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Webflow Mcp:Site Audit

Organization
webflow
webflow-mcp:site-audit

Comprehensive audit of a Webflow site including pages, CMS collections, health scoring, and actionable insights. Use for site analysis, migration planning, or understanding site structure.

Overview

Publisherwebflow
Repositorywebflow-skills
Skill namewebflow-mcp:site-audit
Stars
122
Forks
18
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by webflow on GitHub. Read the source before you install it.

Installation

Install the Webflow Mcp:Site Audit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/webflow/webflow-skills.git /tmp/webflow-skills
mkdir -p .claude/skills
cp -r /tmp/webflow-skills/plugins/webflow-skills/skills/site-audit .claude/skills/webflow-webflow-mcp-site-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Webflow Mcp:Site Audit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Webflow Mcp:Site Audit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Webflow Mcp:Site Audit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Site Audit

Comprehensive audit of a Webflow site's structure, content health, and quality with detailed analysis and multiple export formats.

Important Note

ALWAYS use Webflow MCP tools for all operations:

  • Use Webflow MCP's data_sites_tool with action list_sites for listing available sites
  • Use Webflow MCP's data_sites_tool with action get_site for detailed site information
  • Use Webflow MCP's data_pages_tool with action list_pages for retrieving all pages
  • Use Webflow MCP's data_cms_tool with action get_collection_list for listing CMS collections
  • Use Webflow MCP's data_cms_tool with action get_collection_details for detailed collection schemas
  • Use Webflow MCP's data_cms_tool with action list_collection_items for counting items
  • Use Webflow MCP's webflow_guide_tool to get best practices before starting
  • DO NOT use any other tools or methods for Webflow operations
  • All tool calls must include the required context parameter (15-25 words, third-person perspective)

Instructions

Phase 1: Site Selection & Discovery

  1. Get site: Identify the target site. If user does not provide site ID, ask for it.
  2. Fetch site details: Use Webflow MCP's data_sites_tool with action get_site to retrieve:
    • Site name and ID
    • Last published date
    • Last updated date
    • Timezone
    • Locales (primary and secondary)
    • Custom domains
  3. Ask user preferences: Ask what level of detail they want:
    • Quick summary (counts only)
    • Standard inventory (pages + collections + counts)
    • Detailed inventory (includes all field schemas, item samples, SEO data)
    • Full export (everything + export to file format)

Phase 2: Pages Inventory

  1. List all pages: Use Webflow MCP's data_pages_tool with action list_pages to fetch all pages
  2. Categorize pages:
    • Static pages (no collectionId)
    • CMS template pages (has collectionId)
    • Archived pages
    • Draft pages
  3. Analyze page structure:
    • Count pages by type
    • Identify pages missing SEO metadata
    • Detect orphaned pages (no navigation links)
    • Check for duplicate slugs

Phase 3: CMS Collections Inventory

  1. List all collections: Use Webflow MCP's data_cms_tool with action get_collection_list
  2. For each collection:
    • Get detailed schema using Webflow MCP's data_cms_tool with action get_collection_details
    • Count items using Webflow MCP's data_cms_tool with action list_collection_items
    • Analyze field types and requirements
    • Identify required vs optional fields
    • Detect reference fields and relationships
  3. Collection analysis:
    • Empty collections (0 items)
    • Unused collections (no template page)
    • Large collections (100+ items)
    • Collections with missing required fields

Phase 4: Analysis & Insights

  1. Generate insights:
    • Total content count (pages + items)
    • Content health score
    • SEO readiness
    • Recommended improvements
  2. Identify issues:
    • Missing SEO metadata
    • Empty collections
    • Orphaned pages
    • Draft content ratio
  3. Show relationships:
    • Which pages use which collections
    • Reference field connections
    • Content dependencies

Phase 5: Export & Formatting

  1. Ask export format (if user wants full export):
    • Markdown (readable, great for documentation)
    • JSON (machine-readable, for migrations)
    • CSV (spreadsheet-friendly, for analysis)
    • Text summary (console output only)
  2. Generate report in requested format
  3. Provide actionable insights: Suggest next steps based on findings

Examples

User prompt:

Give me a complete inventory of my site.

