Difference Between Industry-Research and Industry-Funnel Skills in AI-Berkshire

Industry‑Research performs a panoramic value‑chain scan of an entire industry using qualitative "Four Masters" analysis, while Industry‑Funnel runs a quantitative multi‑stage filter to narrow the market down to three specific target companies.

AI‑Berkshire implements its investment research workflow as discrete skills that users invoke via chat commands like /industry-research and /industry-funnel. Understanding the difference between industry‑research and industry‑funnel skills is essential for analysts who need to decide whether to map an entire sector or select specific securities from a crowded market.

Architectural Goals and Design Philosophy

Both skills belong to the investment‑research family defined in the skills/ directory, but they serve distinct analytical purposes.

Industry-Research: Panoramic Value-Chain Mapping

The industry-research skill aims to produce a panoramic value‑chain scan of an industry. According to the specification in skills/industry-research.md, this skill builds an industry‑wide map and applies the "Four Masters" framework (段永平, 巴菲特, 芒格, 李录) to each segment of the chain. It emphasizes qualitative segmentation and macro‑level risk assessment using Munger checklists and civilization trend analysis.

Industry-Funnel: Quantitative Multi-Stage Screening

In contrast, the industry-funnel skill—defined in skills/industry-funnel.md—implements a tiered filter‑funnel that narrows the entire market down to three final target companies. This skill emphasizes quantitative hard screens such as PE thresholds, ROE requirements, cash‑flow ratios, and debt‑to‑asset filters, complemented by structured moat scoring.

Workflow Execution Comparison

The operational pipelines differ significantly in their step‑by‑step execution.

Industry‑Research Workflow:

1. Build a logical investment chain for the specified industry.
2. Generate a full‑chain diagram visualizing the value flow.
3. Scan every listed public company within the sector.
4. Perform "Four Masters" deep‑dives on each segment‑leader.
5. Complete a risk checklist, civilization trend analysis, and portfolio suggestions.

Industry‑Funnel Workflow:

1. Define three market‑wide entry pools based on activity (活跃度), price change (涨幅), and market cap (市值).
2. Apply five hard value‑investment criteria: PE, ROE, cash flow (现金流), debt ratio (负债率), and competitive moat (护城河).
3. Conduct structured analysis for a maximum of ten companies passing the screen.
4. Execute "Four Masters" deep‑dives on the final three selections.
5. Output ETF alternatives, industry‑level positioning notes, and data‑audit steps.

Output Artifacts and Report Formats

Both skills generate markdown reports in the reports/ directory, but with different granularities.

• Industry‑Research generates an industry‑level report at reports/{行业}-industry-{date}.md, containing segment analyses, risk matrices, and portfolio allocations.
• Industry‑Funnel generates a company‑selection report at reports/{行业}-funnel-{date}.md, listing filtered candidates, inclusion/exclusion rationale, and deep‑dives on the final three companies.

Technical Implementation and Shared Infrastructure

Both skills are defined as canonical markdown files under the skills/ directory. The repository’s build script scripts/sync-codex-skills.py converts each source file into a Codex‑compatible description located at codex-skills/industry-research/SKILL.md and codex-skills/industry-funnel/SKILL.md, enabling both Claude‑Code and Codex users to invoke the workflows.

Shared infrastructure includes:

• tools/report_audit.py: A utility used by both skills to verify data quality.
• skills/financial-data.md: Provides data‑source guidelines leveraged by both pipelines.

Practical Usage Examples

Invoke these skills through the AI‑Berkshire chat interface or CLI:

# Map the entire nuclear power value chain

/industry-research 核电

Result: A markdown report reports/核电-industry-YYYYMMDD.md containing a sector‑wide chain diagram, segment‑by‑segment "Four Masters" analysis, and portfolio suggestions.

# Select top 3 AI computing stocks using quantitative filters

/industry-funnel AI算力

Result: A markdown report reports/AI算力-funnel-YYYYMMDD.md listing the initial 30‑60 candidates, the 5‑hard‑criteria screening results, structured analyses for the survivors, and a final three‑company deep‑dive.

Summary

• Industry‑Research conducts macro‑level qualitative mapping of entire value chains, ideal for understanding where value exists in an industry.
• Industry‑Funnel executes micro‑level quantitative filtering to identify specific securities, ideal for determining which companies merit investment.
• Both skills share common infrastructure like scripts/sync-codex-skills.py and tools/report_audit.py, but diverge in their primary output: industry reports versus company selection lists.
• Analysts should typically run Industry‑Research first to understand the sector landscape, followed by Industry‑Funnel to select specific targets.

Frequently Asked Questions

Which skill should I run first when analyzing a new industry?

Run industry‑research first. This skill provides the panoramic value‑chain scan necessary to understand segment dynamics and identify where value concentrates. Once you understand the industry structure, industry‑funnel can quantitatively filter for the best individual securities within that mapped landscape.

What are the "Four Masters" criteria referenced in both skills?

The "Four Masters" (段永平, 巴菲特, 芒格, 李录) represent a qualitative investment framework applied to deep‑dive analyses. While industry‑research applies this framework to every segment of the value chain, industry‑funnel applies it only to the final three companies surviving the quantitative screens, ensuring rigorous qualitative validation of quantitative winners.

How do the generated reports differ between the two skills?

industry‑research outputs reports/{行业}-industry-{date}.md, which contains an industry‑wide map, segment risk matrices, and broad portfolio allocations. industry‑funnel outputs reports/{行业}-funnel-{date}.md, which contains a filtered shortlist, hard‑criteria screening results, and deep‑dives on exactly three target companies. The former is strategic; the latter is tactical.

Can I modify the hard criteria in Industry-Funnel?

The five hard criteria (PE, ROE, cash flow, debt ratio, and moat) are defined in skills/industry-funnel.md as part of the skill specification. To modify these thresholds, you must edit the source markdown file or create a custom skill variant, then regenerate the Codex artifact using scripts/sync-codex-skills.py to apply the changes.

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