Job Application Assistant

CommunityPopular

MadsLorentzen

job-application-assistant

Assists with job applications: evaluating job postings, tailoring CVs, writing cover letters, and preparing for interviews. Triggers on keywords like: job posting, job application, CV, cover letter, resume, interview prep, job fit, career, application, apply, ansøgning, stilling

Overview

Publisher	MadsLorentzen
Repository	`ai-job-search`
Skill name	`job-application-assistant`
Stars	46.2K
Forks	15.9K
Bundled files	9
License	MIT
Links	Skill source Repository

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.
9 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by MadsLorentzen on GitHub. Read the source before you install it.

Installation

Install the Job Application Assistant AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/MadsLorentzen/ai-job-search/tree/master/.claude/skills/job-application-assistant
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/MadsLorentzen/ai-job-search/tree/master/.claude/skills/job-application-assistant

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/MadsLorentzen/ai-job-search.git /tmp/ai-job-search
mkdir -p .claude/skills
cp -r /tmp/ai-job-search/.claude/skills/job-application-assistant .claude/skills/job-application-assistant

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Job Application Assistant 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 Job Application Assistant 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 Job Application Assistant 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.

Job Application Assistant

Workflow

When the user provides a job posting (URL or text), follow this workflow:

Step 1: Research & Evaluate Fit

Fetch the job posting content (use WebFetch for URLs). A 403 is not a dead end - follow the escalation order in 09-web-research.md before concluding a page is unavailable, and prefer the employer's own careers posting over an aggregator listing
Keep the full posting text verbatim for Step 3b to archive - never a summary
Analyze the posting for required competencies, keywords, and priorities
Research the company (website, LinkedIn, mission, recent news), per 09-web-research.md
Score the posting against the candidate's profile using the framework in 04-job-evaluation.md
Present the evaluation table and verdict
Suggest whether the candidate should call the employer before applying (see 04-job-evaluation.md for guidance)
Ask the user if they want to proceed with an application

Step 2: Tailor CV

Before writing either document, derive <company>_<role> once by the Subfolder naming rule in documents/README.md; reuse that exact value for the CV, cover letter, and Step 3b archive path. If the rule says to stop because the derived name is empty, stop before creating any file.
Read the most relevant existing CV variant from cv/ as a starting point
Follow the guidelines in 05-cv-templates.md
Create cv/main_<company>_<role>.tex with tailored content
Adjust: profile statement, skills section, experience bullet emphasis, section order

Step 3: Write Cover Letter

Follow the writing style rules in 03-writing-style.md (critical: no em-dashes, no cliches)
Follow the template structure in 06-cover-letter-templates.md
Create cover_letters/cover_<company>_<role>.tex
Ensure the letter connects specific experience to the role requirements

Step 3b: Record the Application

Run this once both documents exist. A CV or cover letter drafted alone is not yet an application.
Follow /apply Step 6b (.claude/commands/apply.md) exactly: same header, same match-then-update rule, same drafted row, same posting archive, same prohibition on touching job_scraper/seen_jobs.json. It is stated there once so the two paths cannot drift. Four of its values are named in /apply's own terms: cv_file/cover_letter_file are the paths written in Steps 2 and 3 here, source is the posting URL from Step 1, deadline is the application deadline from the posting text Step 1 keeps verbatim (empty when the posting states none - never guess one), and the posting text item 7 archives is the one Step 1 read.
This step exists here because /scrape Step 5 routes straight into this skill. Without it, that path writes two documents and records nothing.

Step 4: Interview Preparation

Follow the framework in 07-interview-prep.md
Prepare STAR-format answers for likely questions
Identify role-specific talking points
Draft questions the candidate should ask the interviewer

Reference Files

File	Purpose
`01-candidate-profile.md`	Education, experience, skills, publications, awards
`02-behavioral-profile.md`	Behavioral assessment, strengths, ideal environments
`03-writing-style.md`	Tone, structure, do's and don'ts
`04-job-evaluation.md`	Scoring framework for job fit
`05-cv-templates.md`	LaTeX CV structure and tailoring rules
`06-cover-letter-templates.md`	LaTeX cover letter structure and tailoring rules
`07-interview-prep.md`	STAR examples, tough questions, roleplay guidelines
`08-application-forms.md`	Portal free-text fields: self-introduction, project entries, character-limited pitches
`09-web-research.md`	Fetching postings and company pages: trust boundary, the WebFetch 403 fallback, escalation order, claim verification

Quick Commands

The user may also ask for individual steps without the full workflow:

"Evaluate this job posting" - Step 1 only
"Write a CV for [company]" - Step 2 only
"Write a cover letter for [role] at [company]" - Step 3 only
"Help me prepare for an interview at [company]" - Step 4 only
"What jobs should I look for?" - Career strategy discussion using profile + evaluation framework

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 Job Application Assistant AI skill do?

Why use Job Application Assistant on TypingMind?

Because you install it once and use it with any model. Job Application Assistant 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 Job Application Assistant in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MadsLorentzen/ai-job-search/tree/master/.claude/skills/job-application-assistant. 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 Job Application Assistant?

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 Job Application Assistant?

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

Is the Job Application Assistant AI skill free?

Yes. It is published on GitHub by MadsLorentzen 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Job Application Assistant

Workflow

Step 1: Research & Evaluate Fit

Step 2: Tailor CV

Step 3: Write Cover Letter

Step 3b: Record the Application

Step 4: Interview Preparation

Reference Files

Quick Commands

Bundled files

Frequently asked questions

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