e02eb28e98
Plugin:skill pairs now read as noun:verb commands instead of repeating the plugin name. Also added concise descriptions to all SKILL.md frontmatter. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2.7 KiB
2.7 KiB
Resume Tailoring - Usage Examples
Example 1: Internal Role (Same Company)
USER: "I want to apply for Principal PM role in 1ES team at Microsoft. Here's the JD: {paste}"
WORKFLOW:
1. Library Build: Finds 29 resumes
2. Research: Microsoft 1ES team, internal culture, role benchmarking
3. Template: Features PM2 Azure Eng Systems role (most relevant)
4. Discovery: Surfaces VS Code extension, Bhavana AI side project
5. Assembly: 92% JD coverage, 75% direct matches
6. Generate: MD + DOCX + Report
7. User approves → Library updated with 6 discovered experiences
RESULT: Highly competitive internal application
Example 2: Career Transition (Different Domain)
USER: "I'm a TPM trying to transition to ecology PM role. JD: {paste}"
WORKFLOW:
1. Library Build: Finds existing TPM resumes
2. Research: Ecology sector, sustainability focus, cross-domain transfers
3. Template: Reframes "Technical Program Manager" → "Program Manager, Environmental Systems"
4. Discovery: Surfaces volunteer conservation work, grad research in environmental modeling
5. Assembly: 65% JD coverage - flags gaps in domain-specific knowledge
6. Generate: Resume + gap analysis with cover letter recommendations
RESULT: Bridges technical skills with environmental domain
Example 3: Career Gap Handling
USER: "I have a 2-year gap while starting a company. JD: {paste}"
WORKFLOW:
1. Library Build: Finds pre-gap resumes
2. Template: Includes startup as legitimate role
3. Discovery: Surfaces skills developed during startup (fundraising, product dev, team building)
4. Assembly: Frames gap as entrepreneurial experience
RESULT: Gap becomes strength showing initiative and diverse skills
Example 4: Multi-Job Batch (3 Similar Roles)
USER: "I want to apply for these 3 TPM roles:
1. Microsoft 1ES Principal PM
2. Google Cloud Senior TPM
3. AWS Container Services Senior PM"
WORKFLOW:
1. Multi-job detection triggered (3 JDs)
2. Library Build once, Gap Analysis deduplicates across all 3
3. Shared Discovery: 30 min session surfaces 5 new experiences
4. Per-Job Processing:
- Microsoft: 85% coverage, emphasizes Azure/1ES alignment
- Google: 88% coverage, emphasizes technical depth
- AWS: 78% coverage, addresses AWS gap in cover letter recs
5. Batch finalization: All 3 reviewed and approved
RESULT: 3 high-quality resumes in 40 min vs 45 min sequential
Example 5: Incremental Batch Addition
WEEK 1: Process 3 jobs (Microsoft, Google, AWS) → 40 min
WEEK 2: "Add Stripe and Meta to my batch"
- Load existing batch with 5 previously discovered experiences
- Only 3 new gaps (vs 14 original)
- 10-minute incremental discovery
- 2 additional resumes in 20 min (vs 30 min from scratch)