mirror of
https://github.com/MadsLorentzen/ai-job-search.git
synced 2026-09-17 00:26:26 +00:00
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
@@ -0,0 +1,173 @@
|
||||
# Job Evaluation Framework
|
||||
|
||||
<!-- SETUP: Skill match areas and career goals are personalized by running /setup -->
|
||||
|
||||
## Scoring Dimensions
|
||||
|
||||
Evaluate each job posting against these five dimensions:
|
||||
|
||||
### 1. Technical Skills Match (0-100)
|
||||
How well do the required/preferred skills align with the candidate's capabilities?
|
||||
|
||||
| Score | Meaning |
|
||||
|-------|---------|
|
||||
| 80-100 | Core requirements are primary skills |
|
||||
| 60-79 | Most requirements match, 1-2 gaps that are learnable |
|
||||
| 40-59 | Partial match, significant upskilling needed |
|
||||
| 0-39 | Fundamental mismatch |
|
||||
|
||||
**Strong match areas:** [YOUR_PRIMARY_SKILLS]
|
||||
**Moderate match areas:** [YOUR_SECONDARY_SKILLS]
|
||||
**Weak match areas:** [SKILLS_YOU_LACK]
|
||||
|
||||
### 2. Experience Match (0-100)
|
||||
Does work history align with what they're looking for?
|
||||
|
||||
| Score | Meaning |
|
||||
|-------|---------|
|
||||
| 80-100 | Direct experience in the same domain and role type |
|
||||
| 60-79 | Related experience, transferable skills clear |
|
||||
| 40-59 | Adjacent experience, would need to make the case |
|
||||
| 0-39 | Unrelated experience |
|
||||
|
||||
**Strong:** [YOUR_DIRECT_EXPERIENCE_DOMAINS]
|
||||
**Moderate:** [YOUR_ADJACENT_EXPERIENCE]
|
||||
**Entry-level:** [ROLES_WITH_LIMITED_EXPERIENCE]
|
||||
|
||||
### 3. Behavioral/Culture Fit (0-100)
|
||||
Does the role and company culture match the behavioral profile?
|
||||
|
||||
| Score | Meaning |
|
||||
|-------|---------|
|
||||
| 80-100 | Culture strongly matches behavioral preferences |
|
||||
| 60-79 | Mixed signals but mostly compatible |
|
||||
| 40-59 | Some friction areas |
|
||||
| 0-39 | Significant culture mismatch |
|
||||
|
||||
**Red flags to research:** Department disorganization, work dominated by maintenance over development, poor chemistry with leadership, culture mismatches. Check reviews, media coverage, LinkedIn connections, and network contacts for insider perspective.
|
||||
|
||||
### 4. Location & Logistics (Pass/Fail + Notes)
|
||||
- Within commute range: PASS
|
||||
- Remote with occasional office: PASS
|
||||
- Requires relocation: FAIL (deal-breaker)
|
||||
- Frequent international travel: FLAG (discuss with user)
|
||||
|
||||
### 5. Career Alignment & Motivation (0-100)
|
||||
Does this role advance career goals and contain tasks that energize?
|
||||
|
||||
| Score | Meaning |
|
||||
|-------|---------|
|
||||
| 80-100 | Strongly aligned with career direction, clear growth path |
|
||||
| 60-79 | Good role but only partially aligned with long-term goals |
|
||||
| 40-59 | Decent job but doesn't build toward career goals |
|
||||
| 0-39 | Dead end or backwards step |
|
||||
|
||||
**Career goals:**
|
||||
- [YOUR_CAREER_GOAL_1]
|
||||
- [YOUR_CAREER_GOAL_2]
|
||||
- [YOUR_CAREER_GOAL_3]
|
||||
|
||||
**Motivation filter:** Evaluate not just whether you *can* do the tasks, but whether the tasks will *energize* you. Consider:
|
||||
- Tasks that energize: [YOUR_ENERGIZING_TASKS]
|
||||
- Tasks that drain: [YOUR_DRAINING_TASKS]
|
||||
- Non-task factors: leadership style, department culture, company values, degree of autonomy
|
||||
|
||||
**Life situation alignment:** Consider personal constraints:
|
||||
- **Security**: [YOUR_FINANCIAL_SITUATION_CONTEXT]
|
||||
- **Flexibility**: [YOUR_SCHEDULE_CONSTRAINTS]
|
||||
- **Professional development**: [YOUR_GROWTH_PRIORITIES]
|
||||
|
||||
### 6. Salary Benchmark (Optional)
|
||||
|
||||
If the salary lookup tool is configured (`salary_data.json` exists), look up the company:
|
||||
```
|
||||
python salary_lookup.py "<Company Name>" --json
|
||||
```
|
||||
|
||||
If a city is known from the posting, add `--city "<City>"` to narrow results.
