# Hr Operations > - Skill: `frank-luongt/hr-operations-2` (Agent Skill) - Install (CLI): `npx skillmds@latest add frank-luongt/hr-operations-2` - Raw SKILL.md: https://api.skillmd.com/api/skills/frank-luongt/hr-operations-2/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: frank-luongt (https://skillmd.com/u/frank-luongt) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/frank-luongt/hr-operations-2 --- --- name: hr-operations description: Manage hiring pipelines, analyze compensation data, create performance review templates, and design onboarding checklists. Use when building HR processes, conducting comp analysis, designing review cycles, or structuring employee onboarding. tags: [hr, hiring, compensation, performance-management] --- # HR Operations Operational HR framework for hiring pipeline management, compensation analysis, performance reviews, and employee onboarding. Covers the process-oriented side of people operations — not strategic workforce planning (which is the CHRO agent's domain). ## Use this skill when - Designing or analyzing a hiring pipeline (stages, conversion rates, time-to-fill) - Conducting compensation benchmarking and pay band analysis - Creating performance review templates and calibration processes - Building employee onboarding checklists (pre-start through 90 days) - Calculating HR metrics (attrition, eNPS, cost-per-hire) - Designing org-level review cycles ## Do not use this skill when - Setting company-wide people strategy or culture (use CHRO agent directly) - Planning OKRs or goal-setting frameworks (use `brainstorm-okrs`) - Running employee engagement surveys (use CHRO agent for strategy) - Handling legal employment matters (use `legal-contract-review` for contract aspects) ## Instructions 1. **Identify the HR operation** — hiring, compensation, performance, or onboarding. 2. **Apply the relevant framework** from the sections below. 3. **Use templates** to standardize output across the organization. 4. **Track metrics** using the HR Metrics Framework for ongoing measurement. --- ## Hiring Pipeline Dashboard ### Pipeline Stages & Benchmarks | Stage | Description | Target Conversion | Target Duration | |-------|------------|-------------------|-----------------| | **Sourced** | Candidate identified (inbound or outbound) | — | — | | **Applied / Screened** | Resume review passed | 20-30% of sourced | 2-3 days | | **Phone Screen** | Recruiter screen completed | 40-60% of screened | 3-5 days | | **Technical / Skills Assessment** | Skills evaluation passed | 30-50% of phone screens | 5-7 days | | **Onsite / Final Interview** | Full interview loop completed | 50-70% of assessments | 5-10 days | | **Offer Extended** | Offer made | 70-90% of onsites | 2-3 days | | **Offer Accepted** | Candidate accepts | 80-90% of offers | 3-7 days | | **Started** | First day completed | 95%+ of accepted | Per start date | ### Pipeline Health Metrics | Metric | Formula | Benchmark | Action if Off | |--------|---------|-----------|---------------| | **Time-to-Fill** | Days from req open to offer accepted | 30-45 days (IC), 45-60 days (manager+) | Review bottleneck stage | | **Cost-per-Hire** | (Internal costs + External costs) / Hires | $3-5K (IC), $10-20K (senior/exec) | Optimize source mix | | **Source Effectiveness** | Hires per source / Candidates per source | Referrals: 2-5x better than job boards | Invest in high-yield channels | | **Offer Acceptance Rate** | Offers accepted / Offers extended | >85% | Review comp competitiveness | | **Quality of Hire** | Performance rating at 6-12 months | >80% meeting/exceeding expectations | Review interview process | ### Pipeline Report Template ```markdown ## Hiring Pipeline — [Period] **Open Requisitions:** [X] | **Hires This Period:** [X] | **Avg Time-to-Fill:** [X] days | Role | Stage | Days in Stage | Recruiter | Hiring Manager | Notes | |------|-------|--------------|-----------|----------------|-------| | | | | | | | ### Funnel