detailed metrics and recommendations |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| summary | Yes | |
| recommendations | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds no further behavioral context such as rate limits, time expectations, or the nature of external fetches, offering minimal value beyond the annotations.
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, front-loaded sentence that efficiently states the core purpose. It is appropriately concise for a tool whose parameters and return format are fully specified in the schema.
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 large set of specialized audit siblings, the description is thin on context for selection. It doesn't mention that this provides a comprehensive overview or when to prefer it over targeted tools, and it omits any note about output shape (though the output schema covers that). The lack of usage guidance undermines completeness.
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?
The schema provides full descriptions for all three parameters at 100% coverage. The description adds no extra meaning, so the baseline of 3 applies. Nothing is lacking in terms of parameter documentation.
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 tool retrieves SEO analysis and recommendations for a website, using a specific verb and resource. While it doesn't explicitly contrast with sibling audit tools, the name and resource make it distinct from performance, accessibility, and security-specific tools.
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?
The description provides no guidance on when to choose this tool over alternative audit or metric tools. An agent must infer from the name that it covers general SEO, with no explicit exclusions or references to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_auditRun Lighthouse AuditBRead-only
Run a comprehensive Lighthouse audit on a website
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to audit | |
| device | No | Device to emulate (default: desktop) | desktop |
| categories | No | ||
| throttling | No | Whether to throttle the audit (default: false) |
Output Schema
| Name | Required | Description |
|---|---|---|
| data | Yes | |
| summary | Yes | |
| recommendations | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and openWorldHint=true, so the agent knows this is a safe read operation. The description adds 'comprehensive' but doesn't disclose behavioral traits like the fact that it runs multiple categories, the time it takes, or that it may be slower than targeted audits. With annotations covering safety, the description adds minimal behavioral context beyond the word 'comprehensive'.
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 sentence with no waste. It's front-loaded with the verb and resource. It could be slightly more informative, but it's concise and to the point.
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?
The tool has an output schema (not shown) and 4 parameters with 75% schema coverage. The description is minimal but the schema and annotations carry some weight. However, given the complexity of a Lighthouse audit (multiple categories, device emulation, throttling), the description could explain what 'comprehensive' means and how it relates to the sibling tools. It's adequate but not complete.
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 75%, so most parameters are documented in the schema. The description doesn't add any parameter-specific meaning beyond what the schema provides. The 'categories' parameter has an enum with 'agentic-browsing' which is unusual, but the description doesn't explain it. Baseline 3 is appropriate since the schema does most of the work.
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 states a specific verb ('Run') and resource ('Lighthouse audit'), and the title clarifies it's a website audit. It's clear what the tool does, though it doesn't explicitly differentiate from siblings like get_performance_score or get_accessibility_score, which are more specific. The description is broad but not misleading.
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?
The description implies usage for running a comprehensive audit, but it doesn't explicitly state when to use this tool versus the more specific sibling tools (e.g., get_performance_score, get_accessibility_score). It doesn't mention alternatives or exclusions. The context signals show many sibling tools that are more targeted, so the description should guide the agent on when to choose this comprehensive audit over those.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
12 tool updates
v1.0.27- Changed
