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Hr Employee Self Service

Community
tuanductran
hr-employee-self-service

Help HR operations teams and digital HR leaders design, implement, and optimize employee self-service programs including ESS portals, HR chatbots, knowledge bases, and manager self-service tools. Use when asked to build an employee self-service portal, design an HR chatbot, create an HR knowledge base, reduce HR inquiry volume, or improve employee access to HR information.

Overview

Publishertuanductran
Repositoryhr-skills
Skill namehr-employee-self-service
Stars
78
Forks
20
Bundled files
3
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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Hr Employee Self Service 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.
    https://github.com/tuanductran/hr-skills/tree/main/skills/hr-employee-self-service
  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/tuanductran/hr-skills.git /tmp/hr-skills
mkdir -p .claude/skills
cp -r /tmp/hr-skills/skills/hr-employee-self-service .claude/skills/hr-employee-self-service
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hr Employee Self Service 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 Hr Employee Self Service 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 Hr Employee Self Service 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.

Employee self-service design and optimization

Design and optimize employee and manager self-service experiences — from HR knowledge bases and ESS portals to AI-powered chatbots and automated workflows that reduce inquiry volume and improve employee autonomy.

Supported tasks

  • Designing employee self-service portals and HR intranets
  • Building HR knowledge bases and FAQ content libraries
  • Designing and implementing HR chatbot and virtual assistant programs
  • Developing manager self-service tools and approval workflows
  • Identifying high-volume HR inquiries suitable for self-service
  • Measuring self-service adoption and deflection rates
  • Designing employee-facing HR content that is clear and findable
  • Building self-service onboarding and offboarding experiences
  • Optimizing search and navigation for HR self-service platforms
  • Training employees and managers to use self-service effectively
  • Connecting self-service to backend HR systems and data
  • Auditing and improving self-service content quality

Key prompts

Self-service strategy and design

  1. "Design an employee self-service strategy for [company] that reduces HR tier-1 inquiry volume by [target percentage]."
  2. "What HR tasks and queries are best suited for self-service versus requiring human HR support?"
  3. "Design an ESS portal experience for [company] that employees actually use instead of emailing HR."
  4. "How do we prioritize which HR processes to self-serve first based on volume, complexity, and employee impact?"
  5. "What does a best-practice employee self-service experience look like for [onboarding / leave / benefits / payslips]?"

HR knowledge base and content

  1. "Design an HR knowledge base structure for [company] covering [top employee topics]."
  2. "Write a clear, employee-friendly FAQ answer for [common HR question, for example, 'How do I request annual leave?']."
  3. "How do we audit existing HR content for accuracy, readability, and findability?"
  4. "What writing principles make HR self-service content easy for employees to understand and act on?"
  5. "Design a content maintenance process that keeps the HR knowledge base accurate as policies change."
  6. "How do we categorize and tag HR content so employees can find it through search without knowing HR terminology?"

HR chatbot and virtual assistant

  1. "Design an HR chatbot for [company] that handles [top 20 employee HR queries] without human intervention."
  2. "What chatbot conversation flows work best for [leave requests / payroll queries / policy questions]?"
  3. "How do we design chatbot escalation paths so employees reach a human HR contact when the bot can't help?"
  4. "What data and integrations does our HR chatbot need to provide personalized, accurate answers?"
  5. "How do we measure HR chatbot effectiveness beyond resolution rate?"
  6. "Write a chatbot conversation script for handling [parental leave inquiry / benefits enrollment / performance review process]."

Manager self-service

  1. "Design a manager self-service workflow for [approval process, for example, salary changes, leave approvals, job changes]."
  2. "What manager self-service tools reduce HR administrative burden while improving manager autonomy?"
  3. "How do we train managers to use self-service tools confidently without creating errors?"
  4. "Design the ideal manager dashboard showing real-time team data (headcount, absence, performance) accessible without HR involvement."

Adoption and measurement

  1. "Design a change management plan to drive employee adoption of our new [ESS portal / HR chatbot]."
  2. "What metrics measure self-service success beyond usage volume?"
  3. "How do we track which HR topics have the lowest self-service resolution rates and prioritize content improvements?"
  4. "Design a continuous improvement process for self-service using employee feedback and usage analytics."

Tips

  • Self-service adoption is determined more by content quality and findability than by the platform technology — employees won't use a portal that gives them wrong or confusing answers.
  • Measure self-service by deflection rate (queries resolved without HR intervention), not just login rates — high visits with low deflection means the content isn't working.
  • Employee self-service works best when HR content is written in plain language from the employee's perspective, not in HR policy language from the organization's perspective.
  • Design for mobile-first access; in high-growth markets like Vietnam, employees frequently access HR information from mobile devices rather than desktop portals.
  • HR chatbots require ongoing content maintenance — set up a regular review cadence to update responses as policies, processes, and organizational details change.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Hr Employee Self Service AI skill do?

Help HR operations teams and digital HR leaders design, implement, and optimize employee self-service programs including ESS portals, HR chatbots, knowledge bases, and manager self-service tools. Use when asked to build an employee self-service portal, design an HR chatbot, create an HR knowledge base, reduce HR inquiry volume, or improve employee access to HR information.

Why use Hr Employee Self Service on TypingMind?

Because you install it once and use it with any model. Hr Employee Self Service 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 Hr Employee Self Service in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tuanductran/hr-skills/tree/main/skills/hr-employee-self-service. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Hr Employee Self Service?

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 Hr Employee Self Service?

As many as you like. As long as a model supports skills, you can use Hr Employee Self Service with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hr Employee Self Service AI skill free?

Yes. It is published on GitHub by tuanductran 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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