This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Tailor a resume to a job description by extracting keywords, scoring match, and rewriting bullets for impact. Use when applying to a role, optimizing for ATS keyword match, or customizing a cover letter.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Tailor a base resume to a specific job description with keyword-match scoring, gap analysis, and rewritten-bullet suggestions.
resume, CV, job application, ATS, applicant tracking system, keyword match, resume tailoring, cover letter, job description, hiring, recruiter, career, job search, bullet rewrite, accomplishment, impact statement
Before tailoring the resume, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
jd.txtresume.txtpython scripts/resume_matcher.py resume.txt jd.txt
references/bullet_rewrite_patterns.mdassets/tailored_resume_template.mdGoal: Get a quantitative score for how well the current resume matches a target job description before submitting.
Steps:
jd.txtpython scripts/resume_matcher.py resume.txt jd.txtExpected Output: A score, a kept-keyword list, and a missing-keyword list.
Time Estimate: 5-10 minutes per job description.
Goal: Convert task-oriented bullets ("responsible for…") into impact bullets that match recruiter and ATS expectations.
Steps:
references/bullet_rewrite_patterns.mdExpected Output: Bullet list rewritten in CAR format with metrics.
Time Estimate: 5 minutes per bullet.
Goal: Pull the strongest 3-5 hooks from the resume that map directly to the top requirements in the job description.
Steps:
python scripts/resume_matcher.py resume.txt jd.txt --jsonExpected Output: 3-5 evidence sentences for the cover letter.
Time Estimate: 10 minutes.
Reads a resume text file and a job description text file, returns:
# Human-readable
python scripts/resume_matcher.py resume.txt jd.txt
# JSON for programmatic use
python scripts/resume_matcher.py resume.txt jd.txt --json
references/bullet_rewrite_patterns.md — CAR pattern, action-verb library, quantification examples, weak-phrase blacklistreferences/ats_optimization_guide.md — How ATS parses resumes, formatting do's and don'ts, keyword density boundsassets/tailored_resume_template.md — A bare resume skeleton with section ordering, length guidance, and keyword-placement notes. Fill in your content.personal-productivity/lead-researcher/ for prepping informational interviewsmarketing/copywriting/ for cover letter prose qualityagents/personas/ workflows when authoring sample profiles아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.