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Varnan-Tech/opendirectory

Use when the user asks to generate JSON-LD or structured data markup for a webpage. Detects applicable schema types (FAQPage, Article, Organization, Product, BreadcrumbList, HowTo, etc.) from page content and outputs valid JSON-LD script blocks ready to paste, flagging missing fields rather than inventing data.

¿Qué es opendirectory?

opendirectory is a Claude Code agent skill that use when the user asks to generate JSON-LD or structured data markup for a webpage. Detects applicable schema types (FAQPage, Article, Organization, Product, BreadcrumbList, HowTo, etc.) from page content and outputs valid JSON-LD script blocks ready to paste, flagging missing fields rather than inventing data.

Compatible con✓Claude Code~Codex CLI~Cursor✓Gemini CLI
npx skills add https://github.com/Varnan-Tech/opendirectory/tree/main/skills/schema-markup-generator

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Documentación

schema-markup-generator

You are an SEO engineer specialising in structured data. Your job is to read a webpage and generate valid JSON-LD schema markup that matches what is actually on the page.

DO NOT INVENT DATA. Every field in the JSON-LD must come from content that exists on the page. If a required field is not present on the page, flag it as missing rather than filling it with placeholder or guessed data.

Before starting, confirm you have a target. Accepted inputs:

  • A live URL to crawl with Chrome
  • A local HTML file path
  • Pasted HTML content

If no input was provided, ask: "What page do you want to generate schema markup for? Give me a URL, a file path, or paste the HTML."


Workflow

Step 1: Setup Check

Check the environment before doing anything else.

For live URLs: Confirm Chrome is running with remote debugging enabled. If the Chrome DevTools MCP is available, proceed. If not, try fetching the page with curl as a fallback.

For local files or pasted HTML: No Chrome needed. Read the content directly.

Check for GITHUB_TOKEN if the user wants a PR at the end. Note its presence but do not block. Output-only mode works without it.

QA: What is the input source? Is it accessible? State what crawl method you will use.


Step 2: Crawl the Page and Extract Content

Connect to the page using the available method.

Using Chrome DevTools MCP:

  • Navigate to the URL
  • Wait for the page to fully load (including JavaScript-rendered content)
  • Extract the full page text content and visible HTML structure
  • Capture: page title, meta description, headings (h1-h6), all body text, image URLs and alt text, links, any visible prices, dates, author names, company name, address, phone numbers, FAQ sections, numbered steps, reviews and ratings

Using curl fallback:

  • Fetch with a browser User-Agent
  • Parse the HTML for the same content listed above

Using local file or pasted HTML:

  • Read the content directly
  • Parse the same fields

QA: List the key content you found. What is the page about? What structured content exists (FAQ pairs, product pricing, article byline, address, steps)?


Step 3: Detect Schema Types Needed

Analyse the extracted content. A page often needs more than one schema type.

Detection rules:

Page typeRequired content signalsSchema type(s) to generate
FAQ page or FAQ section3 or more question/answer pairsFAQPage
Blog post or articleHeadline, author, publish date, article bodyArticle or BlogPosting
Company or about pageCompany name, description, logo or social linksOrganization
Product pageProduct name, price, availabilityProduct
HomepageSite name, search functionalityWebSite
How-to guide or tutorialNumbered steps with descriptionsHowTo
Page with breadcrumb navigationBreadcrumb trail visible on pageBreadcrumbList
Software tool or appApp name, OS, pricing, download linkSoftwareApplication
Local businessPhysical address, phone, hoursLocalBusiness

Apply multiple types if the page qualifies for more than one. A blog post page, for example, often needs Article and BreadcrumbList. An about page often needs Organization and WebSite (if it is the homepage).

State the schema types you will generate and why.

QA: Does the detected type match the page content? Is there enough data to populate the required fields for each type?


Step 4: Read the Spec and Templates

Read references/json-ld-spec.md for the required and recommended fields for each detected schema type.

Read references/output-template.md for the exact JSON structure to use for each type.

For each schema type you will generate, note:

  • Which required fields are present in the page content
  • Which required fields are missing (you will flag these, not invent them)
  • Which recommended fields are present and worth including

Step 5: Generate the JSON-LD

Generate one <script type="application/ld+json"> block per schema type.

Rules:

  • Every value must come from the page content extracted in Step 2
  • Use the templates in references/output-template.md as the structure
  • For missing required fields: add a comment inside the JSON as "MISSING_fieldName": "not found on page" so the user knows what to add
  • For missing recommended fields: omit them silently
  • Use ISO 8601 for all dates and durations
  • Use full absolute URLs for all image, page, and site references
  • Nest objects correctly (author as Person object, publisher as Organization object, etc.)
  • If multiple schema types apply, output each as a separate script block

Do not output generic placeholder values like "Company Name Here" or "Enter description". Either use the real value or flag it as MISSING.

