본문으로 건너뛰기
cccskills
무료GitHub에 공개

hiring-scorecard

Creates structured hiring scorecards for any role. Takes job title, requirements, and team context. Generates comprehensive scorecard with weighted scoring rubric, interview questions per competency, evaluation matrix, red/green flags, and reference check questions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

실행 점수 미검증

설치 방법 보기

포함된 파일(4)

  • SKILL.md2.8 KB
  • references/competency-library.md1.1 KB
  • references/output-template.md14.5 KB
  • references/usage-and-customization.md3.7 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Hiring Scorecard Generator

Build a structured, bias-reducing hiring scorecard that lets an interview panel make consistent, evidence-based decisions for any role.

Contents

  • references/output-template.md -- the full 9-section scorecard.md structure with every block, table, and per-section guideline.
  • references/competency-library.md -- which competencies to score by role type (technical IC, non-technical IC, manager, executive).
  • references/usage-and-customization.md -- how to use the output, focus modes, biases prevented, format adaptations, and legal/compliance reminders.

Inputs

Job Title and Requirements are required; ask before generating if either is missing. The rest sharpen the output: Team Context, Level/Seniority, Role Type, Industry, Interview Panel, Compensation Band, Urgency/Timeline.

Workflow

  1. Gather role context. Confirm job title, level, team structure, reporting line, and business need. Ask for missing required inputs.
  2. Define criteria. Separate must-have from nice-to-have qualifications, each specific and observable with a verification method. See references/output-template.md Section 2.
  3. Select competencies. Choose 6-10 competencies for the role using references/competency-library.md.
  4. Build the scoring rubric. Anchor each competency to the 1-5 behavioral scale. See references/output-template.md Section 3.
  5. Generate interview questions. Write 3-4 behavioral/situational questions per competency with follow-up probes and "what good/bad looks like". See references/output-template.md Section 4.
  6. Create the evaluation matrix. Produce the independent interviewer scoresheet. See Section 5.
  7. Identify flags. List 8-12 concrete red flags and 8-12 green flags tied to observable behavior. See Section 6.
  8. Draft reference checks. Produce targeted reference questions that surface real signal. See Section 7.
  9. Add debrief guide and appendix. Include the debrief agenda, decision framework, anti-bias checklist, scoring calculator, and panel/comparison templates. See Sections 8-9.
  10. Write the file. Output a single scorecard.md in the working directory (or a user-specified path), assembled from all nine sections and ready to hand to a panel without further editing.

For focus modes (technical, leadership, sales/GTM, creative, operations, culture-heavy), format adaptations, and legal/compliance reminders, see references/usage-and-customization.md.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

OneWave-AI의 스킬 모두 보기

이 스킬의 문제 신고