Step 1: Initial Report (Standard Inventory)

📊 Site Audit: MCP Demo#1

**Site Details:**
- Site ID: 6924868ede9d3fbbc3195eb0
- Last published: January 9, 2026
- Last updated: January 9, 2026
- Timezone: Asia/Calcutta
- Primary locale: English (en)

---

**Pages (2 total):**

Static Pages (1):
├── Home (/)

CMS Template Pages (1):
└── Blog Posts Template (/post)
    - Collection: Blog Posts

---

**CMS Collections (1):**

Blog Posts (9 items)
├── Slug: post
├── Fields (8):
│   ├── Name (PlainText, required)
│   ├── Slug (PlainText, required)
│   ├── Post Body (RichText)
│   ├── Post Summary (PlainText)
│   ├── Main Image (Image)
│   ├── Thumbnail image (Image)
│   ├── Featured? (Switch)
│   └── Color (Color)

---

**Summary:**
- ✅ 2 pages (1 static, 1 CMS template)
- ✅ 1 CMS collection with 9 published items
- ✅ Site fully published and up-to-date

Would you like a detailed analysis or export in a specific format?

Step 2: Detailed Analysis (when user requests)

🔍 Detailed Analysis: MCP Demo#1

**Content Health Score: 85/100**

✅ Strengths:
- All collections have items (no empty collections)
- All pages are published (no drafts)
- Site recently published (Jan 9, 2026)
- Consistent field structure in Blog Posts

⚠️ Areas for Improvement:
- No SEO metadata on template page (missing meta description)
- Limited page count (consider adding About, Contact pages)
- No reference fields (could link categories/authors to posts)

💡 Recommendations:
1. Add meta descriptions to all pages for better SEO
2. Consider creating a Categories collection for post organization
3. Add an Authors collection for multi-author blog support
4. Create navigation pages (About, Contact, Privacy Policy)

**Collection Breakdown:**

Blog Posts:
- 9 published items (0 drafts, 0 archived)
- 5 featured posts (56%)
- All required fields populated ✓
- Field usage:
  - Name: 100% (9/9)
  - Slug: 100% (9/9)
  - Post Body: 100% (9/9)
  - Post Summary: 100% (9/9)
  - Main Image: 100% (9/9)
  - Thumbnail: 100% (9/9)
  - Featured: 100% (9/9)
  - Color: 100% (9/9)

**Sample Items:**
1. "Why Webflow is the Best Choice for 2026" (featured)
2. "Top Webflow Features to Look Forward to in 2026"
3. "Webflow vs. Competitors: Who Will Win in 2026?" (featured)

---

Export this inventory? (markdown/json/csv/no)

Step 3: Export Options

📥 Export Format Options:

1. **Markdown** - Human-readable documentation
   - Great for README files, wikis, documentation
   - Preserves structure and formatting

2. **JSON** - Machine-readable structured data
   - Perfect for migrations, integrations
   - Includes all raw API data

3. **CSV** - Spreadsheet-friendly
   - Easy to analyze in Excel/Google Sheets
   - Separate files for pages and collections

Which format would you like? (1/2/3)

Guidelines

Phase 1: Critical Requirements

Site Information:

  • Always fetch complete site details using data_sites_tool with action get_site
  • Include last published and last updated dates
  • Show timezone and locale information
  • Display custom domains if configured

User Options: Offer multiple detail levels:

  • Quick: Just counts
  • Standard: Pages + collections + basic info
  • Detailed: Full schema + analysis + insights
  • Export: Everything + file output

Phase 2: Pages Analysis

Page Categorization:

  • Separate static pages from CMS template pages
  • Flag archived and draft pages separately
  • Show page slugs/URLs for reference
  • Identify pages with missing SEO metadata

Page Health Checks:

  • Missing meta descriptions
  • Missing OG tags
  • Duplicate slugs (error condition)
  • Orphaned pages (not linked in nav)

Phase 3: Collections Analysis

Collection Details: For each collection, show:

