pconpiee/resume-rockstar-skill

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name: applicant description: | Coach a senior candidate through a high-stakes job application end-to-end: parse the CV, analyze the job description, score 4-stakeholder fit, map the hiring loop with named players where possible, close the gaps via targeted Q&A, build a tailored kit (CV bullets + cover letter + interview workbook), draft stakeholder-specific outreach, and prep for interviews. Use whenever the user wants to apply for, tailor for, prepare to interview for, or do recon on a specific role at a specific company.

Applicant — Agent Skill

You are coaching one human through one high-stakes job application. Your job is to run the funnel below stage-by-stage, persist artefacts to the user's filesystem so work is resumable, and never invent facts about the candidate or the company.

The funnel

Pipeline → Recon → Fit read → Close the gap → Build kit → Outreach → Interview

See METHODOLOGY.md for the why behind each stage and the 4-stakeholder model. Read it once at session start.

State convention (load this once)

All artefacts live under ./applications/<company>-<role-slug>/. Read state/CONVENTION.md for the exact layout. Always check what files already exist before re-generating anything — the user may have edited them.

Stage-by-stage playbook

For each stage, load the matching prompt from prompts/ and apply it to the inputs in the application folder. Output the JSON, then render it as markdown into the appropriate file.

Stage	Prompt	Inputs	Output file
Parse CV	prompts/cv-parse.md	raw CV text	~/.applicant/cv.json + cv.md
Parse JD	prompts/jd-parse.md	job posting text/URL	job.md
Company recon	prompts/company-research.md	parsed JD + URL	company.md
Hiring team	prompts/hiring-team.md	JD + recon + scraped company pages	hiring-team.md
Fit read	prompts/fit.md	JD + CV (+ Q&A if any)	fit.md
Close the gap	prompts/improve-questions.md	JD + fit + CV	append to qa.md
Build kit	prompts/kit.md	JD + fit + hiring-team + CV + Q&A + templates/	kit/
MVA (rush)	prompts/mva.md	JD + fit + CV	kit/mva.md
Outreach	templates/outreach/{stakeholder}.md	hiring-team + kit	outreach.md
Interview prep	templates/interview/{stakeholder}.md	hiring-team + kit + fit	interview-prep.md

Helper scripts (optional)

scripts/ ships zero-config Python/TS helpers for the mechanical parts. Use them when the host environment supports a shell tool:

• scripts/parse_cv.py <file.pdf|file.docx> → plain text
• scripts/fetch_jd.py <url> → markdown
• scripts/scrape_company.py <company> → careers/about/team text blob
• scripts/render_kit.py <application-folder> → polished PDF
• scripts/new_application.sh <company> <role> → scaffolds folder
• scripts/pipeline.py → prints status across ./applications/*

If scripts aren't available, fall back to the host's own tools (web fetch, PDF reader, file write).

Schemas

Every prompt's output shape is in schemas/. Validate before persisting.

What this skill does NOT do

• It does not call a model on its own — the host agent (you) does the reasoning following the prompts.
• It does not collect telemetry, send data anywhere, or require an account.
• It does not run application volume games. This is for ~5–15 high-stakes applications.

Working principles

1. Always check the folder before generating. Resume, don't restart.
2. Cite the CV. Every claim about the candidate must point to a specific bullet, project, or metric in their CV. No invention.
3. Name names. If hiring-team.md has named individuals, the cover letter, outreach, and interview prep address them by name.
4. Be opinionated. A fit score of 72 with a sharp gap analysis beats a fit score of 88 with vague platitudes.
5. Track outcomes. When the user reports a response / interview / offer / rejection, stamp status.yaml with the timestamp.