analyze_resources1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "device": { + "type": "string" + }, + "filters": { + "additionalProperties": false, + "properties": { + "minSizeKB": { + "type": "number" + }, + "resourceTypes": { + "items": { + "type": "string" + }, + "type": "array" + } + }, + "required": [ + "resourceTypes", + "minSizeKB" + ], + "type": "object" + }, + "optimization": { + "additionalProperties": false, + "properties": { + "priorities": { + "items": { + "type": "string" + }, + "type": "array" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + } + }, + "required": [ + "recommendations", + "priorities" + ], + "type": "object" + }, + "resources": { + "items": { + "additionalProperties": false, + "properties": { + "filename": { + "type": "string" + }, + "mimeType": { + "type": "string" + }, + "sizeKB": { + "type": "number" + }, + "type": { + "type": "string" + }, + "url": { + "type": "string" + } + }, + "required": [ + "filename", + "type", + "sizeKB", + "mimeType", + "url" + ], + "type": "object" + }, + "type": "array" + }, + "summary": { + "additionalProperties": false, + "properties": { + "resourceCounts": { + "additionalProperties": { + "additionalProperties": false, + "properties": { + "count": { + "type": "number" + }, + "sizeKB": { + "type": "number" + } + }, + "required": [ + "count", + "sizeKB" + ], + "type": "object" + }, + "propertyNames": { + "type": "string" + }, + "type": "object" + }, + "totalResources": { + "type": "number" + }, + "totalSizeKB": { + "type": "number" + } + }, + "required": [ + "totalResources", + "totalSizeKB", + "resourceCounts" + ], + "type": "object" + }, + "timestamp": { + "type": "string" + }, + "url": { + "type": "string" + } + }, + "required": [ + "url", + "device", + "timestamp", + "filters", + "summary", + "resources", + "optimization" + ], + "type": "object" +}
- Changed
check_performance_budget1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "data": { + "additionalProperties": false, + "properties": { + "fetchTime": { + "type": "string" + }, + "overallPassed": { + "type": "boolean" + }, + "results": { + "additionalProperties": { + "additionalProperties": false, + "properties": { + "actual": { + "type": "number" + }, + "budget": { + "type": "number" + }, + "difference": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ] + }, + "passed": { + "type": "boolean" + }, + "unit": { + "type": "string" + } + }, + "required": [ + "actual", + "budget", + "unit", + "passed", + "difference" + ], + "type": "object" + }, + "propertyNames": { + "type": "string" + }, + "type": "object" + } + }, + "required": [ + "overallPassed", + "results", + "fetchTime" + ], + "type": "object" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + }, + "summary": { + "type": "string" + } + }, + "required": [ + "summary", + "data" + ], + "type": "object" +}
- Removed
check_pwa_readiness - Changed
compare_mobile_desktop2 fields changed- changed
Input schema / properties / categories / items / enumPrevious value: -[ - "performance", - "accessibility", - "best-practices", - "seo", - "pwa" -]New value: +[ + "performance", + "accessibility", + "best-practices", + "seo", + "agentic-browsing" +] - changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "data": { + "additionalProperties": false, + "properties": { + "differences": { + "additionalProperties": { + "additionalProperties": false, + "properties": { + "better": { + "enum": [ + "mobile", + "desktop" + ], + "type": "string" + }, + "desktop": { + "type": "number" + }, + "difference": { + "type": "number" + }, + "mobile": { + "type": "number" + } + }, + "required": [ + "mobile", + "desktop", + "difference", + "better" + ], + "type": "object" + }, + "propertyNames": { + "type": "string" + }, + "type": "object" + }, + "includeDetails": { + "type": "boolean" + } + }, + "required": [ + "differences" + ], + "type": "object" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + }, + "summary": { + "type": "string" + } + }, + "required": [ + "summary", + "data" + ], + "type": "object" +}
- Changed
find_unused_javascript1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "device": { + "type": "string" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + }, + "summary": { + "additionalProperties": false, + "properties": { + "hasUnusedCode": { + "type": "boolean" + }, + "totalFilesAnalyzed": { + "type": "number" + }, + "totalUnusedKB": { + "type": "number" + } + }, + "required": [ + "totalUnusedKB", + "totalFilesAnalyzed", + "hasUnusedCode" + ], + "type": "object" + }, + "thresholdBytes": { + "type": "number" + }, + "timestamp": { + "type": "string" + }, + "unusedFiles": { + "items": { + "additionalProperties": false, + "properties": { + "filename": { + "type": "string" + }, + "totalKB": { + "type": "number" + }, + "unusedKB": { + "type": "number" + }, + "unusedPercent": { + "type": "number" + }, + "url": { + "type": "string" + } + }, + "required": [ + "filename", + "totalKB", + "unusedKB", + "unusedPercent", + "url" + ], + "type": "object" + }, + "type": "array" + }, + "url": { + "type": "string" + } + }, + "required": [ + "url", + "device", + "timestamp", + "summary", + "unusedFiles", + "recommendations" + ], + "type": "object" +}
- Changed
get_accessibility_score1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "data": { + "additionalProperties": false, + "properties": { + "accessibilityScore": { + "type": "number" + }, + "audits": { + "items": { + "additionalProperties": false, + "properties": { + "description": { + "type": "string" + }, + "displayValue": { + "type": "string" + }, + "score": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ] + }, + "title": { + "type": "string" + } + }, + "required": [ + "title", + "score", + "displayValue" + ], + "type": "object" + }, + "type": "array" + }, + "fetchTime": { + "type": "string" + }, + "includeDetails": { + "type": "boolean" + } + }, + "required": [ + "accessibilityScore", + "fetchTime", + "includeDetails" + ], + "type": "object" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + }, + "summary": { + "type": "string" + } + }, + "required": [ + "summary", + "data" + ], + "type": "object" +}
