Atlas / Skills / nowork-studio / Schema Markup Generator

Schema Markup GeneratorSAFE

skills/nowork-studio/schema-markup-generator

Open-source SEO, GEO, and marketing skills for AI agents.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
3,908
01

Overview

Open-source SEO, GEO, and marketing skills for AI agents.

Read from source at commit f08bca773eb5OBSERVED · 2026-10-08
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: schema-markup-generator
argument-hint: "<URL or page type, e.g. 'FAQ page' or 'product page'>"
description: >
  Generate JSON-LD structured data markup for rich results in Google Search.
  Supports FAQ, HowTo, Article, Product, LocalBusiness, and multi-type schemas.
  Validates against Google requirements and provides implementation guidance.
  Use when asked to "add schema markup", "generate structured data", "JSON-LD",
  "rich snippets", "FAQ schema", "product markup", "add structured data to my
  page", "how to get rich snippets", or any structured data task.
---

# Schema Markup Generator

This skill creates Schema.org structured data markup in JSON-LD format to help search engines understand your content and enable rich results in SERPs.

## When This Must Trigger

Use this when the conversation involves any of these situations — even if the user does not use SEO terminology:

Use this whenever the task needs a shippable asset or transformation that should feed directly into quality review, deployment, or monitoring.

- Adding FAQ schema for expanded SERP presence
- Creating How-To schema for step-by-step content
- Adding Product schema for e-commerce pages
- Implementing Article schema for blog posts
- Adding Local Business schema for location pages
- Creating Review/Rating schema
- Implementing Organization schema for brand presence
- Any page where rich results would improve visibility

## What This Skill Does

1. **Schema Type Selection**: Recommends appropriate schema types
2. **JSON-LD Generation**: Creates valid structured data markup
3. **Property Mapping**: Maps your content to schema properties
4. **Validation Guidance**: Ensures schema meets requirements
5. **Nested Schema**: Handles complex, multi-type schemas
6. **Rich Result Eligibility**: Identifies which rich results you can target

## Quick Start

Start with one of these prompts.

### Generate Schema for Content

```
Generate schema markup for this [content type]: [content/URL]
```

```
Create FAQ schema for these questions and answers: [Q&A list]
```

### Specific Schema Types

```
Create Product schema for [product name] with [details]
```

```
Generate LocalBusiness schema for [business name and details]
```

### Audit Existing Schema

```
Review and improve this schema markup: [existing schema]
```

## Data Sources

**With ~~web crawler connected:**
Automatically crawl and extract page content (visible text, headings, lists, tables), existing schema markup, page metadata, and structured content elements that map to schema properties.

**With manual data only:**
Ask the user to provide:
1. Page URL or full HTML content
2. Page type (article, product, FAQ, how-to, local business, etc.)
3. Specific data needed for schema (prices, dates, author info, Q&A pairs, etc.)
4. Current schema markup (if optimizing existing)

Proceed with the full workflow using provided data. Note in the output which data is from automated extraction vs. user-provided data.

## Instructions

When a user requests schema markup:

1. **Identify Content Type and Rich Result Opportunity**

   Reference the CORE-EEAT Benchmark item **O05 (Schema Markup)** for content-type to schema mapping:

   ```markdown
   ### CORE-EEAT Schema Mapping (O05)

   | Content Type | Required Schema | Conditional Schema |
   |-------------|----------------|--------------------|
   | Blog (guides) | Article, Breadcrumb | FAQ, HowTo |
   | Blog (tools) | Article, Breadcrumb | FAQ, Review |
   | Blog (insights) | Article, Breadcrumb | FAQ |
   | Alternative | Comparison*, Breadcrumb, FAQ | AggregateRating |
   | Best-of | ItemList, Breadcrumb, FAQ | AggregateRating per tool |
   | Use-case | WebPage, Breadcrumb, FAQ | — |
   | FAQ | FAQPage, Breadcrumb | — |
   | Landing | SoftwareApplication, Breadcrumb, FAQ | WebPage |
   | Testimonial | Review, Breadcrumb | FAQ, Person |

   *Use the mapping above to ensure schema type matches content type (CORE-EEAT O05: Pass criteria).*
   ```

   ```markdown
   ### Schema Analysis

   **Content Type**: [blog/product/FAQ/how-to/local business/etc.]
   **Page URL**: [URL]

   **Eligible Rich Results**:
   
   | Rich Result Type | Eligibility | Impact |
   |------------------|-------------|--------|
   | FAQ | ✅/❌ | High - Expands SERP presence |
   | How-To | ✅/❌ | Medium - Shows steps in SERP |
   | Product | ✅/❌ | High - Shows price, availability |
   | Review | ✅/❌ | High - Shows star ratings |
   | Article | ✅/❌ | Medium - Shows publish date, author |
   | Breadcrumb | ✅/❌ | Medium - Shows navigation path |
   | Video | ✅/❌ | High - Shows video thumbnail |
   
   **Recommended Schema Types**:
   1. [Primary schema type] - [reason]
   2. [Secondary schema type] - [reason]
   ```

2. **Generate Schema Markup**

   Based on the identified content type, generate the appropriate JSON-LD schema. Supported types: FAQPage, HowTo, Article/BlogPosting/NewsArticle, Product, LocalBusiness, Organization, BreadcrumbList, Event, Recipe, and combined multi-type schemas.

   > **Reference**: See [references/schema-templates.md](references/schema-templates.md) for complete, copy-ready JSON-LD templates for all schema types with required and optional properties.

   For each schema generated, include:
   - All required properties for the chosen type
   - Rich result preview showing expected SERP appearance
   - Notes on which properties are required vs. optional

   When combining multiple schema types on one page, wrap them in a JSON array inside a single `<script type="application/ld+json">` tag.

3. **Provide Implementation and Validation**

    ```markdown
    ## Implementation Guide

    ### Adding Schema to Your Page

    **Option 1: In HTML <head>**
    ```html
    <head>
      <script type="application/ld+json">
        [Your JSON-LD schema here]
      </script>
    </head>
    ```

    **Option 2: Before closing </body>**
    ```html
      <script type="application/ld+json">
        [Your JSON-LD schema here]
      </script>
  
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-08 · audit v0.4.1 · source sha f08bca773eb5full audit observations/trust-audit/skill/nowork-studio__schema-markup-generator.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-08f08bca773eb5SAFEB89first audit
05

Questions

What does the Schema Markup Generator skill do?

Open-source SEO, GEO, and marketing skills for AI agents.

Is Schema Markup Generator safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Schema Markup Generator access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (f08bca773eb5), read on 2026-10-08. The repository is watched, and a new audit runs when it changes — this is the first audit.

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