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Initial release: AI-powered job application framework
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
AI Job Search
committed by
Mads Lorentzen
Mads Lorentzen
co-authored by
Claude Opus 4.6
Claude Opus 4.6
commit
c66d599d75
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# /apply - Drafter-Reviewer Job Application Workflow
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You are orchestrating a two-agent job application workflow. The job posting is provided below as `$ARGUMENTS` (either a URL or pasted text).
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Follow these steps **exactly in order**. Do not skip steps.
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---
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## Step 0: Parse Input
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- If `$ARGUMENTS` looks like a URL, use `WebFetch` to retrieve the job posting content.
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- If it is pasted text, use it directly.
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- Extract: **company name**, **role title**, **department** (if mentioned), **location**, and **language** of the posting (Danish or English).
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- Store these for use throughout the workflow.
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---
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## Step 1: DRAFTER - Evaluate Fit
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Read the evaluation framework:
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- `.claude/skills/job-application-assistant/04-job-evaluation.md`
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- `.claude/skills/job-application-assistant/01-candidate-profile.md`
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Using the framework from `04-job-evaluation.md`, evaluate the job posting against the candidate's profile. If the salary lookup tool is configured, run:
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```bash
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python salary_lookup.py "<Company Name>" --json
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```
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If the posting specifies a city, add `--city "<City>"` to narrow results. Parse the JSON output and include the salary benchmark in the evaluation. If the tool is not configured or returns an error, skip the salary benchmark.
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Present the evaluation to the user with:
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1. **Skills match** - which required/preferred skills match vs. gaps
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2. **Experience match** - how work history maps to the role
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3. **Behavioral/culture match** - how behavioral profile fits the role/company culture
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4. **Salary benchmark** - salary index for the company (if available)
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5. **Overall fit score** and recommendation (strong fit / moderate fit / weak fit)
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After presenting the evaluation, ask the user:
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> "Should I proceed with drafting the CV and cover letter for this role?"
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**If the user says no, stop here.** If yes, continue to Step 2.
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---
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## Step 2: DRAFTER - Draft CV + Cover Letter
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Read the following reference files:
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- `.claude/skills/job-application-assistant/01-candidate-profile.md`
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- `.claude/skills/job-application-assistant/03-writing-style.md`
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- `.claude/skills/job-application-assistant/05-cv-templates.md`
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- `.claude/skills/job-application-assistant/06-cover-letter-templates.md`
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Also read the most recent existing CV and cover letter files for structural reference:
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- Read any existing `cv/main_*.tex` file as a LaTeX template reference
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- Read any existing `cover_letters/cover_*.tex` or `cover_letters/Cover_*.tex` file as a template reference
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### CV (`cv/main_<company>.tex`)
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- Always in **English**
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- Follow the moderncv/banking format from `05-cv-templates.md`
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- Tailor the profile statement and experience bullets to the specific role
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- Reframe skills and achievements to match job requirements
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- Keep to 2 pages
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### Cover Letter (`cover_letters/cover_<company>_<role>.tex`)
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- **Match the language of the job posting** (Danish posting -> Danish cover letter, English posting -> English cover letter)
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- Follow the structure from `06-cover-letter-templates.md`
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- Use the `cover.cls` template
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- Tailor the opening paragraph to the specific role and company
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- Address to a named person if available in the posting, otherwise "Dear Hiring Manager" (or equivalent in posting language)
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- Keep to approximately one page
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- Any mention of agentic coding or AI tooling must reference **Claude Code** by name
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Write both files to disk.
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---
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## Step 3: REVIEWER - Research & Critique
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Use the **Agent tool** to spawn a `general-purpose` reviewer agent with the following prompt:
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```
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You are a hiring manager proxy reviewing a job application. Your job is to make the application as targeted and compelling as possible.