Conversion (Period) | Stage Transition | Volume | Conversion | Benchmark | Delta | |-----------------|--------|------------|-----------|-------| | Sourced → Screened | | % | 25% | | | Screened → Phone | | % | 50% | | | Phone → Assessment | | % | 40% | | | Assessment → Onsite | | % | 60% | | | Onsite → Offer | | % | 80% | | | Offer → Accepted | | % | 85% | | ``` --- ## Compensation Analysis Framework ### Market Benchmarking Process | Step | Action | Data Source | |------|--------|------------| | 1 | Define comparison cohort (industry, size, geo, role) | Radford, Pave, Levels.fyi, Option Impact | | 2 | Pull market data at P25, P50, P75 | Survey data + real-time platforms | | 3 | Map internal roles to market equivalents | Job architecture / leveling framework | | 4 | Compare internal comp to market percentile targets | Internal HRIS data | | 5 | Identify outliers (below P25 or above P75) | Comp analysis output | | 6 | Build adjustment recommendations | Budget-constrained optimization | ### Pay Band Design | Level | P25 (Below Market) | P50 (Market Rate) | P75 (Above Market) | Spread | |-------|--------------------|--------------------|---------------------|--------| | IC1 (Junior) | $ | $ | $ | ±15-20% | | IC2 (Mid) | $ | $ | $ | ±15-20% | | IC3 (Senior) | $ | $ | $ | ±20-25% | | IC4 (Staff) | $ | $ | $ | ±20-25% | | M1 (Manager) | $ | $ | $ | ±20-25% | | M2 (Director) | $ | $ | $ | ±25-30% | | M3 (VP) | $ | $ | $ | ±25-30% | ### Total Compensation Modeling | Component | IC (Individual Contributor) | Manager+ | |-----------|---------------------------|----------| | Base Salary | 60-70% of total comp | 50-60% of total comp | | Variable / Bonus | 10-15% | 15-25% | | Equity (RSUs / Options) | 15-25% | 20-30% | | Benefits | 5-10% | 5-10% | ### Internal Equity Analysis ```markdown ## Compensation Equity Review — [Department/Team] | Employee | Role | Level | Tenure | Base | Total Comp | Market % | Compa-Ratio | Flag | |----------|------|-------|--------|------|------------|----------|-------------|------| | | | | | $ | $ | P[X] | X.XX | | **Compa-Ratio:** Employee pay / Pay band midpoint (1.0 = at midpoint) - <0.85 = Below range (retention risk) - 0.85-1.15 = Within range (healthy) - >1.15 = Above range (review justification) ``` --- ## Performance Review Templates ### Self-Assessment Template ```markdown ## Self-Assessment — [Name] — [Review Period] ### Accomplishments 1. [Achievement with quantified impact] 2. [Achievement with quantified impact] 3. [Achievement with quantified impact] ### Areas for Growth 1. [Skill or behavior to develop] 2. [Skill or behavior to develop] ### Goals for Next Period 1. [Specific, measurable goal] 2. [Specific, measurable goal] ### Career Aspirations [Where I want to grow in the next 12-24 months] ``` ### Manager Assessment Template ```markdown ## Manager Assessment — [Employee Name] — [Review Period] ### Performance Summary **Overall Rating:** [Exceeds / Meets / Developing / Below] ### Key Accomplishments 1. [With business impact] 2. [With business impact] ### Strengths - [Strength with evidence] - [Strength with evidence] ### Development Areas - [Area with specific examples and improvement plan] - [Area with specific examples and improvement plan] ### Rating Justification [Evidence-based narrative — avoid recency bias, include full period] ### Compensation Recommendation - Merit increase: [X]% - Promotion: [Yes/No — if yes, to what level] - Equity refresh: [Yes/No — amount] ``` ### Calibration Process | Step | Action | Participants | |------|--------|-------------| | 1 | Managers submit initial ratings | Direct managers | | 2 | Pre-calibration: review distribution | HR Business Partner | | 3 | Calibration session: discuss outliers | Manager peers + skip-level | | 4 | Adjust ratings based on cross-team view | Managers | | 5 | Final approval | Department head | | 6 | Deliver reviews to employees | Direct managers | **Rating