How to Package Your Industry Expertise into an AI Skill for Knowledge Monetization

Hello, I’m Fengyun. Last month I bundled the insights from over 90 public‑account articles I wrote into a Skill called wechat-article-writer-v2. After testing, the AI produced articles that sounded exactly like my own writing.

1. What Is a Skill?

A Skill is a specialized app for AI, similar to how installing an app on a phone adds focused functionality. Without a Skill, an AI is like a bright intern without training; with a Skill, it becomes a proficient worker following a detailed handbook.

A Skill consists of a folder with a SKILL.md configuration file and optional subfolders for scripts, assets, and reference materials.

my-skill/
├── SKILL.md   # skill definition (name, description, trigger)
├── references/   # domain knowledge files
│   └── template.md   # output template
├── scripts/   # optional execution scripts
└── assets/   # optional templates and media

2. Which Experience Is Worth Packaging?

Not every piece of knowledge should become a Skill. I learned this after trying to store scattered prompts as notes, which quickly became unmanageable. I now use four criteria; meeting any one means the experience is ready for a Skill:

Same instruction issued more than three times (repetitive work).

Output format varies each time (needs a fixed template).

Prompt length exceeds 200 characters (consumes too many tokens).

Multiple team members perform the same task (needs standardization).

For example, when writing my public‑account articles I repeatedly tell the AI to use first‑person narration, add life‑related analogies, avoid “first/second/last”, and vary paragraph length—over 300 characters each time. Packaging these rules into a Skill lets me invoke them with a single command:

@wechat-article-writer-v2 Write a practical article about Claude Code

3. Six‑Step No‑Code Creation Process

Step 1: Clarify Three Things

Problem to solve – e.g., “Make the AI write articles in my personal style”.

Trigger keyword – short, memorable, e.g., “public‑account article ‘Fengyun style’”.

Output standards – fixed layout, sections, tone (first‑person, conversational, include analogies, forbid AI‑like phrasing).

Step 2: Create the Skill in WorkBuddy

Open WorkBuddy → Skills → Add Skill → Create Custom Skill, then fill the basic fields:

Skill name : short English name, e.g., weekly-report.

Description : one sentence of what it does, e.g., “Check public‑account articles for typos, sensitive words, and formatting”.

Trigger keywords : 2‑3 phrases, e.g., “review” or “public‑account review”.

Step 3: Write SKILL.md

This file is the AI’s training handbook. My version contains five sections:

Overview – purpose of the Skill.

Core Principles – three iron‑clad rules ordered by priority.

Workflow – step‑by‑step actions and linked reference files.

Reference Index – list of the seven supporting documents.

Precautions – forbid fabricating material or distorting facts.

A minimal starter can be a single prompt block, for example:

You are a professional public‑account editor. The user provides article content; you must check for typos, sensitive words, formatting, and title appeal, then output three sections: Overall Evaluation, Issue List, Optimization Suggestions.

Step 4: Prepare Reference Files (Strongly Recommended)

Adding domain‑specific reference files lets the AI “look up” material instead of relying solely on prompt comprehension, dramatically improving accuracy.

references/
├── author-profile.md      # personal background, catchphrases, quotes
├── writing-style-guide.md # detailed style rules (intro, structure, conclusion, diction)
├── reusable-materials.md # 16 analogies, 25+ quotes, 9 experience snippets
├── article-templates.md   # six article structure templates
├── knowledge-system.md    # knowledge‑map overview
├── anti-ai-writing-guide.md # guide to evade AI detectors
└── selfmedia-playbook.md  # title formulas, prohibited words, layout tips

Step 5: Test and Refine

I iterated the Skill five times. The first version sounded too “AI‑like”; I added a blacklist of prohibited words. The second matched the style but was dry, so I enriched the material library. The third had rich material but overly regular structure, prompting me to adjust paragraph‑length rules. After the fifth revision the output finally felt authentic.

Step 6: Publish

Two publishing paths:

SkillHub – fill front‑matter (version, category, platforms, license), add an icon, submit for review, then users can discover and install it.

Team Sharing – zip the Skill folder and distribute to colleagues, or place it in {workspace}/.workbuddy/skills/ for project‑wide access.

4. How to Monetize a Skill

Three main routes:

SkillHub revenue share – earnings depend on platform policy; the more essential and niche the problem solved, the higher the usage.

Knowledge‑paid funnel – publish the creation process as an article (like this one) to attract AI‑plus‑media enthusiasts, then guide them to follow your public account, join your community, and purchase your courses. The Skill itself may be free, but the underlying knowledge system is sold.

Enterprise customization – build bespoke Skills for companies (e.g., a law‑firm contract‑review Skill or a hospital medical‑record‑organizing Skill) and charge project fees.

5. Common Pitfalls

Insufficient material → AI‑like output : Early versions used only style rules, resulting in fake‑sounding text. Adding real anecdotes, analogies, and quotes made the output lively.

Too many reference files → slow generation and high token cost : I created seven files, causing high token consumption. Adding an “on‑demand load” mechanism in SKILL.md reduced token usage by about one‑third.

Neglecting security checks : Importing a third‑party Skill once introduced a script that read ~/.ssh. WorkBuddy’s security scanner flagged it as a P0 risk. Since then I always review code, reject P0, verify P1, and trust P2.

6. Who Should Try This?

Anyone with deep, hard‑to‑copy industry experience can benefit—finance professionals, HR specialists, e‑commerce sellers, etc. Their tacit knowledge, once structured into a Skill, becomes a scalable service that AI can deliver to many users.

Start now; the best time was ten years ago, the second‑best time is today.