daypunk/lockedin/lockedin-render-resume-en

Claude Code and agent skill by daypunk/lockedin

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Writes an English resume from the user's experience, tuned to one of 10 built-in personas. Metric-first XYZ/CAR bullets, two-turn writer/reviewer with a 5-dimension rubric. Activate when the user says "render resume", "make a resume", "polish my resume", or names a target role. The writer turn loads the matching spec from ./personas/ before drafting.

Install

npx vskill@latest install daypunk/lockedin/lockedin-render-resume-en

SKILL.md

render-resume-en

Research-based calibration. Ships with full rubric, writer and reviewer prompts, and a banned-phrase regex list. Dimension definitions derived from cross-source consensus across 20+ US tech resume guides. See research-notes.md for citations.

Use this when

  • User asks for an English resume targeting a tech / PM persona.
  • User wants their existing resume "polished" against the rubric.

Do NOT use when

  • User wants a Korean cover letter → render-jaso.
  • The vault has no project / role / achievement nodes yet → seed first.

Required design constraints

  • Metric-first bullets — every bullet contains a number (%, x,

$, count, or duration). Rubric enforces ≥80% metric density via regex.

  • XYZ or CAR per bullet — XYZ = "Accomplished X as measured by Y,

by doing Z"; CAR = Challenge / Action / Result compressed to one bullet line. Active voice, quantified result. (STAR is the implicit story arc; XYZ/CAR is the bullet shape.)

  • Active voice — banned: "was responsible for", "helped to", "worked

on", "was involved in".

  • No keyword stuffing — ATS-friendly via real verbs and metrics, not

hidden keywords.

  • Target persona — 10 built-in personas under ./personas/

(us-tech-senior, us-tech-mid, pm-product, backend-senior, frontend-senior, mobile-senior, data-engineer-mid, ml-engineer-mid, designer-senior, marketing-mid). Each spec file contains tone guidance, action verb cluster, and persona-specific banned phrases.

Two-turn pattern

Same writer/reviewer split as render-jaso:

  1. Writer turn produces the resume markdown.
  2. Reviewer turn re-loads RUBRIC.md fresh, runs the metric-density

regex, scores action-verb diversity, ATS keyword coverage, vagueness banlist. Emits JSON.

Final checklist

  • Metric-density regex passed (≥80% bullets contain a number).
  • Reviewer turn was a separate Claude context with fresh RUBRIC.md load.
  • Concrete ontology slugs quoted (project / role / achievement).
  • Active voice; no banned phrases.

Files in this directory

SKILL.md
research-notes.md citations with URL + ISO date + 2-sentence gloss
RUBRIC.md 5 dimensions; score bands; fixture authoring guide
prompt-writer.md writer turn instruction
prompt-reviewer.md reviewer turn instruction (separate Claude context)
banned_phrases.json regex list of weak / vague / templated phrases
personas/
us-tech-senior.md Senior IC / Staff / Principal
us-tech-mid.md Mid-level IC (3-7y)
pm-product.md Product Manager
backend-senior.md Senior backend engineer, distributed systems focus
frontend-senior.md Senior frontend engineer, perf + design system focus
mobile-senior.md Senior iOS/Android engineer
data-engineer-mid.md Mid-level data engineer, dbt/Airflow/warehouse
ml-engineer-mid.md Mid-level ML engineer, classical ML productization
designer-senior.md Senior product / UX designer
marketing-mid.md Mid-level growth / product marketing manager

Security

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  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

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