- Changed
get_core_web_vitals3 fields changed- removed
Input schema / properties / threshold / properties / fidRemoved value: -{ - "description": "First Input Delay threshold in milliseconds", - "minimum": 0, - "type": "number" -} - added
Input schema / properties / threshold / properties / inpAdded value: +{ + "description": "Interaction to Next Paint threshold in milliseconds (compared against TBT in lab runs)", + "minimum": 0, + "type": "number" +} - changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "data": { + "additionalProperties": false, + "properties": { + "coreWebVitals": { + "additionalProperties": { + "additionalProperties": false, + "properties": { + "score": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ] + }, + "title": { + "type": "string" + }, + "value": { + "type": "string" + } + }, + "required": [ + "title", + "value" + ], + "type": "object" + }, + "propertyNames": { + "type": "string" + }, + "type": "object" + }, + "fetchTime": { + "type": "string" + }, + "includeDetails": { + "type": "boolean" + }, + "thresholdResults": { + "additionalProperties": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ] + }, + "propertyNames": { + "type": "string" + }, + "type": "object" + } + }, + "required": [ + "coreWebVitals", + "thresholdResults", + "fetchTime" + ], + "type": "object" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + }, + "summary": { + "type": "string" + } + }, + "required": [ + "summary", + "data" + ], + "type": "object" +}
- Changed
get_lcp_opportunities1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "data": { + "additionalProperties": false, + "properties": { + "fetchTime": { + "type": "string" + }, + "includeDetails": { + "type": "boolean" + }, + "lcpValue": { + "type": "number" + }, + "needsImprovement": { + "type": "boolean" + }, + "opportunities": { + "items": { + "additionalProperties": false, + "properties": { + "description": { + "type": "string" + }, + "displayValue": { + "type": "string" + }, + "id": { + "type": "string" + }, + "numericValue": { + "type": "number" + }, + "score": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ] + }, + "title": { + "type": "string" + } + }, + "required": [ + "id" + ], + "type": "object" + }, + "type": "array" + }, + "threshold": { + "type": "number" + } + }, + "required": [ + "lcpValue", + "threshold", + "needsImprovement", + "opportunities", + "fetchTime" + ], + "type": "object" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + }, + "summary": { + "type": "string" + } + }, + "required": [ + "summary", + "data" + ], + "type": "object" +}
- Changed
get_performance_score1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "data": { + "additionalProperties": false, + "properties": { + "fetchTime": { + "type": "string" + }, + "metrics": { + "additionalProperties": { + "additionalProperties": false, + "properties": { + "score": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ] + }, + "title": { + "type": "string" + }, + "value": { + "type": "string" + } + }, + "required": [ + "title", + "value" + ], + "type": "object" + }, + "propertyNames": { + "type": "string" + }, + "type": "object" + }, + "performanceScore": { + "type": "number" + } + }, + "required": [ + "performanceScore", + "metrics", + "fetchTime" + ], + "type": "object" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + }, + "summary": { + "type": "string" + } + }, + "required": [ + "summary", + "data" + ], + "type": "object" +}
- Changed
get_security_audit2 fields changed- changed
Input schema / properties / checks / items / enumPrevious value: -[ - "https", - "mixed-content", - "csp", - "hsts", - "vulnerabilities" -]New value: +[ + "https", + "csp", + "hsts", + "origin-isolation", + "clickjacking", + "trusted-types", + "third-party-cookies", + "deprecations" +] - changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "data": { + "additionalProperties": false, + "properties": { + "auditCount": { + "type": "number" + }, + "audits": { + "items": { + "additionalProperties": false, + "properties": { + "description": { + "type": "string" + }, + "displayValue": { + "type": "string" + }, + "id": { + "type": "string" + }, + "score": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ] + }, + "status": { + "enum": [ + "pass", + "fail", + "warning" + ], + "type": "string" + }, + "title": { + "type": "string" + } + }, + "required": [ + "id", + "title", + "description", + "score", + "displayValue", + "status" + ], + "type": "object" + }, + "type": "array" + }, + "failedAudits": { + "type": "number" + }, + "fetchTime": { + "type": "string" + }, + "overallScore": { + "type": "number" + }, + "passedAudits": { + "type": "number" + } + }, + "required": [ + "overallScore", + "audits", + "auditCount", + "passedAudits", + "failedAudits", + "fetchTime" + ], + "type": "object" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + }, + "summary": { + "type": "string" + } + }, + "required": [ + "summary", + "data" + ], + "type": "object" +}
- Changed
