comp 分析
- 作者仓库星标 19,014
- 作者仓库 knowledge-work-plugins
/comp-analysis
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Analyze compensation data for benchmarking, band placement, and planning. Helps benchmark compensation against market data for hiring, retention, and equity planning.
Usage
/comp-analysis $ARGUMENTS
What I Need From You
Option A: Single role analysis "What should we pay a Senior Software Engineer in SF?"
Option B: Upload comp data Upload a CSV or paste your comp bands. I'll analyze placement, identify outliers, and compare to market.
Option C: Equity modeling "Model a refresh grant of 10K shares over 4 years at a $50 stock price."
Compensation Framework
Components of Total Compensation
- Base salary: Cash compensation
- Equity: RSUs, stock options, or other equity
- Bonus: Annual target bonus, signing bonus
- Benefits: Health, retirement, perks (harder to quantify)
Key Variables
- Role: Function and specialization
- Level: IC levels, management levels
- Location: Geographic pay adjustments
- Company stage: Startup vs. growth vs. public
- Industry: Tech vs. finance vs. healthcare
Data Sources
- With ~~compensation data: Pull verified benchmarks
- Without: Use web research, public salary data, and user-provided context
- Always note data freshness and source limitations
Output
Provide percentile bands (25th, 50th, 75th, 90th) for base, equity, and total comp. Include location adjustments and company-stage context.
## Compensation Analysis: [Role/Scope]
### Market Benchmarks
| Percentile | Base | Equity | Total Comp |
|------------|------|--------|------------|
| 25th | $[X] | $[X] | $[X] |
| 50th | $[X] | $[X] | $[X] |
| 75th | $[X] | $[X] | $[X] |
| 90th | $[X] | $[X] | $[X] |
**Sources:** [Web research, compensation data tools, or user-provided data]
### Band Analysis (if data provided)
| Employee | Current Base | Band Min | Band Mid | Band Max | Position |
|----------|-------------|----------|----------|----------|----------|
| [Name] | $[X] | $[X] | $[X] | $[X] | [Below/At/Above] |
### Recommendations
- [Specific compensation recommendations]
- [Equity considerations]
- [Retention risks if applicable]
If Connectors Available
If ~~compensation data is connected:
- Pull verified market benchmarks by role, level, and location
- Compare your bands against real-time market data
If ~~HRIS is connected:
- Pull current employee comp data for band analysis
- Identify outliers and retention risks automatically
Tips
- Location matters — Always specify location for benchmarking. SF vs. Austin vs. London are very different.
- Total comp, not just base — Include equity, bonus, and benefits for a complete picture.
- Keep data confidential — Comp data is sensitive. Results stay in your conversation.
- 流狐分类
- 数据
- 作者声明 Agent
- 未找到明确声明;不据此推断已兼容或已测试
- 静态检查
- 88 / 100 · 启发式扫描,不代表运行安全
- 作者 / 版本 / 许可
- @anthropics · 未声明 license
- 流狐 Token 估算
- 低消耗
- 流狐接入估算
- 即装即用
- 是否需要外部 API Key
- 未发现要求
- 检测到的系统要求
- 未声明
- 底层运行要求
- 未声明
- 检测到的文件与系统行为
-
- 只读
- 检测到的网络行为
- 仅限本地
- 安装命令数
- 无(仅作为资料)
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
作者没有在当前 SKILL.md 中定义固定输出样例。 Usage
Option A: Single role analysis "What should we pay a Senior Software Engineer in SF?" Option B: Upload comp data
Compensation Framework
Base salary: Cash compensation Equity: RSUs, stock options, or other equity Bonus: Annual target bonus, signing bonus
Role: Function and specialization Level: IC levels, management levels Location: Geographic pay adjustments
With ~~compensation data: Pull verified benchmarks Without: Use web research, public salary data, and user-provided context Always note data freshness and source limitations
# /comp-analysis
> If you see unfamiliar placeholders or need to check which tools are connected, see [CONNECTORS.md](../../CONNECTORS.md).
Analyze compensation data for benchmarking, band placement, and planning. Helps benchmark compensation against market data for hiring, retention, and equity planning.
## Usage
```
/comp-analysis $ARGUMENTS
```
## What I Need From You
**Option A: Single role analysis**
"What should we pay a Senior Software Engineer in SF?"
**Option B: Upload comp data**
Upload a CSV or paste your comp bands. I'll analyze placement, identify outliers, and compare to market.
**Option C: Equity modeling**
"Model a refresh grant of 10K shares over 4 years at a $50 stock price."
## Compensation Framework
### Components of Total Compensation
- **Base salary**: Cash compensation
- **Equity**: RSUs, stock options, or other equity
- **Bonus**: Annual target bonus, signing bonus
- **Benefits**: Health, retirement, perks (harder to quantify)
### Key Variables
- **Role**: Function and specialization
- **Level**: IC levels, management levels
- **Location**: Geographic pay adjustments
- **Company stage**: Startup vs. growth vs. public
- **Industry**: Tech vs. finance vs. healthcare
### Data Sources
- **With ~~compensation data**: Pull verified benchmarks
- **Without**: Use web research, public salary data, and user-provided context
- Always note data freshness and source limitations
## Output
Provide percentile bands (25th, 50th, 75th, 90th) for base, equity, and total comp. Include location adjustments and company-stage context.
```markdown
## Compensation Analysis: [Role/Scope]
### Market Benchmarks
| Percentile | Base | Equity | Total Comp |
|------------|------|--------|------------|
| 25th | $[X] | $[X] | $[X] |
| 50th | $[X] | $[X] | $[X] |
… 作者原文负责流程事实;流狐只索引当前章节、要点、文件与命令。
章节 -> Usage → What I Need From You → Compensation Framework → Components of Total Compensation → Key Variables → Data Sources
要点 -> Option A: Single role analysis · Option B: Upload comp data · Option C: Equity modeling · Base salary · Equity · Bonus · Benefits · Role
文件/命令 -> CONNECTORS.md · ../../CONNECTORS.md · Role/Scope · Below/At/Above
内容 SHA-256 -> 5d1a317036c2
原文结构
适用与边界
原文中的明确线索
CONNECTORS.md、../../CONNECTORS.md、Role/Scope、Below/At/Above