comp-analysis

/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.

Lark-native execution (depth core: LARK-PATTERNS, LARK-RECIPES, LARK-FUSION). Verified market benchmarks come from the specialty ~~compensation data external MCP (keep it as-is — no Lark equivalent). The collaboration layer is Lark: hold comp bands and per-employee placement in a Lark Base as system-of-record (P5) — read with lark_base_search, write with lark_base_record_upsert; scaffold a new comp-band Base via base-deploy rather than hand-rolling. Pull current-employee comp from ~~HRIS (or its Base approximation). When the user uploads a CSV, land it via lark_drive_upload / lark_sheets_read. Surface the band-placement result and any outliers/retention risks as an interactive card (lark_im_card_send, P4), not a wall of text. Comp is sensitive — keep PII out of broad channels; resolve a single recipient with lark_contact_search (P1) and DM them.

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. (CSV → lark_drive_upload then lark_sheets_read with a jq projection, P3; or read an existing comp Base with lark_base_search — note lark_base_search does NOT support jq and REQUIRES search_fields; narrow with select_fields/limit and pass the field name(s) to match. If you don't know the field names, discover them first via lark_api GET /open-apis/bitable/v1/apps/{base}/tables/{table}/fields.)

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 (specialty external MCP) is connected:

• Pull verified market benchmarks by role, level, and location
• Compare your bands against real-time market data

If ~~HRIS (specialty external MCP, or its Lark Base approximation) is connected:

• Pull current employee comp data for band analysis
• Identify outliers and retention risks automatically

Lark-native: persist & share the result

• System-of-record (P5): keep comp bands + per-employee placement in a Lark Base. Read with lark_base_search — it does NOT support jq and REQUIRES search_fields; pass the field name(s) to match and narrow output with select_fields/limit (discover field names via lark_api GET /open-apis/bitable/v1/apps/{base}/tables/{table}/fields if unknown). Write/update each placement row with lark_base_record_upsert (dry_run: true first, P2). Don't have a comp Base yet? Scaffold one with base-deploy.
• Share securely (P1/P4): resolve the requesting manager with lark_contact_search → DM the band-placement summary + outliers/retention flags as an interactive card (lark_im_card_send, print_json: true then dry_run: true). Never broadcast comp to a group channel.
• For record/field/dashboard depth on the comp Base, delegate to the lark-base skill.

Tips

1. Location matters — Always specify location for benchmarking. SF vs. Austin vs. London are very different.
2. Total comp, not just base — Include equity, bonus, and benefits for a complete picture.
3. Keep data confidential — Comp data is sensitive. Results stay in your conversation.