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Hr Candidate Experience

Community
tuanductran
hr-candidate-experience

Help HR teams, recruiters, and talent acquisition leaders design and improve the candidate experience across the full hiring journey. Use when asked to improve candidate experience, map the candidate journey, reduce candidate drop-off, design interview feedback, create a candidate communication plan, or measure candidate satisfaction.

Overview

Publishertuanductran
Repositoryhr-skills
Skill namehr-candidate-experience
Stars
78
Forks
20
Bundled files
4
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.

  • 4 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 Candidate Experience 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-candidate-experience
  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-candidate-experience .claude/skills/hr-candidate-experience
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hr Candidate Experience 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 Candidate Experience 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 Candidate Experience 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.

Candidate experience design

Design and optimize the end-to-end candidate experience — from first impression and application through interviews, offers, and rejection — to improve conversion rates, employer brand, and quality of hire.

Supported tasks

  • Mapping the candidate journey and identifying friction points
  • Designing application and pre-screening experiences
  • Creating candidate communication plans and message templates
  • Designing structured interview experiences that respect candidate time
  • Building post-interview feedback and update processes
  • Designing offer and acceptance experiences
  • Creating compassionate and on-brand rejection communications
  • Measuring candidate experience through surveys and NPS
  • Auditing the candidate experience for bias and accessibility
  • Designing virtual and in-person interview day experiences
  • Building candidate experience standards and training for hiring teams
  • Analyzing candidate drop-off rates and conversion patterns

Key prompts

Candidate journey mapping

  1. "Map the end-to-end candidate journey for [role type] at [company] and identify the top three friction points."
  2. "What does the ideal candidate experience look like from first contact to offer acceptance for [company]?"
  3. "Design a candidate journey map for [senior leadership / technical / volume hiring] roles showing touchpoints, emotions, and pain points."
  4. "How do we audit our current candidate experience to identify where and why candidates drop off?"
  5. "What moments in the hiring process matter most to candidates' perception of [company] as an employer?"

Communication and transparency

  1. "Write a candidate communication plan covering every hiring stage from application to final decision."
  2. "Design an automated communication sequence that keeps candidates informed without requiring recruiter manual effort."
  3. "Write a [acknowledgment / screening invitation / interview confirmation / post-interview update] email for candidates."
  4. "How do we communicate realistic timelines to candidates when our hiring process is genuinely slow?"
  5. "What do candidates most want to know at each stage of the process and how do we proactively share it?"
  6. "Write a transparent 'what to expect' guide for candidates going through our interview process."

Interview experience

  1. "Design an interview day experience for [on-site / virtual] candidates that is professional and welcoming."
  2. "Write an interview preparation guide to send candidates before their interview with [company]."
  3. "What interviewer behaviors most damage candidate experience and how do we prevent them?"
  4. "How do we train interviewers to be professional, engaging, and on-brand during candidate interactions?"
  5. "Design a structured debrief process that reaches timely decisions without making candidates wait unnecessarily."

Offer and rejection experience

  1. "Write an offer communication for [candidate] that reinforces their excitement about joining [company]."
  2. "Design an offer acceptance experience that maintains momentum and reduces offer decline risk."
  3. "Write a rejection communication that is respectful, specific enough to be useful, and protects employer brand."
  4. "How do we handle candidate feedback requests after rejection in a way that is honest and helpful?"
  5. "What touchpoints between offer acceptance and start date reduce pre-boarding dropout?"

Measurement and improvement

  1. "Design a candidate experience survey for [application / interview / offer] stage that generates actionable data."
  2. "What candidate experience metrics should we track and how do we benchmark them?"
  3. "How do we analyze candidate NPS data to identify which part of our process needs the most improvement?"
  4. "Design a candidate experience improvement roadmap for [company] based on [survey findings]."
  5. "How do we build a continuous candidate experience feedback loop into our TA operations?"

Tips

  • Candidate experience is a brand experience — every interaction either strengthens or damages how candidates perceive the company, even if they don't get the job.
  • Communication speed and transparency are the cheapest and highest-impact improvements to candidate experience; silence is interpreted as disrespect.
  • Train every interviewer, not just recruiters — hiring manager and panel behavior during interviews is the most memorable part of the candidate experience.
  • Rejection experience matters as much as hiring experience; rejected candidates become customers, referrals, and future applicants — treat them accordingly.
  • Measure candidate experience at each stage, not just at the end; waiting until post-hire to survey loses feedback from candidates who dropped out or declined.

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 Candidate Experience AI skill do?

Help HR teams, recruiters, and talent acquisition leaders design and improve the candidate experience across the full hiring journey. Use when asked to improve candidate experience, map the candidate journey, reduce candidate drop-off, design interview feedback, create a candidate communication plan, or measure candidate satisfaction.

Why use Hr Candidate Experience on TypingMind?

Because you install it once and use it with any model. Hr Candidate Experience 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 Candidate Experience in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tuanductran/hr-skills/tree/main/skills/hr-candidate-experience. 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 Candidate Experience?

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 Candidate Experience?

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

Is the Hr Candidate Experience 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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