Selvakumar Duraipandian

The Problem: 
WordPress outputs HTML that’s difficult for AI systems to parse accurately. Important content gets lost in markup, scripts, and styling.
The Solution: 
AgentMark provides clean Markdown versions of your posts and pages through simple <code>.md</code> endpoints, plus an industry-standard <code>llms.txt</code> file that helps AI agents discover your best content.
<h4>Use Cases</h4>
<ul>
<li>AI Search Engines: Help tools like Perplexity, Claude, and ChatGPT cite your content accurately</li>
<li>RAG Systems: Enable companies to build knowledge bases from your public content</li>
<li>Documentation: Provide developers with clean, parseable API docs</li>
<li>Content Syndication: Share articles in a universal, lightweight format</li>
<li>Knowledge Graphs: Help semantic web tools understand your site structure</li>
</ul>
<h4>Key Features</h4>
<ul>
<li>Zero Configuration: Works out of the box with sensible defaults</li>
<li>Markdown Endpoints: Access any post/page as Markdown by adding <code>.md</code> to the URL</li>
<li>llms.txt Standard: Auto-generates discovery file for AI agents</li>
<li>YAML Front Matter: Rich metadata for better AI understanding</li>
<li>Flexible: Control which post types are exposed</li>
<li>Performance: Built-in caching and rate limiting</li>
<li>Privacy-Focused: Per-post control over AI access</li>
<li>Standards-Compliant: Follows emerging llms.txt specification</li>
</ul>
<h4>Business Value</h4>
<ul>
<li>Future-Proof: Position your content for the AI-driven web</li>
<li>Zero Cost: No API fees or external dependencies</li>
<li>SEO Boost: Alternate content formats can improve discoverability</li>
<li>Competitive Edge: Early adoption of AI-friendly formats</li>
<li>Analytics: Track which content AI agents prefer</li>
</ul>

AgentMark

AI-Ready Markdown Endpoints & llms.txt discovery for WordPress. Clean, machine-readable content for AI agents and RAG systems.

Muhammad Adnan Hanif

HR RAG Chatbot helps employees get instant answers to HR policy questions using advanced AI technology. The plugin uses Retrieval Augmented Generation (RAG) to provide accurate, context-aware responses based on your company’s HR policies.
Features: 
* Multiple LLM support (Google Gemini API, OpenAI API) 
* Document indexing and chunking 
* Employee context awareness 
* Chat history logging 
* Gutenberg block and shortcode support
Third-Party Services: 
This plugin integrates with Google Gemini API and OpenAI API. These are third-party services and their use is subject to their respective terms of service and privacy policies. The plugin does not include or bundle these services – you must obtain your own API keys from the service providers.
<h3>External Services & Data Usage</h3>
This plugin connects to external AI services to generate responses. Please review the following information about data usage and privacy.
Services Used:
<ol>
<li>
Google Gemini API (if configured)
<ul>
<li>Used for: Generating AI responses to user questions</li>
<li>Data sent: User questions, HR policy document excerpts, employee context (designation, grade, etc.)</li>
<li>Privacy Policy: https://policies.google.com/privacy</li>
<li>Terms of Service: https://policies.google.com/terms</li>
</ul>
</li>
<li>
OpenAI API (if configured)
<ul>
<li>Used for: Generating AI responses to user questions</li>
<li>Data sent: User questions, HR policy document excerpts, employee context (designation, grade, etc.)</li>
<li>Privacy Policy: https://openai.com/privacy</li>
<li>Terms of Service: https://openai.com/terms</li>
</ul>
</li>
</ol>
What Data Is Transmitted: 
* User’s question text 
* Relevant HR policy document chunks (retrieved from your local database) 
* Employee profile information (if configured: designation, grade, department, location, years of service) 
* System prompts and model parameters
Important Privacy Notes: 
* Data is transmitted only when generating responses to user questions 
* No data is permanently stored by external AI providers for training purposes (per their policies) 
* All HR policy documents are stored locally in your WordPress database 
* You control what data is indexed and made available to the chatbot
Local WordPress Storage:
The plugin stores the following data in your WordPress database: 
* Option name: <code>hr_rag_options</code> – Plugin settings including API keys 
* Database tables: <code>wp_hr_rag_docs</code>, <code>wp_hr_rag_chunks</code>, <code>wp_hr_rag_chats</code> 
* Transients: <code>hr_rag_context_{session_id}</code> – Temporary employee context (expires after 1 hour) 
* Chat logs: Questions, answers, and context used for each conversation
Data Control:
You have full control over your data: 
* Delete API keys anytime from plugin settings 
* Clear all indexed documents using “Delete” buttons in Knowledge Base 
* Remove all chat logs from the database 
* Uninstall plugin to remove all data (see Uninstallation section) 
* No data is sent to external services without your API keys configured
Developer Contact: 
For questions about this plugin’s data handling, visit: https://faststeptech.com/contact/
<h3>Third-Party Service Attribution</h3>
This plugin uses the following third-party services:
<ul>
<li>Google Gemini API – AI language model service by Google</li>
<li>OpenAI API – AI language model service by OpenAI</li>
</ul>
These services are not included with the plugin. Users must register and obtain API keys independently from the respective service providers. Use of these services is subject to their terms of service and privacy policies.
<h3>Uninstallation</h3>
When you uninstall this plugin: 
1. All plugin options (<code>hr_rag_options</code>) are removed 
2. All database tables (<code>wp_hr_rag_docs</code>, <code>wp_hr_rag_chunks</code>, <code>wp_hr_rag_chats</code>) are deleted 
3. All transients are cleared 
4. No data remains in your WordPress installation

HR RAG Chatbot

AI-powered HR policy chatbot using RAG (Retrieval Augmented Generation) technology.

AgentMark vs HR RAG Chatbot