From egg
This skill should be used when the user wants to analyze a job description against their resume, extract keywords, identify gaps, or prepare tailoring notes. Trigger phrases include "analyze JD", "analyze this job description", "extract keywords from JD", "gap analysis for", "what does this role need", "compare my resume to this JD", "tailor resume", "optimize resume for JD", "build resume for", "target job description", "customize resume for", "resume for this role", "refactor resume", "update resume for", "match resume to JD", or when a user pastes a job description alongside their resume. It produces a notes.md analysis file that resume-tailor uses to generate the final resume.
npx claudepluginhub luqmannurhakimbazman/ashfordThis skill uses the workspace's default tool permissions.
Analyze a job description against the master resume (`hojicha/resume.tex`) and candidate context (`hojicha/candidate-context.md`). Output: `hojicha/<company>-<role>-resume/notes.md`.
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Analyze a job description against the master resume (hojicha/resume.tex) and candidate context (hojicha/candidate-context.md). Output: hojicha/<company>-<role>-resume/notes.md.
candidate-context.md. You may rephrase and emphasize -- never invent.Read the master resume, candidate context, and the job description.
Required:
- Job description (pasted text, file, or URL -- fetch URL content if needed)
- Master resume: hojicha/resume.tex
- Candidate context: hojicha/candidate-context.md
Optional (ask if not provided):
- Company name
- Role title
- Special instructions (e.g., "emphasize ML experience")
Derive <company> and <role> from the JD. Use lowercase, hyphenated slugs (e.g., kronos-research-ml-researcher-resume).
Cross-reference JD requirements against candidate materials. If there are 2+ areas where the JD demands depth that current materials don't address:
references/candidate-discovery.md for probing techniqueshojicha/candidate-context.mdSkip if candidate-context.md already covers the JD requirements. Note in the output if skipped and why.
Extract and categorize keywords from the JD:
| Category | Examples |
|---|---|
| Hard skills | Python, PyTorch, distributed training |
| Soft skills | Leadership, cross-functional collaboration |
| Domain knowledge | NLP, reinforcement learning, quantitative finance |
| Tools/platforms | AWS, Docker, Kubernetes |
| Qualifications | BSc in CS, 3+ years experience |
Separate into Required vs Preferred. Count frequency -- terms repeated across the JD are high-priority. Include both acronyms and full forms (e.g., "Natural Language Processing (NLP)").
Map each JD requirement to existing resume content:
candidate-context.mdFor each gap, provide:
Prioritize High gaps first. Include at least one concrete project idea. Never recommend fabricating experience.
Create hojicha/<company>-<role>-resume/notes.md containing:
After completing the analysis, tell the user: "Analysis complete. Run the resume-tailor skill to generate the tailored resume.tex from these notes."