Core Components of the Zhangxuefeng-Skill Architecture: A Three-Layer Agent Skill Design

The Zhangxuefeng-skill architecture comprises three tightly coupled layers—a YAML manifest that defines the Agentic Protocol, a curated Markdown knowledge base containing mind models and heuristics, and an interaction layer with cross-runtime installation scripts.

The alchaincyf/zhangxuefeng-skill repository implements a self-contained Agent Skill that emulates Zhang Xuefeng's decision-making perspective on education and career planning. Designed to the Agent Skills protocol, this architecture separates concerns into a manifest layer, a knowledge base, and interaction assets, enabling deployment across 50+ compatible runtimes without code modification.

The Three-Layer Architecture

The Zhangxuefeng-skill architecture is deliberately simple yet expressive, consisting of three layers that handle runtime configuration, factual knowledge, and user interaction respectively.

1. Manifest and Runtime Glue (SKILL.md)

The SKILL.md file serves as the executable surface of the skill. It contains a YAML front-matter block that registers the skill name (zhangxuefeng-perspective), description, and runtime entry point.

• Agentic Protocol Definition: The manifest defines a step-wise workflow (classification → mandatory web search → model-driven response) that drives the agent's behavior
• Role-Play Rules: Specifies first-person voice requirements and NE-style tonal characteristics
• Failure-Mode Map: Documents recovery procedures when workflow steps are missed

When the skill loads, the runtime reads this markdown file and treats each heading as a callable routine, making the manifest both documentation and executable code.

2. Knowledge Base (references/research/)

The knowledge base layer contains six curated Markdown files that serve as the sole authoritative sources for the skill's responses:

• 01-writings.md — Primary source research from books and articles
• 02-conversations.md — Interview transcripts and dialogues
• 03-expression-dna.md — Sentence style, vocabulary, and pacing guidelines
• 04-external-views.md — Third-party perspectives and analyses
• 05-decisions.md — Documented decision frameworks and heuristics
• 06-timeline.md — Chronological events and milestones

These files contain the 5 core mind models, 8 decision heuristics, and the expression DNA that governs the skill's communication style. According to the Agentic Protocol implemented in SKILL.md, the skill must pull concrete data from these files after performing mandatory live web searches, ensuring every suggestion is grounded in both historical context and current facts.

The knowledge base is maintained separately from the logic layer; the Nuwa generator automatically updates these files, allowing the skill to evolve without modifying the manifest.

3. Interaction Layer (README.md, examples/, assets/)

The interaction layer provides the human-facing interface and installation infrastructure:

• Installation Scripts: The README.md documents the cross-runtime installation command npx skills add alchaincyf/zhangxuefeng-skill, which auto-detects the host runtime and copies the skill to the correct directory
• Example Conversations: examples/demo-conversation.md records full end-to-end dialogues (lines 37-61) demonstrating how the step-wise flow produces concrete answers
• Visual Assets: assets/hero.gif provides visual branding when the skill appears in registries

This layer ensures the skill is discoverable, installable, and demonstrable across all supported runtimes including Claude Code, Codex, Cursor, OpenClaw, and Hermes.

How the Agentic Protocol Works

The Zhangxuefeng-skill architecture enforces a data-first philosophy through its Agentic Protocol. The workflow requires:

1. Question Classification — Categorize the inquiry into education, career, or decision analysis
2. Mandatory Web Search — Fetch real-time data (employment rates, median salaries, admission scores) before generating responses
3. Model-Driven Response — Apply the mind models and heuristics from the knowledge base to the fresh data

This protocol ensures the skill never hallucinates facts; it must cite concrete data from the research files or freshly retrieved web sources before applying Zhang Xuefeng's analytical frameworks.

Installation and Runtime Compatibility

The architecture is runtime-agnostic, implementing the standard Agent Skills protocol that abstracts runtime-specific details.

# Install the skill with auto-detection

npx skills add alchaincyf/zhangxuefeng-skill

# Invoke from a compatible agent

agent --skill zhangxuefeng-perspective \
      "用张雪峰的视角帮我分析下 2026 年 AI 方向的就业前景"

The skill self-registers across 50+ supported runtimes because it relies solely on the protocol interface rather than runtime-specific APIs.

Summary

• The Zhangxuefeng-skill architecture separates concerns into three layers: the SKILL.md manifest defining the Agentic Protocol, the references/research/ knowledge base containing mind models and heuristics, and the interaction layer providing installation and examples.

• Data-first enforcement: The protocol mandates web searches and knowledge base lookups before model generation, preventing hallucinations.

• Runtime-agnostic design: Standard Agent Skills protocol compatibility enables deployment across Claude Code, Codex, Cursor, and 47+ other runtimes without modification.

• Self-documenting structure: Markdown files serve as both source code and documentation, with the Nuwa generator maintaining the knowledge base independently of logic changes.

Frequently Asked Questions

What is the Agent Skills protocol?

The Agent Skills protocol is a standardized interface that allows self-contained skills to register with compatible AI runtimes. According to the alchaincyf/zhangxuefeng-skill source code, this protocol requires only a YAML manifest and markdown content files, enabling the skill to run on any runtime that supports the npx skills add installation method.

How does the knowledge base stay current?

The knowledge base automatically updates through the Nuwa generator, which refreshes the six research files (01-writings.md through 06-timeline.md) with new primary sources and derived artefacts. Because the knowledge layer is decoupled from the manifest in SKILL.md, updates occur without touching the core workflow logic.

Which runtimes support this skill?

The architecture supports 50+ runtimes including Claude Code, Codex, Cursor, OpenClaw, and Hermes. The skill achieves this compatibility by implementing the standard Agent Skills protocol rather than runtime-specific APIs, making it truly portable across different agent environments.

Can I modify the role-play rules?

Yes. The role-play rules, including voice characteristics and tonal requirements, are defined in the SKILL.md file under the manifest section. Because this is plain markdown with YAML front-matter, you can edit the first-person voice settings and NE-style tone parameters directly without recompiling code.

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