|
| 1 | +# Evaluation Walkthrough |
| 2 | + |
| 3 | +> A step-by-step example of how career-copilot evaluates a job offer, showing what each block produces and how the scoring works. |
| 4 | +
|
| 5 | +--- |
| 6 | + |
| 7 | +## Starting the Evaluation |
| 8 | + |
| 9 | +Paste a job URL into Copilot CLI: |
| 10 | + |
| 11 | +``` |
| 12 | +Evaluate this: https://boards.greenhouse.io/example/jobs/12345 |
| 13 | +``` |
| 14 | + |
| 15 | +career-copilot reads your `cv.md`, `config/profile.yml`, `modes/_profile.md`, and `modes/_shared.md`, then runs the full A-F evaluation pipeline. |
| 16 | + |
| 17 | +--- |
| 18 | + |
| 19 | +## Block A — Role Summary |
| 20 | + |
| 21 | +The AI extracts structured metadata from the JD: |
| 22 | + |
| 23 | +```markdown |
| 24 | +## A — Role Summary |
| 25 | + |
| 26 | +| Field | Value | |
| 27 | +|-------|-------| |
| 28 | +| **Company** | Acme Corp | |
| 29 | +| **Role** | Senior Backend Engineer | |
| 30 | +| **Archetype** | AI Platform / LLMOps | |
| 31 | +| **Domain** | Developer Tools | |
| 32 | +| **Function** | Engineering | |
| 33 | +| **Seniority** | Senior | |
| 34 | +| **Remote** | Hybrid (NYC, 3 days/week) | |
| 35 | +| **Location** | New York, USA | |
| 36 | +| **Team size** | 8-person platform team | |
| 37 | +| **URL** | https://boards.greenhouse.io/example/jobs/12345 | |
| 38 | + |
| 39 | +**TL;DR**: Build and maintain the AI inference platform serving 10M+ daily requests. |
| 40 | +The team owns model deployment, observability, and cost optimization. |
| 41 | +``` |
| 42 | + |
| 43 | +The **archetype** classification determines which scoring weights and profile sections apply. |
| 44 | + |
| 45 | +--- |
| 46 | + |
| 47 | +## Block B — CV Match (Score: 4.2/5) |
| 48 | + |
| 49 | +A requirement-by-requirement comparison against your CV: |
| 50 | + |
| 51 | +```markdown |
| 52 | +## B — CV Match (Score: 4.2/5) |
| 53 | + |
| 54 | +### Requirements Mapping |
| 55 | + |
| 56 | +| # | JD Requirement | CV Evidence | Strength | |
| 57 | +|---|---------------|-------------|----------| |
| 58 | +| 1 | 5+ years backend engineering | 7 years across 3 companies | ✅ Strong | |
| 59 | +| 2 | Kubernetes & container orchestration | Led K8s migration for 200-service platform | ✅ Strong | |
| 60 | +| 3 | ML model serving (TensorFlow Serving, Triton) | Deployed PyTorch models via custom pipeline | ⚠️ Partial | |
| 61 | +| 4 | Observability (Datadog, Prometheus) | Built Grafana dashboards, Prometheus alerting | ✅ Strong | |
| 62 | +| 5 | Cost optimization at scale | No direct evidence | ❌ Gap | |
| 63 | + |
| 64 | +### Gaps & Mitigation |
| 65 | + |
| 66 | +| Gap | Severity | Mitigation Strategy | |
| 67 | +|-----|----------|---------------------| |
| 68 | +| ML serving frameworks (Triton) | Medium | Adjacent: custom serving pipeline + quick Triton ramp-up | |
| 69 | +| Cloud cost optimization | Low | Portfolio project on spot instance optimization | |
| 70 | +``` |
| 71 | + |
| 72 | +**How scoring works**: Each requirement is weighted by how prominently it appears in the JD. Strong matches contribute fully, partial matches at 50%, gaps at 0%. The weighted average gives the block score. |
| 73 | + |
| 74 | +--- |
| 75 | + |
| 76 | +## Block C — Level & Strategy (Score: 4.0/5) |
| 77 | + |
| 78 | +Compares your seniority to what the JD expects: |
| 79 | + |
| 80 | +```markdown |
| 81 | +## C — Level & Strategy (Score: 4.0/5) |
| 82 | + |
| 83 | +**JD Level**: Senior (IC4-IC5 equivalent) |
| 84 | +**Candidate Level**: Senior-to-Staff trajectory |
| 85 | +**Assessment**: At-level to slightly over-leveled |
| 86 | + |
| 87 | +### Positioning Strategy |
| 88 | +- Lead with: Platform ownership and cross-team impact |
| 89 | +- Key proof points: Led K8s migration (cv.md §3), mentored 4 engineers (cv.md §5) |
| 90 | +- Risk: None — strong at-level match with growth headroom |
| 91 | +``` |
| 92 | + |
| 93 | +--- |
| 94 | + |
| 95 | +## Block D — Comp & Market (Score: 3.8/5) |
