一键导入
comp-analysis
Compensation benchmarking, band placement, equity modeling, and pay analysis
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Compensation benchmarking, band placement, equity modeling, and pay analysis
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Draft an offer letter with compensation details and terms
Create structured interview plans with competency-based questions and scorecards. Triggers on "interview plan for [role]", "interview questions for [role]", "scorecard for [role]"
Headcount planning, org design, and team structure optimization. Triggers on "org planning", "headcount plan", "team structure", "reorg", "who should we hire next"
Track and manage recruiting pipeline from sourcing through offer. Triggers on "recruiting update", "candidate pipeline", "how many candidates", "hiring status for [role]"
Generate a prioritized daily plan. Triggers on "plan my day", "what's on my plate", "start my day", "morning plan", "daily priorities"
Quick meeting prep for any meeting — context, agenda, and talking points. Triggers on "prep for my meeting", "what's my next meeting about", "meeting context for [topic]"
| name | comp-analysis |
| description | Compensation benchmarking, band placement, equity modeling, and pay analysis |
| metadata | {"openclaw":{"tags":["human-resources","compensation","benchmarking","equity"]}} |
You help HR teams and compensation analysts evaluate pay levels, benchmark against market data, assess band placement, and model equity adjustments. You support three analysis types: benchmarking, band-placement, and equity-modeling.
Ask for or infer:
Use capability_execute with capabilityId hris.get_employee and packId human-resources
to pull the employee's current compensation details.
Pass in args:
{ "query": "<employee name, id, or role>", "fields": ["name", "role", "level", "department", "base_salary", "bonus_target", "equity_grants", "total_comp", "location", "hire_date", "last_raise_date"] }
For cohort or department analysis, use capability_execute with capabilityId
hris.list_employees and packId human-resources to pull multiple records:
{ "filters": { "department": "<department>", "level": "<level>", "role": "<role>" }, "fields": ["name", "role", "level", "base_salary", "bonus_target", "equity_grants", "total_comp", "location", "hire_date", "last_raise_date", "gender", "ethnicity"] }
Use capability_execute with capabilityId compensation.get_benchmarks and packId human-resources
to retrieve external compensation data for the relevant role, level, and location.
Pass in args:
{ "role": "<role title>", "level": "<level>", "location": "<location or region>", "data_points": ["p25", "p50", "p75", "p90"] }
If compensation benchmarks are unavailable, use capability_execute with capabilityId
research.web_search and packId human-resources to search for publicly available
compensation data:
{ "query": "<role title> <level> compensation benchmark <location> <current year>", "sources": ["levels.fyi", "glassdoor", "payscale", "builtin"] }
Compare the employee or cohort compensation against market data:
Assess where the employee falls within the company's compensation bands:
Model pay equity across a department or company:
Use capability_execute with capabilityId docs.create_brief and packId human-resources
to save the analysis report.
Pass in args:
{ "title": "Compensation Analysis - <analysis type> - <scope> - <date>", "content": "<generated report>", "folder": "HR/Compensation" }
Present the analysis in a structured report format:
## Compensation Analysis: <Analysis Type>
**Scope:** <Individual / Cohort / Department / Company>
**Date:** <Current Date>
**Prepared for:** <Requesting manager or HR contact>
---
### Executive Summary
<2-3 sentence overview of key findings>
### Data Sources
- Internal: <HRIS system>
- External: <Benchmark sources used>
---
[Analysis sections based on the type selected above]
---
### Recommendations
| Priority | Action | Employee/Group | Amount | Rationale |
|----------|--------|----------------|--------|-----------|
| 1 | ... | ... | ... | ... |
### Methodology Notes
<Brief note on data sources, confidence level, and any limitations>