# How the Management-Deep-Dive Skill Evaluates Corporate Leadership: An 8-Step Technical Breakdown

> Discover how the management-deep-dive skill evaluates corporate leadership using an 8-step technical breakdown. Assess executive integrity, strategic vision, and more for a comprehensive view.

- Repository: [Xbt Lin/ai-berkshire](https://github.com/xbtlin/ai-berkshire)
- Tags: deep-dive
- Published: 2026-07-03

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**The management-deep-dive skill evaluates corporate leadership through an eight-step data-driven workflow that assesses executive integrity, strategic vision, capital allocation discipline, and governance structure, culminating in a weighted composite score and star rating.**

The **management-deep-dive** skill in the `xbtlin/ai-berkshire` repository transforms raw public data into rigorous leadership assessments using a structured, parallelized workflow. Defined in [`skills/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/management-deep-dive.md), this tool mirrors institutional investment research processes to evaluate corporate management across multiple quantitative and qualitative dimensions.

## Architecture of the Management-Deep-Dive Skill

The skill operates as an orchestrated multi-agent system that gathers disparate data streams concurrently. According to the source code in [`skills/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/management-deep-dive.md), the workflow spans lines 25–170 and implements a **data-driven** methodology where every qualitative judgment maps to a table of sourced facts. The architecture supports parallel execution, allowing multiple agents to harvest executive statements, financial records, and side-channel feedback simultaneously. The repository’s overall agent architecture is documented in [`AGENTS.md`](https://github.com/xbtlin/ai-berkshire/blob/main/AGENTS.md), which explains how these skills sync with the Codex execution environment.

## The 8-Step Leadership Evaluation Workflow

### Step 1: Identify Key Executives and Parallel Data Collection

The workflow initiates with a **WebSearch** to identify CEOs, CFOs, founders, actual controllers, and senior managers. The system then spawns parallel agents to gather public statements, capital-allocation histories, governance disclosures, and side-channel intelligence (lines 25–44).

### Step 2: CEO Ability-Circle Evaluation

This phase splits into two critical components:
- **Strategic Vision**: Validates past forecasts against actual outcomes to assess predictive accuracy.
- **Execution Capability**: Measures delivery metrics, talent attraction success, crisis handling, and iteration speed (lines 45–68).

### Step 3: Integrity Assessment

The most critical evaluation tracks **promises versus delivery** through a commitment-fulfilment table. The system examines behavior during crises and evaluates attitudes toward shareholders, employees, customers, suppliers, and regulators (lines 70–112).

### Step 4: Capital-Allocation Ability

The skill catalogs M&A activity, share repurchases, dividends, and new-business investments. Each entry receives a 1–5 score and cross-checks against `tools/financial_rigor.py verify-valuation` for financial rigor (lines 116–154).

### Step 5: Governance Structure Review

This inspection covers equity structure (A-shares, super-voting rights, VIEs), board independence metrics, large-shareholder activity, and senior-executive compensation relative to profit performance (lines 159–176).

### Step 6: Side-Channel Validation

To triangulate the leadership narrative, the system pulls **employee sentiment** from Glassdoor and Zhihu, **customer/merchant reviews** from App Store and forums, and industry reputation data (lines 83–110).

### Step 7: Post-CEO Continuity Analysis

The evaluation asks whether the firm survives the CEO’s departure. It assesses management team depth, succession plan quality, and historic hand-over success (lines 113–122).

### Step 8: Report Generation and Final Scoring

The skill generates a markdown report at `reports/{company_name}-management-{YYYYMMDD}.md` applying weighted scores:
- **Integrity**: 35%
- **Ability**: 25%
- **Capital-Allocation**: 25%
- **Governance**: 15%

The final **"buy-person"** rule translates the composite score into a ★-rating (lines 124–170).

## Implementation: Invoking the Skill

Developers can trigger the workflow programmatically or via command-line interfaces.

```python

# Example: invoking the skill from a Python script using the Codex CLI

from codex import run_skill

# Evaluate the leadership of “美团”

result = run_skill(
    skill="management-deep-dive",
    arguments="美团"
)

print(result)   # prints the generated markdown report

```

Alternatively, use the slash command defined in [`codex-prompts/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-prompts/management-deep-dive.md):

```bash

# Example: using the Claude-compatible slash command in a chat interface

/management-deep-dive 美团

```

Both methods forward arguments to the underlying workflow defined in the markdown skill file.

## Summary

- The **management-deep-dive** skill in `xbtlin/ai-berkshire` implements an eight-step parallel workflow to evaluate corporate leadership.
- **Integrity assessment** carries the highest weight (35%) and tracks promises versus delivery through sourced fact tables.
- **Capital-allocation** decisions are scored 1–5 and validated using `tools/financial_rigor.py verify-valuation`.
- The workflow generates timestamped markdown reports with weighted composite scores and star ratings.
- Invocations are supported via Python `run_skill()` API or the `/management-deep-dive` slash command.

## Frequently Asked Questions

### What is the primary source file for the management-deep-dive skill?

The complete workflow specification resides in [`skills/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/management-deep-dive.md) within the `xbtlin/ai-berkshire` repository. This file defines all eight evaluation steps, scoring weights, and output formats. A minimal wrapper exposing the skill as a slash command exists in [`codex-prompts/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-prompts/management-deep-dive.md).

### How does the skill weight different leadership criteria?

The final composite score applies specific weights: **integrity** at 35%, **ability** at 25%, **capital-allocation** at 25%, and **governance** at 15%. These weightings reflect the AI Berkshire team's emphasis on management integrity as the primary determinant of long-term investment quality.

### What tool validates the financial assumptions in capital-allocation analysis?

The skill calls `tools/financial_rigor.py verify-valuation` to cross-check and validate financial assumptions underlying M&A decisions, share repurchases, and investment moves. This ensures quantitative rigor in the 1–5 scoring of capital allocation decisions.

### Can the workflow evaluate private companies or only public entities?

While the source code demonstrates evaluation of public companies like "美团" (Meituan), the architecture relies on **WebSearch** and public data sources (Glassdoor, App Store, regulatory filings). The framework can theoretically assess any entity with sufficient public digital footprint, though data availability determines output quality.