hr-performance-review

hr-performance-review is a skill for Claude Code from modu-ai/moai-cowork. It costs 97 tokens per session (2,581 once invoked), scanned A, original, Apache-2.0.

A skill for designing and running employee performance reviews. It covers MBO, OKRs, KPIs, 360-degree feedback, review guides, and feedback conversations; OKRs set goals and measurable results, while KPIs track ongoing performance.

In plain words
What is it for?
It is for setting goals and metrics, building review templates, designing 360-degree evaluations, writing appraisal guidance, and preparing feedback conversations.
Why use it?
It helps organizations connect individual work with company goals and use clearer, more consistent review processes.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the moai-recruiter plugin — 6 skills, 2 agents shipped together

Good fit It is for setting goals and metrics, building review templates, designing 360-degree evaluations, writing appraisal guidance, and preparing feedback conversations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/modu-ai/moai-cowork/hr-performance-review
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add modu-ai/moai-cowork --skill hr-performance-review
Clone the repo
git clone --depth 1 https://github.com/modu-ai/moai-cowork

Made for: Claude Code.

Or install moai-recruiter, the plugin that ships this one along with the rest of its 6 skills, 2 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for hr-performance-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/modu-ai/moai-cowork/hr-performance-review/github.svg)](https://agentmods.dev/skills/modu-ai/moai-cowork/hr-performance-review)
Your own site
<a href="https://agentmods.dev/skills/modu-ai/moai-cowork/hr-performance-review"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-cowork/hr-performance-review/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for hr-performance-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/modu-ai/moai-cowork/hr-performance-review"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-cowork/hr-performance-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 97 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,581 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00097 $0.02581
Opus 5 $0.00048 $0.01290
Sonnet 5 $0.00019 $0.00516
Haiku 4.5 $0.00010 $0.00258

Measured 8d ago against content hash 81e72be63334, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

hr-performance-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/moai-recruiter/skills/hr-performance-review/SKILL.md · 198 lines

How it starts

The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.

성과평가 (Performance Review)

개요

조직 규모와 문화에 맞는 성과평가 체계를 설계하고 실행을 지원한다. 2026년 추세인 OKR+KPI 병행 운영, AI 기반 성과 분석, 360도 피드백을 반영하며 근로기준법 준수 기반의 공정한 평가 프로세스를 구축한다.

트리거 키워드

성과평가, 인사 고과, 성과 리뷰, KPI 설정, OKR, MBO, 360도 평가, 피드백 면담, 목표 설정, 성과 관리, 연봉 협상, 직원 평가

워크플로우

1단계: 조직 현황 및 평가 목적 확인

  • 조직 규모 (스타트업 / 중소기업 / 대기업)
  • 현재 사용 중인 성과관리 방식
  • 평가 목적:
    • 보상 연계 (연봉 인상, 성과급)
    • 성장 지원 (육성, 역량 개발)
    • 조직 목표 정렬 (전사 방향성 공유)

2단계: 성과관리 프레임워크 선택

2026년 트렌드: OKR + KPI 병행

구분 MBO KPI OKR
초점 책임·보상 연계 수치 측정 방향·정렬
주기 연간 상시 분기
보상 연계 강함 있음 원칙적 분리
투명성 낮음 중간 높음 (전사 공개)
적합 조직 위계적 전통 기업 반복·안정 업무 스타트업·혁신 조직
주요 도입 공공기관, 대기업 전통 업종 전 산업 SK, 한화 금융 계열, 스타트업

2026년 권장 접근법:

  • 스타트업 / 테크 기업: OKR(분기) + KPI(상시 모니터링) 병행
  • 중소기업: 단순화된 MBO + 핵심 KPI 3-5개
  • 대기업 전통 업종: MBO 기반 + 팀 단위 OKR 도입 검토
  • 공통: AI 기반 성과 데이터 분석 도입 트렌드

3단계: OKR 작성 지원

OKR 작성 원칙:

  • Objective (목표): 질적, 도전적, 동기 부여적 (1-5개)
    • 예: "고객이 사랑하는 온보딩 경험 구축"
  • Key Results (핵심결과): 측정 가능, 시간 한정 (목표당 2-5개)
    • 예: "온보딩 완료율 60% → 85%로 향상 (3개월)"
    • 예: "NPS 점수 32점 → 50점으로 개선"

OKR 작성 체크리스트:

  • Objective는 영감을 주는가? (Not: "xx% 달성")
  • Key Results는 수치로 측정 가능한가?
  • Key Results 달성 여부로 Objective 달성을 판단할 수 있는가?
  • 60-70% 달성 가능한 도전적 목표인가? (Stretch Goal)
  • 보상과 직접 연결되어 있지 않은가? (OKR 원칙)

4단계: 평가 설계

평가 항목 구성:

성과 평가 (What: 목표 달성도) — 60~70% 비중
  - KPI/OKR Key Results 달성률
  - 목표 대비 실적 (정량)
  - 주요 프로젝트 기여도

역량 평가 (How: 행동 방식) — 30~40% 비중
  - 직무 역량 (업무 전문성)
  - 리더십/협업 역량
  - 성장 가능성 (잠재력)

360도 평가 설계:

  • 상향 평가: 부하직원 → 관리자 (익명 보장)
  • 동료 평가: 동료 → 동료 (협업 역량 중심)
  • 자기 평가: 본인 → 본인 (성찰 및 성장 계획)
  • 평가 항목: 5점 척도 + 서술형 피드백

5단계: 평가 면담 (Calibration & Feedback)

평가 면담 스크립트 (기본 구조):

① 시작 (5분): 면담 목적과 분위기 설정
   "오늘은 지난 [기간] 동안의 성장과 다음 [기간] 계획을 함께 이야기해보려 해요."

② 자기 평가 확인 (10분):
   "스스로 가장 잘 해냈다고 생각하는 것은 무엇인가요?"
   "아쉬웠던 부분이나 더 잘할 수 있었던 점은?"

③ 관리자 피드백 (10분):
   - 긍정적 피드백: 구체적 행동 + 영향 + 감사
   - 개선 피드백: 관찰 사실 + 영향 + 기대 행동 (SBI 모델)

④ 다음 기간 목표 합의 (10분):
   OKR/KPI 초안 함께 검토

⑤ 지원 사항 확인 (5분):
   "제가 어떻게 지원해드리면 목표 달성에 도움이 될까요?"

Read the full file on GitHub · 198 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 198 lines · 97 tokens per session scan A 81e72be63334

Subscribe to this mod's changes

hr-performance-review is a skill published in the GitHub repository modu-ai/moai-cowork (300 stars, last pushed 8d ago), licensed Apache-2.0. It adds 97 tokens to every session and 2,581 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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