# Deep Research Skills in AI Berkshire: Management Deep-Dives and Company Analysis > Explore AI Berkshire's deep research skills: Management Deep-Dive and Deep-Company Series. Generate citation-rich reports for investment investigations and gain in-depth company analysis. - Repository: [Xbt Lin/ai-berkshire](https://github.com/xbtlin/ai-berkshire) - Tags: deep-dive - Published: 2026-07-29 --- **AI Berkshire provides two specialized deep research skills—the Management Deep-Dive and the Deep-Company Series—that generate long-form, citation-rich reports for multi-day investment investigations.** AI Berkshire is an open-source investment research framework designed for rigorous company analysis. Unlike standard screening tools, its **deep research skills** conduct comprehensive investigations into management quality and business models, outputting structured markdown reports suitable for institutional-grade due diligence. ## What Are Deep Research Skills in AI Berkshire? Deep research skills differ fundamentally from quick-look screening capabilities. According to the canonical definitions in [`skills/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/management-deep-dive.md) and [`skills/deep-company-series.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/deep-company-series.md), these skills execute multi-day investigation workflows with explicit scoring methodologies and strict output formats. They require specific slash-command triggers and produce deliverables including composite scoring models, cross-chapter consistency checks, and series indexes. ## Available Deep Research Skills ### Management Deep-Dive Skill The **Management Deep-Dive** skill performs a longitudinal assessment of company leadership based on the principle that "buying stocks means buying people" (买股票就是买人). Triggered via the command `/management-deep-dive [ ]`, this skill produces a multi-section markdown report saved to `reports/[Company]-management-[YYYYMMDD].md`. The output includes: - Key management personnel tables - Promise-versus-fulfillment tracking matrices - Capital allocation records (M&A, buybacks, dividends, new ventures) - Governance structure assessments (equity structure, compensation, related-party transactions) - Side-channel verification (Glassdoor ratings, customer reviews) - Composite scoring model weighted as: Integrity (35%), Strategy (25%), Capital Allocation (25%), Governance (15%) The skill internally calls `tools/financial_rigor.py verify-valuation` to validate valuation assumptions during the analysis. ### Deep-Company Series Skill The **Deep-Company Series** skill generates a comprehensive 3-8 article series titled "Understanding X" (看懂X), covering company panoramas, economic moats, profit engines, hidden assets, AI variables, financials, management, and investment decisions. Triggered via `/deep-company-series `, the skill creates a dedicated folder structure at `reports/[Company]/《看懂[Company]》/` containing sequentially numbered markdown files: - `01-开篇-认识[Company].md` – Opening chapter establishing company context - `07-管理层-买人三问.md` – Management evaluation using the "Three Questions" framework - `08-决策-估值三情景.md` – Investment decision scenarios with three valuation contexts Each article follows a strict editorial skeleton requiring head-quote blocks, narrative hooks, key-point recaps, next-chapter previews, and legal disclaimers. The skill generates a series index file `00-系列说明.md` (not published) and enforces cross-chapter consistency checks for terminology, figures, and citations before final release. ## Source Files and Implementation The deep research capabilities are defined across multiple canonical locations in the xbtlin/ai-berkshire repository: - [`skills/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/management-deep-dive.md) – Canonical workflow definition including investigation steps, scoring tables, and governance evaluation criteria - [`skills/deep-company-series.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/deep-company-series.md) – Canonical definition for the article series workflow, chapter templates, and writing standards - [`codex-skills/management-deep-dive/SKILL.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-skills/management-deep-dive/SKILL.md) – Auto-generated Codex wrapper for GitHub Copilot integration - [`codex-skills/deep-company-series/SKILL.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-skills/deep-company-series/SKILL.md) – Auto-generated Codex wrapper mirroring the series workflow - [`codex-prompts/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-prompts/management-deep-dive.md) and [`codex-prompts/deep-company-series.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-prompts/deep-company-series.md) – Slash-command prompt layer definitions The public command reference in [`README.md`](https://github.com/xbtlin/ai-berkshire/blob/main/README.md) lists both `/management-deep-dive` and `/deep-company-series` as available deep-research triggers. ## Summary - AI Berkshire offers two distinct **deep research skills**: **Management Deep-Dive** and **Deep-Company Series**. - **Management Deep-Dive** evaluates leadership across four weighted dimensions, generating timestamped markdown reports with composite governance scores and capital allocation histories. - **Deep-Company Series** produces structured 3-8 article investigations with enforced consistency checks, standardized editorial frameworks, and non-published series indexes. - Both skills are defined in `skills/` with Codex-compatible wrappers in `codex-skills/` and prompt integrations in `codex-prompts/`. - These tools target multi-day research workflows rather than rapid screening, as implemented in the xbtlin/ai-berkshire framework. ## Frequently Asked Questions ### What is the difference between deep research skills and standard skills in AI Berkshire? Standard skills perform quick screening and checklist tasks, while deep research skills conduct multi-day investigations generating long-form, citation-rich output. The deep research capabilities specifically target management assessment and comprehensive business model analysis through structured methodologies defined in [`skills/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/management-deep-dive.md) and [`skills/deep-company-series.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/deep-company-series.md). ### How do I run a management deep-dive analysis? Execute the slash command `/management-deep-dive ` to trigger the skill. The system generates a report at `reports/[Company]-management-[Date].md` containing management scoring tables, capital allocation histories, and governance assessments using the composite weighting model (Integrity 35%, Strategy 25%, Capital Allocation 25%, Governance 15%). ### What outputs does the deep-company series skill create? The skill creates a folder structure at `reports/[Company]/《看懂[Company]》/` containing 3-8 markdown files following the "Understanding X" series format. Each article follows a strict skeleton with head-quotes, narrative hooks, and cross-references, plus a non-published index file `00-系列说明.md` that maintains series continuity and enforces terminology consistency across chapters. ### Where are the deep research skill definitions stored in the repository? Canonical definitions reside in [`skills/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/management-deep-dive.md) and [`skills/deep-company-series.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/deep-company-series.md). Auto-generated Codex-compatible wrappers exist in [`codex-skills/management-deep-dive/SKILL.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-skills/management-deep-dive/SKILL.md) and [`codex-skills/deep-company-series/SKILL.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-skills/deep-company-series/SKILL.md), with prompt integrations located in [`codex-prompts/management-deep-dive.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-prompts/management-deep-dive.md) and [`codex-prompts/deep-company-series.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-prompts/deep-company-series.md).