| 96 | + |
| 97 | +Market research via web search: |
| 98 | + |
| 99 | +```markdown |
| 100 | +## D — Comp & Market (Score: 3.8/5) |
| 101 | + |
| 102 | +### Market Compensation |
| 103 | +| Source | Range | |
| 104 | +|--------|-------| |
| 105 | +| levels.fyi | $180K-$240K (Senior, NYC) | |
| 106 | +| Glassdoor | $170K-$220K | |
| 107 | +| H1B data | $195K (median, similar roles) | |
| 108 | + |
| 109 | +### JD Stated Comp |
| 110 | +$175K-$210K base + equity (if mentioned) |
| 111 | + |
| 112 | +### Assessment |
| 113 | +Slightly below market median for NYC Senior Backend. Equity could compensate. |
| 114 | +Negotiate toward $200K+ base if offer comes in. |
| 115 | +``` |
| 116 | + |
| 117 | +--- |
| 118 | + |
| 119 | +## Block E — Red Flags & Cultural Signals (Score: 4.5/5) |
| 120 | + |
| 121 | +Proactive detection of concerns: |
| 122 | + |
| 123 | +```markdown |
| 124 | +## E — Red Flags & Cultural Signals (Score: 4.5/5) |
| 125 | + |
| 126 | +### 🟢 Positive Signals |
| 127 | +- Clear team structure and reporting line mentioned |
| 128 | +- Concrete technical challenges (not vague "fast-paced") |
| 129 | +- Remote flexibility (hybrid, not forced 5-day) |
| 130 | + |
| 131 | +### 🟡 Watch |
| 132 | +- "Startup mentality" in a 500-person company — could mean under-resourced |
| 133 | + |
| 134 | +### 🔴 Red Flags |
| 135 | +- None detected |
| 136 | +``` |
| 137 | + |
| 138 | +--- |
| 139 | + |
| 140 | +## Block F — Final Verdict |
| 141 | + |
| 142 | +The weighted global score and recommendation: |
| 143 | + |
| 144 | +```markdown |
| 145 | +## F — Final Verdict |
| 146 | + |
| 147 | +| Dimension | Score | Weight | |
| 148 | +|-----------|-------|--------| |
| 149 | +| CV Match | 4.2 | 30% | |
| 150 | +| Level & Strategy | 4.0 | 20% | |
| 151 | +| Comp & Market | 3.8 | 20% | |
| 152 | +| Cultural Signals | 4.5 | 15% | |
| 153 | +| North Star Alignment | 4.0 | 15% | |
| 154 | + |
| 155 | +### Global Score: 4.1 / 5 — Grade: B+ |
| 156 | + |
| 157 | +**Recommendation**: Good match, worth applying. Strong technical alignment |
| 158 | +with moderate comp upside. The platform ownership scope matches your |
| 159 | +growth trajectory. |
| 160 | + |
| 161 | +### Suggested Next Steps |
| 162 | +1. Apply with tailored CV (run `generate PDF` mode) |
| 163 | +2. Prepare STAR stories for system design and K8s migration |
| 164 | +3. Research the team lead on LinkedIn for culture fit signals |
| 165 | +``` |
| 166 | + |
| 167 | +--- |
| 168 | + |
| 169 | +## Score Interpretation |
| 170 | + |
| 171 | +| Score Range | Grade | Meaning | |
| 172 | +|------------|-------|---------| |
| 173 | +| 4.5+ | A | Strong match — apply immediately | |
| 174 | +| 4.0–4.4 | B | Good match — worth applying | |
| 175 | +| 3.5–3.9 | C | Decent but not ideal — apply only with specific reason | |
| 176 | +| Below 3.5 | D-F | Recommend against applying | |
| 177 | + |
| 178 | +--- |
| 179 | + |
| 180 | +## Output Files |
| 181 | + |
| 182 | +After evaluation, career-copilot creates: |
| 183 | + |
| 184 | +| File | Location | Content | |
| 185 | +|------|----------|---------| |
| 186 | +| Evaluation report | `reports/001-acme-corp-2026-04-10.md` | Full A-F analysis | |
| 187 | +| Tailored PDF | `output/cv-acme-corp-2026-04-10.pdf` | ATS-optimized resume | |
| 188 | +| Tracker entry | `data/applications.md` | Pipeline row with score and status | |
| 189 | + |
| 190 | +--- |
| 191 | + |
| 192 | +## Try It Yourself |
| 193 | + |
| 194 | +```bash |
| 195 | +# 1. Setup (if not done) |
| 196 | +bash setup.sh |
| 197 | + |
| 198 | +# 2. Open Copilot CLI in this directory |
| 199 | + |
| 200 | +# 3. Paste any job URL |
| 201 | +# "Evaluate this: https://boards.greenhouse.io/company/jobs/123456" |
| 202 | + |
| 203 | +# 4. For batch evaluation, add URLs to batch/batch-input.tsv and run: |
| 204 | +# "Process the batch" |
| 205 | +``` |
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