get_seo_analysis1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "data": { + "additionalProperties": false, + "properties": { + "audits": { + "items": { + "additionalProperties": false, + "properties": { + "description": { + "type": "string" + }, + "displayValue": { + "type": "string" + }, + "score": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ] + }, + "title": { + "type": "string" + } + }, + "required": [ + "title", + "score", + "displayValue" + ], + "type": "object" + }, + "type": "array" + }, + "fetchTime": { + "type": "string" + }, + "includeDetails": { + "type": "boolean" + }, + "seoScore": { + "type": "number" + } + }, + "required": [ + "seoScore", + "fetchTime", + "includeDetails" + ], + "type": "object" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + }, + "summary": { + "type": "string" + } + }, + "required": [ + "summary", + "data" + ], + "type": "object" +}
- Changed
run_audit2 fields changed- changed
Input schema / properties / categories / items / enumPrevious value: -[ - "performance", - "accessibility", - "best-practices", - "seo", - "pwa" -]New value: +[ + "performance", + "accessibility", + "best-practices", + "seo", + "agentic-browsing" +] - changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "data": { + "additionalProperties": false, + "properties": { + "categories": { + "additionalProperties": { + "additionalProperties": false, + "properties": { + "score": { + "type": "number" + }, + "title": { + "type": "string" + } + }, + "required": [ + "title", + "score" + ], + "type": "object" + }, + "propertyNames": { + "type": "string" + }, + "type": "object" + }, + "fetchTime": { + "type": "string" + }, + "metrics": { + "additionalProperties": { + "additionalProperties": false, + "properties": { + "score": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ] + }, + "title": { + "type": "string" + }, + "value": { + "type": "string" + } + }, + "required": [ + "title", + "value" + ], + "type": "object" + }, + "propertyNames": { + "type": "string" + }, + "type": "object" + }, + "version": { + "type": "string" + } + }, + "required": [ + "categories", + "metrics", + "version", + "fetchTime" + ], + "type": "object" + }, + "recommendations": { + "items": { + "type": "string" + }, + "type": "array" + }, + "summary": { + "type": "string" + } + }, + "required": [ + "summary", + "data" + ], + "type": "object" +}
12 tool updates
v1.0.26- Added
analyze_resources - Added
check_performance_budget - Added
check_pwa_readiness - Added
compare_mobile_desktop - Added
find_unused_javascript - Added
get_accessibility_score - Added
get_core_web_vitals - Added
get_lcp_opportunities - Added
get_performance_score - Added
get_security_audit - Added
get_seo_analysis - Added
run_audit
TDQS
Scored across 11 tools
There is significant overlap between run_audit and the specific getter tools (accessibility, SEO, performance), as run_audit likely encompasses all of those. Additionally, get_lcp_opportunities, find_unused_javascript, and analyze_resources all target performance optimization with unclear boundaries.
Most tools follow a clear verb_noun pattern (e.g., get_*, run_audit, compare_mobile_desktop, check_performance_budget). Minor deviations include run_audit vs. get_security_audit (both use 'audit' but different verbs) and find_unused_javascript/analyze_resources not using 'get_' prefix, but the overall convention is consistent.
With 11 tools, the set is well-scoped for a website auditing server. Each tool covers a distinct aspect of Lighthouse auditing (performance, SEO, accessibility, security, resources), and the count is within the ideal 3-15 range without feeling bloated.
The tool surface covers major Lighthouse categories (performance, accessibility, SEO, security, Core Web Vitals, resources) and includes useful extras like budget checks and mobile/desktop comparison. However, it lacks explicit best practices and PWA audits, which are standard Lighthouse categories, creating minor gaps.
Maintenance
Related MCP Connectors
MCP server for building and testing AI agents with multi-model experimentation and insights.
- RampifyOAuthdev.rampify
SEO MCP server: crawl your site, find AI-visibility gaps, and ship the fix from your coding agent.
Website QA for your coding agent: audit SEO, performance, security, accessibility over MCP.
Your agent needs to crawl a site and say what is wrong with it — broken tags, duplicate content, pages nothing can index, resources that never load. **What you can ask for** • "Crawl this site and list every page with a duplicate title or missing description." • "Which pages are non-indexable, and why?" • "Run Lighthouse on these URLs and give me the failing audits." • "Show the internal link graph and the orphan pages." • "Give me this page's raw HTML and its microdata." **How to use it** Point any MCP client at https://mcp.aisa.one/seo-onpage/mcp and sign in with OAuth — there is no key to create or paste. 20 tools: submit a crawl and read its summary, pages, resources, links and waterfall; duplicate content and duplicate tags; keyword density; non-indexable and uncrawlable resources; parsed content, raw HTML, microdata, screenshots and Lighthouse. **Why this rather than the source** A crawler you drive from the agent, with the audit results as structured data rather than a PDF. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Find the broken pages here, then ask the same agent what those pages used to rank for — without adding a second server. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** https://mcp.aisa.one/seo/mcp for all of it at once — rankings, keywords, backlinks, site health and AI-answer visibility across DataForSEO, Semrush and Ahrefs.
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