QA: For each generated block, verify: Is every value traceable to the page content? Are all required fields either populated or explicitly flagged as MISSING?


Step 6: Validate the Output

Before presenting the output, run through this checklist for each JSON-LD block:

  • Valid JSON syntax (no trailing commas, balanced braces)
  • @context is "https://schema.org"
  • @type matches the intended schema type
  • All required fields for the type are either populated or flagged as MISSING
  • All URLs are absolute (start with https://)
  • All dates use ISO 8601 format
  • No invented data: every value traces to page content
  • No placeholder strings left in the output

Fix any syntax errors before presenting. State which required fields were found and which were flagged as MISSING.


Step 7: Output and Deploy

Present the output clearly.

For each schema block:

  1. State the schema type and which page it belongs to
  2. Show the full <script type="application/ld+json"> block in a code block
  3. State where in the HTML to place it (inside <head> before </head>)
  4. List any MISSING fields the user needs to fill in manually

Then ask: "Should I open a GitHub PR to inject this into your codebase, or do you want to add it manually?"

If the user confirms a PR:

  • Check for GITHUB_TOKEN and GITHUB_REPO in the environment
  • Detect the framework (Next.js, Astro, plain HTML, etc.) to know the right injection point
  • Insert the script block in the correct location for the framework
  • Open a PR via the GitHub CLI or API

Framework-specific injection points:

FrameworkWhere to inject
Next.js (App Router)Add <Script type="application/ld+json"> inside the page component, or use next/head for pages router
AstroAdd inside <head> in the page's layout or front matter
HTMLAdd inside <head> before </head>
JekyllAdd to _includes/head.html or the page's front matter with a custom head include
NuxtAdd via useHead() composable or <Head> component

QA: Was the output placed correctly? Are all MISSING fields clearly communicated to the user?


What Good Output Looks Like

  • Every JSON-LD value traces directly to visible page content
  • Required fields are populated or explicitly flagged as MISSING with a clear label
  • JSON syntax is valid (parseable by any JSON validator)
  • URLs are absolute and correct
  • Dates are in ISO 8601 format
  • The placement instruction matches the user's actual framework
  • The user knows exactly what to do next

What Bad Output Looks Like

  • Invented values not present on the page ("Best Company Inc.", generic descriptions)
  • Placeholder strings left in the output
  • Relative URLs instead of absolute URLs
  • Missing @context or @type
  • Invalid JSON (trailing comma, unbalanced brackets)
  • Wrong schema type for the page content
  • Silent omission of required fields without flagging them

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

Varnan-Tech/opendirectory

Use when the user asks to generate a blog cover image, thumbnail, or article header. Automatically uses modern typography, brand logos, and Google Search grounding to create beautiful 16:9 images with Gemini 3.1 Flash Image Preview.

Varnan-Tech/opendirectory

World-class brand strategist and naming expert. Uses an interrogation-led discovery phase to extract your brand's DNA, then applies scientific naming frameworks (Phonosemantics) and automated multi-TLD domain checking.

Varnan-Tech/opendirectory

Use when the user asks to generate or update a project's CLAUDE or AGENTS context file from a codebase scan. Writes a focused file under 100 lines containing only the non-obvious build commands, conventions, and gotchas Claude Code needs.

Varnan-Tech/opendirectory

Use when the user wants to verify cold emails, enrich a lead list, or autonomously guess email addresses from a CSV using ValidEmail.co or the open-source Reacher engine.

Varnan-Tech/opendirectory

Competitive intelligence orchestrator tracking companies across 8+ platforms (GitHub, Twitter, Reddit, HN, PH, YC Jobs) with heat scores and AI briefings.

Varnan-Tech/opendirectory

Give it your product URL or description. It finds your top 5 competitors, runs three-track PR research across all of them (editorial, podcasts, communities), identifies which channels appear most frequently, looks up the journalist or host for each, and returns a tiered outreach list with story angles and ready-to-send cold pitch drafts tailored to your product. Use when asked to find PR opportunities, discover where competitors got featured, build a media outreach list, find which journalists cover my space, or get pitch templates for press coverage.

Varnan-Tech/opendirectory

Generate high-converting, deep-dive growth case studies in MDX format. Use this skill when asked to write a case study or blog post about a company's growth, tech stack, or product-led strategy. It handles the full pipeline (researching the company via Tavily, generating a 16:9 cover image, quality checking the draft, uploading assets to cloud storage, and pushing directly to the target repository).

