| name | patterns |
| description | Analyze rejection patterns across all tracked applications to find what's working and what's wasting time. Triggers on patterns, rejection analysis, pattern analysis, improve targeting. |
Patterns — Rejection Pattern Detector
Read ~/.openclaw/workspace/skills/career-ops/references/scoring-system.md for scoring context.
Data Paths
- Tracker:
~/.openclaw/workspace/career-ops-data/data/applications.md
- Reports:
~/.openclaw/workspace/career-ops-data/reports/
- Profile:
~/.openclaw/workspace/career-ops-data/config/profile.yml
- Portals:
~/.openclaw/workspace/career-ops-data/portals.yml
- Script:
node ~/.openclaw/workspace/skills/career-ops/scripts/analyze-patterns.mjs
Minimum Threshold
Before running analysis, check: does data/applications.md have at least 5 entries with status beyond "Evaluated"?
If not: tell the user there's not enough data yet and suggest coming back with more outcomes.
Step 1 — Run Analysis Script
Execute: node ~/.openclaw/workspace/skills/career-ops/scripts/analyze-patterns.mjs
Parse JSON output containing: metadata, funnel, scoreComparison, archetypeBreakdown, blockerAnalysis, remotePolicy, companySizeBreakdown, scoreThreshold, techStackGaps, recommendations.
Step 2 — Generate Report
Save to reports/pattern-analysis-{YYYY-MM-DD}.md with sections:
- Conversion Funnel
- Score vs Outcome
- Archetype Performance
- Top Blockers
- Remote Policy Patterns
- Tech Stack Gaps
- Recommended Score Threshold
- Top 5 Recommendations
Step 3 — Present Summary
Condensed view:
- One-line stat summary
- Top 3 findings
- Link to full report
Step 4 — Offer to Apply Recommendations
Suggest actionable changes:
- Update
portals.yml to filter out low-converting roles
- Set score threshold in profile
- Adjust archetype targeting
Outcome Classification
| Status | Outcome |
|---|
| Interview, Offer, Responded, Applied | Positive |
| Rejected, Discarded | Negative |
| SKIP, NO APLICAR | Self-filtered |
| Evaluated | Pending |