|
||||
|
||||
Present findings as:
|
||||
```
|
||||
### Salary Benchmark
|
||||
| Metric | Value |
|
||||
|--------|-------|
|
||||
| [Category] index | XX.X (+/-X.X% vs baseline) |
|
||||
| Overall index | XX.X (+/-X.X% vs baseline) |
|
||||
```
|
||||
|
||||
Interpret results relative to the baseline defined in the data file's metadata. For index-based data, higher typically means above-market compensation.
|
||||
|
||||
If the salary tool is not configured, skip this section.
|
||||
|
||||
## Output Format
|
||||
|
||||
Present the evaluation as:
|
||||
|
||||
```
|
||||
## Job Fit Evaluation: [Role] at [Company]
|
||||
|
||||
| Dimension | Score | Notes |
|
||||
|-----------|-------|-------|
|
||||
| Technical Skills | XX/100 | [brief note] |
|
||||
| Experience Match | XX/100 | [brief note] |
|
||||
| Behavioral Fit | XX/100 | [brief note] |
|
||||
| Location | PASS/FAIL | [brief note] |
|
||||
| Career Alignment | XX/100 | [brief note] |
|
||||
|
||||
**Overall Score: XX/100** (weighted average of scored dimensions)
|
||||
|
||||
### Verdict: [Strong Fit / Good Fit / Moderate Fit / Weak Fit / Poor Fit]
|
||||
|
||||
### Key Strengths for This Role
|
||||
- [bullet points]
|
||||
|
||||
### Gaps to Address
|
||||
- [bullet points]
|
||||
|
||||
### Recommendation
|
||||
[1-2 sentences: apply/skip/apply with caveats]
|
||||
|
||||
### Company Research Checklist
|
||||
- [ ] Checked company website (mission, values, recent news)
|
||||
- [ ] Checked review sites (Glassdoor, Jobindex, etc.)
|
||||
- [ ] Checked LinkedIn for team size, recent hires, connections
|
||||
- [ ] Checked media for restructuring, growth, or workplace issues
|
||||
- [ ] Identified network contacts who may know the team/manager
|
||||
```
|
||||
|
||||
## Weighting
|
||||
- Technical Skills: 30%
|
||||
- Experience Match: 25%
|
||||
- Behavioral Fit: 15%
|
||||
- Career Alignment: 30%
|
||||
|
||||
(Location is pass/fail, not weighted)
|
||||
|
||||
## Thresholds
|
||||
- **Strong Fit** (75+): Definitely apply, tailor everything
|
||||
- **Good Fit** (60-74): Apply, address gaps in cover letter
|
||||
- **Moderate Fit** (45-59): Consider carefully, discuss with user
|
||||
- **Weak Fit** (30-44): Probably skip unless strategic reasons
|
||||
- **Poor Fit** (<30): Skip
|
||||
|
||||
## Pre-Application: Call the Employer (Best Practice)
|
||||
|
||||
Before writing the application, consider whether the candidate should call the contact person listed in the posting. **Only call if there are substantive questions** - never call just to "be remembered."
|
||||
|
||||
### When to Suggest Calling
|
||||
- The posting has unclear or ambiguous requirements
|
||||
- It's unclear which competencies are essential vs. nice-to-have
|
||||
- The role description is vague about day-to-day tasks
|
||||
- There's a named contact person who invites questions
|
||||
|
||||
### Good Questions to Ask
|
||||
- "What are the primary challenges in this role?"
|
||||
- "How is time typically divided across the listed responsibilities?"
|
||||
- "Which competencies are most critical for success in this position?"
|
||||
- "What does success look like in the first 6-12 months?"
|
||||
|
||||
### Rules for the Call
|
||||
- Prepare a 30-second "elevator pitch" about your background in case they ask
|
||||
- The call's purpose is **gathering information**, not delivering a pitch
|
||||
- Take notes - use what you learn to tailor the application
|
||||
- Reference the conversation naturally in the cover letter ("After speaking with [name], I was especially drawn to...")
|
||||
Reference in New Issue
Block a user