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## Your Tasks
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### 1. Research the Company
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Use WebSearch and WebFetch to research:
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- The company's website, mission, and recent news
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- The specific department or team (if mentioned in the posting)
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- Any recent projects, press releases, or strategic initiatives relevant to the role
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- Company culture and values
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### 2. Read All Reference Materials
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Read these files to understand the candidate and quality standards:
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- `.claude/skills/job-application-assistant/01-candidate-profile.md`
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- `.claude/skills/job-application-assistant/02-behavioral-profile.md`
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- `.claude/skills/job-application-assistant/03-writing-style.md`
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- `.claude/skills/job-application-assistant/04-job-evaluation.md`
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- `.claude/skills/job-application-assistant/05-cv-templates.md`
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- `.claude/skills/job-application-assistant/06-cover-letter-templates.md`
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### 3. Read the Drafts
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Read the drafted CV and cover letter:
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- `cv/main_<COMPANY>.tex`
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- `cover_letters/cover_<COMPANY>_<ROLE>.tex`
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### 4. Read the Job Posting
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<JOB_POSTING>
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<INSERT_JOB_POSTING_TEXT_HERE>
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</JOB_POSTING>
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### 5. Produce Feedback
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Return a structured critique with **specific, actionable suggestions** in these categories:
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**a) Missed keywords/requirements**
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- List any requirements or keywords from the posting that are not addressed in the CV or cover letter
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- For each, suggest where and how to add them (with specific text suggestions)
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**b) Company/department-specific angles**
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- Based on your research, suggest specific angles to add
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- Suggest how to connect experience to the company's strategic priorities
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**c) Action-oriented reframing**
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- Identify passive or generic statements and suggest action-oriented rewrites
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**d) Tone and style issues**
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- Check against the writing style guide (03-writing-style.md)
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- Flag any issues with tone, formality, or voice
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**e) Verification checklist**
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Run this checklist and report pass/fail for each:
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- [ ] All claims match actual profile - no fabricated skills, experience, or achievements
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- [ ] Job titles, dates, company names, and locations are correct
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- [ ] Contact details are correct
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- [ ] Profile statement is tailored to the specific role
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- [ ] Key job requirements are addressed
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- [ ] No LaTeX syntax errors (balanced braces, correct commands)
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- [ ] No spelling or grammar errors
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- [ ] Agentic coding / AI tooling references mention Claude Code by name
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- [ ] Cover letter addressed correctly
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- [ ] Cover letter fits approximately one page
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- [ ] CV follows 2-page moderncv/banking format
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**CRITICAL RULE:** All suggestions must be grounded in actual profile data. Do NOT suggest fabricating skills, experience, or achievements. If a requirement is a gap, say so honestly and suggest how to frame adjacent experience instead.
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Return your full feedback as a single structured message.
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```
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**Important:** Before spawning the agent, replace `<COMPANY>`, `<ROLE>`, and `<INSERT_JOB_POSTING_TEXT_HERE>` with the actual values from Steps 0-2.
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---
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## Step 4: DRAFTER - Revise Based on Feedback
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Once the reviewer agent returns its feedback:
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1. Read the reviewer's suggestions carefully
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2. Read both draft files again
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3. Incorporate the suggestions that improve the application:
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- Add missed keywords where they fit naturally
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- Add company-specific angles from the reviewer's research
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- Reframe passive statements to be more action-oriented
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- Fix any tone/style issues
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- Fix any verification checklist failures
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4. Update both files **in place** (edit, don't recreate)
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5. Do NOT incorporate suggestions that would fabricate skills or experience
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---
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## Step 5: Present Final Output
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After revision, present to the user:
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### Verification Checklist
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Re-run the full verification checklist from CLAUDE.md and report pass/fail for each item.
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### Key Tailoring Decisions
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Summarize 3-5 key decisions made to tailor the application:
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- What was emphasized and why
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- What company-specific angles were incorporated
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- What the reviewer suggested that was most impactful
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- Any gaps that were acknowledged or reframed
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### Files Created
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List the files written:
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- `cv/main_<company>.tex`
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- `cover_letters/cover_<company>_<role>.tex`
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Tell the user: "Both files are ready for your review. Open them to check the final output before compiling."
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@@ -0,0 +1,198 @@
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# /setup - Profile Onboarding Interview
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You are running the onboarding setup for the AI Job Search framework. Your goal is to collect the user's professional information and populate all profile files so the `/apply` workflow works out of the box.