Varnan-Tech/opendirectory

Scans your project for outdated npm, pip, Cargo, Go, or Ruby packages. Runs a CVE security audit. Fetches changelogs, summarizes breaking changes with Gemini, and opens one PR per risk group (patch, minor, major). Includes Diagnosis Mode for install conflicts. Use when asked to update dependencies, check for outdated packages, open dependency PRs, scan for package updates, audit for CVEs, or flag breaking changes in upgrades. Trigger when a user says "check for outdated packages", "update my dependencies", "open PRs for dependency updates", "scan for CVEs", or "which packages need upgrading".

Varnan-Tech/opendirectory

Generates and updates README.md and API reference docs by reading your codebase's functions, routes, types, schemas, and architecture. Uses graphify to build a knowledge graph first, then writes accurate docs from it. Use when asked to write docs, generate a README, document an API, update stale docs, create an API reference from code, add an architecture section, or document a project in any language. Trigger when a user says their docs are missing, outdated, or wants to document their codebase without writing it manually.

Varnan-Tech/opendirectory

Evaluates expired domain candidates against a target niche, scores them by topical relevance, historical activity level, and history cleanliness, then outputs a ranked shortlist with explainable reasoning and risk flags.

Varnan-Tech/opendirectory

Brutally honest developer-experience audit for a GitHub repo. Scores 10 DX dimensions (time-to-first-success, README clarity, visual proof, install, quick-start, docs, examples, community, trust, marketing), writes a shareable roast in the requested tone (brutal/honest/kind), produces a prioritized action plan ranked by impact × effort, and sketches an ideal README. Trigger when user says "roast my repo", "audit my README", "dx audit", "developer experience review", "score my GitHub project", "before launch checklist", or "make my repo shareable".

Varnan-Tech/opendirectory

Drafts and designs a complete HTML email newsletter from a topic or content brief. Outputs paste-ready HTML for Loops, Mailchimp, Beehiiv, Resend, or any standard email platform. Includes subject line options and plain-text fallback. Trigger when a user says "write a newsletter", "draft an email newsletter", "create an HTML email", "design an email for my subscribers", or "write a newsletter about [topic]".

Varnan-Tech/opendirectory

Takes a GitHub PR URL or the current branch and writes a plain-English explanation of what it does and why, then posts it as a PR comment. Use when asked to explain a PR, summarize a pull request, write a plain-English description of a PR, add a summary comment to a PR, or understand what a PR changes. Trigger when a user says "explain this PR", "summarize this pull request", "what does this PR do", "add a comment explaining the PR", or shares a GitHub PR URL and asks what it does.

Varnan-Tech/opendirectory

Audit how often LLMs recommend your brand vs competitors and generate a GEO action plan.

Varnan-Tech/opendirectory

Takes a competitor's public GitHub repo URL, fetches their open issues via the GitHub REST API, filters noise locally, clusters issues into 6 demand categories, computes a demand score per issue and per cluster, and outputs a ranked demand gap report with a GTM messaging brief. Use when asked to scan a competitor's GitHub issues, find what their users are begging for, turn GitHub complaints into product positioning, identify competitor feature gaps, or generate messaging from real user demand. Trigger when a user says "scan competitor issues", "what are users asking for on X repo", "find demand gaps in Y", "turn GitHub issues into messaging", or "what should I build based on competitor complaints".

Varnan-Tech/opendirectory

Find recurring confusion in your repo's GitHub Discussions, rank it by urgency, and draft the actual docs fixes and content angles — with verbatim community quotes and source links as evidence.

Varnan-Tech/opendirectory

SEO keyword research workflow for blog generation using Google Trends data. Use when writing blog posts, planning content calendars, or optimizing articles for search engines. Finds breakout keywords, builds content structure, and generates SEO-optimized blog outlines targeting tech and developer audiences.

Varnan-Tech/opendirectory

Generates a professionally designed case study PDF for B2B SaaS sales and marketing. Supports 7 page layouts, 9 style presets, 1-4 page output. Trigger when user says "create a case study", "write a customer story", "make a case study PDF", "design a success story", "turn this customer win into a PDF".

Varnan-Tech/opendirectory

Generates data visualization charts (bar, line, area, pie, doughnut, scatter, radar, treemap) as PNG using Apache ECharts v6. 1080×1080px default, 5 style presets, highlight annotations. Trigger when user says "create a chart", "visualize data", "make a bar chart", "line graph", "pie chart", "data visualization", "chart this data", "plot", "graph", or "visualize these numbers".

Varnan-Tech/opendirectory

Fetches low-star App Store and Google Play reviews, clusters them into broken-promise patterns, and generates a ranked copy brief with positioning opportunities.

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