What Is the dyp-ask Skill and How Does It Simulate Duan Yongping’s Thinking?

The dyp-ask skill is a specialized Claude-Code slash command that injects a Duan Yongping persona into a large language model, forcing structured, value-investing reasoning through a predefined prompt template stored in skills/dyp-ask.md.

The dyp-ask skill is implemented in the open-source xbtlin/ai-berkshire repository as a reproducible workflow for emulating the investment mindset of Duan Yongping (DYP), the Chinese entrepreneur and value investor renowned for his disciplined fundamental analysis. By codifying DYP’s decision heuristics into a machine-readable prompt template, the repository lets users invoke institutional-grade value investing logic via natural language queries.

Architectural Overview of the dyp-ask Skill

The implementation spans three core artifacts that separate the prompt definition from the execution runtime:

• skills/dyp-ask.md – The authoritative source definition for the Claude-Code slash command. This file declares the persona prompt, required parameter schema, and the transformation logic that converts user queries into DYP-style responses.
• codex-prompts/dyp-ask.md – An auto-generated, Codex-compatible mirror of the skill definition. This artifact ensures that environments without Claude-Code can access identical behavior through a standard OpenAI-style completion API.
• scripts/sync-codex-skills.py – The synchronization engine that regenerates the Codex prompt whenever the source definition in skills/dyp-ask.md changes, guaranteeing a single source of truth across both runtimes.

How the dyp-ask Skill Simulates Duan Yongping’s Thinking

The simulation relies on four deliberate design choices that bias the model toward DYP’s documented investment philosophy.

Persona Injection

The prompt template in skills/dyp-ask.md explicitly instructs the LLM to adopt the voice and perspective of Duan Yongping. By prefixing the system context with “You are Duan Yongping, a disciplined value investor…”, the skill anchors the model’s output to DYP’s characteristic vocabulary and conservative temperament, suppressing generic speculative advice.

Focused Decision Framework

Embedded within the template is DYP’s classic investment checklist: valuation, cash-flow sustainability, and competitive advantage (moats). When processing a query, the model evaluates the target company through these specific lenses rather than applying broad technical analysis or momentum-based metrics.

Iterative Reasoning

The skill enforces a step-by-step analytical workflow by expanding the user’s question into a series of sub-queries. The prompt asks the model to sequentially determine intrinsic value, calculate margin-of-safety buffers, and stress-test competitive positioning—mirroring the methodical due diligence DYP applies to Berkshire Hathaway-style holdings.

Structured Result Formatting

Final outputs are rendered in structured markdown tables that mimic the format of DYP’s published research notes. This normalization makes the generated analysis machine-readable for downstream automation, such as populating investment memos or risk dashboards.

Implementation Details and Code Examples

Users can trigger the skill through either the Claude-Code CLI or a direct Codex API call. Both paths ultimately resolve to the same underlying template in skills/dyp-ask.md.

Invoke the skill inside a Claude-Code session:

/ask dyp-ask "Evaluate the investment case for Kuaishou Technology (1024.HK)."

Example response structure:

> **Response (as Duan Yongping)**  
- **Intrinsic Value:** ¥110 / share  
- **Margin of Safety:** 20 % (current price ¥88)  
- **Key Moats:** Network effects, strong cash-flow generation, expanding overseas user base.  
- **Recommendation:** BUY – aligns with DYP’s long-term growth thesis.

For programmatic access via the Codex runtime, send a POST request to the generated prompt:

curl -X POST https://api.codex.ai/v1/execute \
  -H "Authorization: Bearer <YOUR_TOKEN>" \
  -d '{
        "prompt_id": "dyp-ask",
        "variables": {"question":"Is Tesla a good long-term hold for a value investor?"}
      }'

After any edit to skills/dyp-ask.md, the maintainer runs python3 scripts/sync-codex-skills.py to regenerate codex-prompts/dyp-ask.md, ensuring that both invocation methods remain bitwise consistent.

Summary

• The dyp-ask skill is defined in skills/dyp-ask.md as a Claude-Code slash command that simulates Duan Yongping’s value-investing methodology.
• A synchronization script, scripts/sync-codex-skills.py, keeps the Codex-compatible version in codex-prompts/dyp-ask.md identical to the source.
• The skill uses persona injection and a focused decision framework to constrain the LLM to fundamental analysis, margin-of-safety calculations, and moat evaluation.
• Outputs are formatted as structured markdown tables suitable for automated investment research pipelines.

Frequently Asked Questions

What file contains the official definition of the dyp-ask skill?

The canonical definition lives in skills/dyp-ask.md at the repository root. This markdown file contains the system prompt, parameter schema, and logic required by the Claude-Code runtime. A derivative copy is auto-generated at codex-prompts/dyp-ask.md for API compatibility.

How does the repository keep Claude-Code and Codex prompts synchronized?

The Python utility scripts/sync-codex-skills.py parses the source definitions under skills/ and regenerates the Codex-compatible versions under codex-prompts/. Running this script after any edit ensures that both execution paths reference the same Duan Yongping persona and investment checklist.

Can I use the dyp-ask skill outside of Claude-Code?

Yes. While the slash-command syntax (/ask dyp-ask) is specific to Claude-Code, the codex-prompts/dyp-ask.md file exposes the same functionality as a standard completion prompt. Any HTTP client can call the Codex endpoint using the prompt ID dyp-ask to receive DYP-style analysis without the CLI.

What investment methodology does the dyp-ask skill follow?

The skill implements Berkshire Hathaway-style value investing as practiced by Duan Yongping. It emphasizes intrinsic value calculation, rigorous margin-of-safety requirements, and durable competitive advantages (moats), while explicitly excluding growth-at-any-price or technical trading heuristics.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}