ai-job-search/.claude/skills/job-application-assistant/04-job-evaluation.md

framework_version

framework_version
1.0.0

Job Evaluation Framework

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...")