  • Display name and singular name
  • Slug (URL structure)
  • Total field count
  • Required vs optional fields breakdown
  • Item count (published/draft/archived)
  • Last updated date

Field Analysis: Categorize by type:

  • Text fields (PlainText, RichText)
  • Media fields (Image, Video, File)
  • Relationship fields (Reference, MultiReference)
  • Data fields (DateTime, Number, Color)
  • Boolean fields (Switch)
  • Selection fields (Option)

Field Validation:

  • Show max length constraints
  • Show validation patterns
  • Flag required fields
  • Identify reference field targets

Phase 4: Analysis & Insights

Content Health Score (0-100): Calculate based on:

  • SEO metadata completeness (25 points)
  • Content-to-page ratio (20 points)
  • Field utilization (20 points)
  • Recent updates (15 points)
  • Structure quality (20 points)

Issue Detection:

  • 🔴 Critical: Missing required fields, duplicate slugs
  • ⚠️ Warning: Empty collections, missing SEO, drafts
  • 💡 Suggestion: Add pages, create relationships, organize

Recommendations: Suggest improvements based on:

  • Missing page types (About, Contact, etc.)
  • Underutilized collections
  • Missing relationships between collections
  • SEO optimization opportunities

Phase 5: Export Formats

Markdown Export:

markdown
# Site Audit: [Site Name]

## Site Information
- ID: [site-id]
- Last Published: [date]

## Pages
### Static Pages
- Home (/)
- About (/about)

### CMS Templates
- Blog Post (/post/[slug])

## Collections
### Blog Posts (47 items)
**Fields:**
- Title (PlainText, required)
- Slug (PlainText, required)
- Content (RichText)
...

JSON Export:

json
{
  "site": {
    "id": "...",
    "name": "...",
    "lastPublished": "..."
  },
  "pages": [...],
  "collections": [...]
}

CSV Export: Generate separate files:

  • pages.csv: All pages with metadata
  • collections.csv: Collection metadata
  • fields.csv: All fields across collections
  • items.csv: Item counts per collection

Performance Optimization

Batch Processing:

  • For sites with 20+ collections, show progress
  • For collections with 100+ items, paginate counts
  • Provide estimated time for large sites

Error Handling:

  • If data_pages_tool with action list_pages fails, continue with collections
  • If data_cms_tool with action get_collection_details fails, show basic collection info
  • Report partial successes separately
  • Offer to retry failed operations

Data Efficiency:

  • Use pagination for large result sets
  • Only fetch detailed schemas when needed
  • Limit item samples to 3-5 per collection
  • Cache site info for repeat operations

Best Practices

Read-Only Operation:

  • No confirmation needed (read-only)
  • Safe to run multiple times
  • No side effects or modifications

Clear Organization:

  • Group by content type (pages/collections)
  • Use visual hierarchy (├── └──)
  • Show counts prominently
  • Highlight issues with icons (✅ ⚠️ 🔴 💡)

Actionable Output:

  • Always end with recommendations
  • Offer export options for detailed inventories
  • Suggest next steps based on findings
  • Provide comparison against best practices

Version Tracking: If user runs inventory multiple times:

  • Compare with previous run
  • Show changes (new pages, deleted collections)
  • Track content growth over time
  • Alert on significant changes

Frequently asked questions

What does the Webflow Mcp:Site Audit AI skill do?

Comprehensive audit of a Webflow site including pages, CMS collections, health scoring, and actionable insights. Use for site analysis, migration planning, or understanding site structure.

Why use Webflow Mcp:Site Audit on TypingMind?

Because you install it once and use it with any model. Webflow Mcp:Site Audit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Webflow Mcp:Site Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/webflow/webflow-skills/tree/main/plugins/webflow-skills/skills/site-audit. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Webflow Mcp:Site Audit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Webflow Mcp:Site Audit?

As many as you like. As long as a model supports skills, you can use Webflow Mcp:Site Audit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Webflow Mcp:Site Audit AI skill free?

Yes. It is published on GitHub by webflow under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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