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---
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## Step 0: Welcome & Choose Path
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Welcome the user and explain what this setup does. Then offer two paths:
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> **Welcome to the AI Job Search setup!**
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>
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> I'll help you set up your professional profile so Claude can evaluate job postings, tailor CVs, write cover letters, and prepare you for interviews.
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>
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> **Two ways to get started:**
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>
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> **Path A: Import from CV (recommended)** - Share your existing CV or resume (mention the file with @ or paste the text). I'll extract your information automatically and ask follow-up questions for anything missing.
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>
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> **Path B: Interview mode** - I'll walk you through structured questions section by section. Great if you're starting from scratch.
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>
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> Which do you prefer?
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If the user specifies `$ARGUMENTS` containing `--section <name>`, skip to that section only for updating.
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---
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## Path A: Document Import
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If the user provides a CV/resume:
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1. Read the document thoroughly
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2. Extract all structured information: name, contact, education, experience, skills, publications, awards
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3. Present a summary of what was extracted
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4. Ask follow-up questions for gaps (behavioral profile, career goals, deal-breakers, salary expectations, references)
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5. Proceed to file generation (Step 3)
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---
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## Path B: Interview Mode
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Walk through each section conversationally. Ask questions naturally, not as a form. Let the user answer in their own words and you'll structure the data.
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### Section 1: Identity & Contact
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Ask about:
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- Full name
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- Location (city, country)
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- Phone, email, LinkedIn, GitHub
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- Languages spoken (with proficiency levels)
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- Current employment status
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- Family/commute constraints (if any)
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### Section 2: Education
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For each degree:
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- Level (PhD, MSc, BSc, etc.), field, institution, years
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- Thesis topic (if applicable)
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- Key coursework or topics
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Also ask about certifications (online courses, professional certs).
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### Section 3: Professional Experience
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For each role (most recent first):
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- Job title, company, dates, location
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- Key responsibilities (3-5 bullets)
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- Key achievements or projects
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- Technologies/tools used
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Also ask about independent projects, freelance work, or side projects.
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### Section 4: Technical Skills
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- Programming languages + proficiency level
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- ML/AI frameworks and tools
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- Domain expertise
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- Software tools and platforms
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- Any other technical skills
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### Section 5: Publications & Awards (optional)
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- Peer-reviewed papers, conference presentations
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- Hackathons, competitions, awards
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- Skip if not applicable
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### Section 6: Behavioral Profile (optional)
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If they have a formal assessment (PI, DISC, Myers-Briggs, StrengthsFinder):
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- Ask them to describe or share the results
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If not, ask behavioral questions:
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- "What work environments do you thrive in?"
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- "What drains your energy at work?"
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- "How do you prefer to work in teams?"
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- "How do you make decisions - quickly or deliberately?"
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- "What's your communication style?"
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- Synthesize answers into a behavioral profile
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### Section 7: Career Goals & Preferences
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- Target roles and industries
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- What excites you in work
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- Deal-breakers and must-haves
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- Salary expectations/baseline (optional)
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- What environments to avoid
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- Commute/location constraints
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### Section 8: References (optional)
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For each reference:
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- Name, title, company, email, phone
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- Relationship to the user
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### Section 9: Job Search Configuration
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This section generates the search queries that power `/scrape`. Use the information from Sections 1, 4, and 7 to build targeted queries.
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Ask about:
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- **Role titles to search for:** "What job titles should I search for? For example: Data Scientist, ML Engineer, Geophysicist." Collect 3-8 specific titles.
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- **Key skills as search terms:** "Which of your skills are most likely to appear in job postings?" Pick 3-5 that are distinctive and searchable.
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- **Target companies (optional):** "Are there specific companies you'd like to monitor for openings?"
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- **Geographic scope:** "Which cities or regions should I search in? How far are you willing to commute?" Use this to define the location filter tiers (ideal, acceptable, borderline, too far).
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- **Job portals:** "The framework includes tools for Danish job portals (Jobindex, Jobbank, Jobdanmark, Jobnet). Are these the right ones for you, or do you use other sites?" Note: if the user is outside Denmark, acknowledge that the built-in CLI tools are Denmark-specific and suggest they can add their own portal integrations or rely on LinkedIn/Google site-searches.