Distribution Guidance (avoid forced ranking):** | Rating | Target Distribution | Notes | |--------|-------------------|-------| | Exceeds Expectations | 15-20% | Truly exceptional, not just "good" | | Meets Expectations | 60-70% | Solid performance at level | | Developing | 10-15% | New to role or specific growth areas | | Below Expectations | 5-10% | Requires performance improvement plan | --- ## Employee Onboarding Checklist ### Pre-Start (Before Day 1) - [ ] IT equipment ordered and configured (laptop, monitors, peripherals) - [ ] Software accounts provisioned (email, Slack, GitHub, HRIS, etc.) - [ ] Building access / badge arranged - [ ] Welcome email sent with Day 1 logistics - [ ] Manager prep: 30/60/90 plan drafted, buddy assigned - [ ] Onboarding calendar populated (orientation, training, 1:1s) ### Week 1: Orientation - [ ] HR orientation (benefits enrollment, policies, compliance training) - [ ] Manager 1:1: goals, expectations, communication preferences - [ ] Team introductions and stakeholder meetings - [ ] Buddy assigned and first buddy check-in - [ ] Dev environment / tooling setup (engineering roles) - [ ] Review team norms, rituals, and documentation ### Day 30: Foundation - [ ] Completed all required compliance training - [ ] Attended at least one cross-functional meeting - [ ] Delivered first small contribution (PR, analysis, design, etc.) - [ ] Manager 1:1 review: progress check, blockers, feedback - [ ] 30-day survey: onboarding experience feedback ### Day 60: Contribution - [ ] Independently handling core responsibilities - [ ] Building relationships beyond immediate team - [ ] Participated in team planning/sprint activities - [ ] Manager 1:1: development conversation, skill gaps identified - [ ] Buddy check-in: social integration and cultural acclimation ### Day 90: Integration - [ ] Fully productive at expected level for tenure - [ ] Probation review completed (if applicable) - [ ] Manager 1:1: formal 90-day review, goal-setting for next quarter - [ ] 90-day survey: onboarding effectiveness - [ ] Onboarding formally concluded — transition to steady-state 1:1 cadence --- ## HR Metrics Framework | Metric | Formula | Benchmark | Frequency | |--------|---------|-----------|-----------| | **Attrition Rate** | Departures / Avg headcount x 100 | <15% annual (tech) | Monthly | | **Regrettable Turnover** | High-performer departures / Total departures | <30% of total attrition | Quarterly | | **eNPS** | % Promoters - % Detractors | >30 = good, >50 = excellent | Quarterly | | **Offer Acceptance Rate** | Accepted / Extended x 100 | >85% | Monthly | | **Time-to-Fill** | Avg days from req open to accepted | 30-45 days | Monthly | | **Cost-per-Hire** | Total recruiting spend / Hires | $3-5K IC, $10-20K senior | Quarterly | | **Span of Control** | Direct reports per manager | 5-8 (IC teams), 3-5 (manager of managers) | Annually | | **Diversity** | % representation by dimension | Set org-specific targets | Quarterly | --- ## Common Mistakes - **Compensation decisions without market data** — internal perception of "fair pay" often diverges from market reality; always benchmark - **Performance reviews without clear criteria** — vague criteria lead to bias; use rubrics tied to level expectations - **Onboarding that ends after Day 1** — orientation is not onboarding; the 30/60/90 framework is the minimum - **Hiring pipeline without source attribution** — if you don't know which sources produce the best hires, you can't optimize - **Forced ranking** — forces managers to label good performers as poor; use guided distribution instead - **Ignoring span of control** — managers with 15+ reports cannot coach effectively; restructure before it becomes a retention issue --- ## Additional Resources - Related skill: `brainstorm-okrs` (goal-setting alignment for performance reviews) - Radford / Pave / Levels.fyi — compensation benchmarking data - SHRM — HR operations best practices