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**Important:** Also suggest role types the user may not have considered, based on their skill profile. For example:
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- If they have strong Python + domain expertise: "Have you considered roles like 'Technical Consultant' or 'Solutions Engineer' in your domain?"
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- If they have ML + a specific industry: "Companies in adjacent industries also hire for these skills. Should I include searches for [adjacent sector]?"
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- If they have project management experience alongside technical skills: "Would you also want to search for 'Technical Project Manager' or 'Team Lead' roles?"
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This proactive suggestion step helps users discover career paths they might not have considered.
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---
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## Step 3: Generate Profile Files
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Once all information is collected (via either path), generate the following files:
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### 1. Update `CLAUDE.md`
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Replace all `[PLACEHOLDER]` tokens with the user's actual information. Keep the structure, workflow, and verification checklist intact.
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### 2. Populate `01-candidate-profile.md`
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Write the full candidate profile with structured sections: Identity, Education, Professional Experience, Independent Projects, Technical Skills, Publications, Awards, References.
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### 3. Populate `02-behavioral-profile.md`
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Write the behavioral profile based on assessment results or synthesized answers.
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### 4. Update `04-job-evaluation.md`
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Replace skill match areas with the user's actual skills:
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- Strong match areas: [their primary skills]
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- Moderate match areas: [their secondary skills]
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- Weak match areas: [skills they lack]
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Update career goals and motivation filters with their actual preferences.
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### 5. Update `05-cv-templates.md`
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Add role-specific profile statement templates based on their background.
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### 6. Update `07-interview-prep.md`
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Create STAR examples from their actual experience (at least 3-4 examples).
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### 7. Update `cv/main_example.tex`
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Replace placeholder personal data with their actual name, contact info, and add their education and most recent experience entries.
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### 8. Generate `.claude/skills/job-scraper/search-queries.md`
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Replace all placeholder tokens in the search queries file with the user's actual information from Section 9:
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- Replace `[YOUR_PRIMARY_ROLE_TYPE]`, `[YOUR_PRIMARY_JOB_TITLE]`, etc. with actual role titles
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- Replace `[YOUR_KEY_SKILL]`, `[YOUR_DOMAIN_KEYWORD_1]`, etc. with actual skills and domain terms
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- Replace `[YOUR_CITY]`, `[YOUR_COUNTRY]`, `[YOUR_REGION]` with actual location
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- Fill in the location filter tiers (ideal, acceptable, borderline, too far) based on commute constraints
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- Organize queries into priority categories matching the user's career direction:
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- Priority 1: Their strongest/most desired role direction
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- Priority 2: Their domain expertise
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- Priority 3: Adjacent roles they could pivot into
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- Priority 4: Broader roles (wider net)
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---
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## Step 4: Confirm & Next Steps
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Present a summary:
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> **Setup complete!** Here's what was generated:
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>
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> - `CLAUDE.md` - Your full candidate profile
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> - `.claude/skills/job-application-assistant/01-candidate-profile.md` - Structured profile
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> - `.claude/skills/job-application-assistant/02-behavioral-profile.md` - Behavioral assessment
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> - `.claude/skills/job-application-assistant/04-job-evaluation.md` - Personalized evaluation framework
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> - `.claude/skills/job-application-assistant/05-cv-templates.md` - CV templates with your profile statements
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> - `.claude/skills/job-application-assistant/07-interview-prep.md` - STAR examples from your experience
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> - `cv/main_example.tex` - Your LaTeX CV template
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> - `.claude/skills/job-scraper/search-queries.md` - Job search queries for `/scrape`
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>
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> **Try it out:**
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> - Run `/scrape` to search for matching jobs right now
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> - Run `/apply` with a job posting URL to see the full application workflow
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> - Run `/setup --section search` later to update your search queries as your priorities evolve
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---
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## Design Principles
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- Each section is a natural conversation, not a form
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- The user can skip optional sections
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- Synthesize answers into structured formats (the user doesn't need to know markdown or LaTeX)
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- Can be re-run with `--section <name>` to update specific sections (e.g., `/setup --section search` to reconfigure job search queries without re-doing the full profile)
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- Section 9 (search) proactively suggests role types the user may not have considered
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- At the end, suggest running `/scrape` and `/apply` with a test job posting
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