Add 03-skills presentation: Skills for AI agents
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03-skills/presentation.md
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03-skills/presentation.md
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Skills: Teaching AI How to Think
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Lazy-loaded expertise for efficient, reliable agents
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<!-- speaker_note: Title slide. Core message: skills make agents both smarter AND cheaper to run. -->
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The Problem
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===
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You have two bad options:
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**Option A: Stuff everything into the system prompt**
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- 🪣 20,000+ tokens of instructions, always loaded
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- 🔇 Context pollution degrades *all* tasks
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- 💸 You pay for expertise you're not using
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**Option B: Wing it**
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- 🎲 Agent improvises on critical tasks
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- 🔀 Inconsistent results every time
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- 😬 "Creative" solutions in production
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Neither is acceptable.
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===
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<!-- speaker_note: Set up the tension. Everyone building agents hits this wall. -->
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What is a Skill?
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===
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```mermaid +render +width:100%
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graph TD
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S["🎯 Skill"] --> MD["📋 SKILL.md<br/>Instructions, rules, edge cases"]
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S --> SC["⚙️ scripts/<br/>Helper scripts"]
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S --> TM["📄 templates/<br/>Output templates"]
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S --> AS["📦 assets/<br/>Supporting files"]
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style MD fill:#4a9eff,stroke:#333,color:#fff
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style S fill:#ff6b6b,stroke:#333,color:#fff
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style SC fill:#51cf66,stroke:#333,color:#fff
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style TM fill:#51cf66,stroke:#333,color:#fff
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style AS fill:#51cf66,stroke:#333,color:#fff
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```
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**SKILL.md is the brain. Everything else is optional.**
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<!-- speaker_note: The SKILL.md IS the SOP. Scripts and templates are scaffolding. -->
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Lazy Loading
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===
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How it works: scan descriptions → load on demand → unload when done
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```mermaid +render +width:100%
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graph LR
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subgraph BEFORE["❌ Without Skills"]
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direction TB
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BP["System Prompt<br/>20,000+ tokens"]
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BP --> W1["Weather SOPs"]
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BP --> W2["Security SOPs"]
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BP --> W3["Deploy SOPs"]
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BP --> W4["Testing SOPs"]
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BP --> W5["... everything else"]
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end
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subgraph AFTER["✅ With Skills"]
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direction TB
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AP["System Prompt<br/>~500 tokens<br/>(descriptions only)"]
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AP -->|"task matches"| L1["Load: Weather<br/>+2,000 tokens"]
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end
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style BEFORE fill:#ffcccc,stroke:#cc0000
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style AFTER fill:#ccffcc,stroke:#00cc00
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style BP fill:#ff6b6b,stroke:#333,color:#fff
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style AP fill:#51cf66,stroke:#333,color:#fff
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style L1 fill:#4a9eff,stroke:#333,color:#fff
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```
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**10 skills × 2,000 tokens = 20,000 always loaded → ~500 base + 2,000 on demand**
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<!-- speaker_note: This is the efficiency win. 10x reduction in baseline context. Analogy: a pro doesn't carry every manual — they know which shelf to reach for. -->
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SOPs = Reliability
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===
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The SKILL.md **is** the standard operating procedure.
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**Without Skill** 🎲
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> "Check if my server is secure"
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- Runs random checks from training data
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- Misses half the important ones
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- Suggests changes that conflict with your infra
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**With Skill** 📋
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> "Check if my server is secure"
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- Loads healthcheck SKILL.md
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- Follows structured audit checklist
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- Firewall → SSH → Updates → Services
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- Prioritised report with specific fixes
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**Runbook vs. "figure it out"**
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<!-- speaker_note: This is the reliability win. Same request, wildly different outcomes. Like giving a junior engineer a runbook vs saying figure it out. -->
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Skills vs. Tools vs. System Prompts
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===
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| Layer | Answers | Example |
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| **Tools** | What *can* I do? | Read files, search web, send messages |
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| **System Prompt** | Who *am* I? | Helpful, concise, safety-conscious |
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| **Skills** | *How* do I do X well? | Step-by-step server security audit |
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```mermaid +render +width:100%
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graph LR
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T["🔧 Tools<br/>Capability"] --> A["🤖 Agent"]
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SP["🧠 System Prompt<br/>Identity"] --> A
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SK["🎯 Skills<br/>Expertise"] --> A
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style T fill:#ff6b6b,stroke:#333,color:#fff
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style SP fill:#ffd93d,stroke:#333,color:#000
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style SK fill:#4a9eff,stroke:#333,color:#fff
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style A fill:#51cf66,stroke:#333,color:#fff
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```
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Tools without skills = workshop full of power tools, no training
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<!-- speaker_note: All three layers are needed. Tools are hands, prompts are personality, skills are expertise. -->
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Real-World Examples
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* **Weather Skill** ☀️ — Simple. ~50 lines. Query APIs, format forecasts, handle locations. Loaded when someone asks "what's the weather?"
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* **Healthcheck Skill** 🔒 — Structured security audit playbook. Firewall, SSH, updates, service exposure. Prioritised findings with specific remediations.
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* **SecureTransport Flow Engineering** 🔐 — Deep domain expertise. File transfer flows, PGP encryption, SFTP patterns, error log locations, testing harnesses. Months of tribal knowledge, instantly available.
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* **Skill Creator** 🏗️ — A meta-skill: a skill for *building skills*. Encodes the structure, best practices, and packaging conventions.
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<!-- speaker_note: Range from trivial to deeply complex. The ST skill is a great example of tribal knowledge capture. -->
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The Bigger Picture
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===
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**Expertise Preservation** 🧠
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- Skills capture tribal knowledge
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- Your best engineer writes it once
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- Every agent benefits, forever
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- People leave. Skills persist.
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**Composability** 🧩
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- Modular: share, version, stack
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- Discoverable skill catalogues
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- ClawHub: a marketplace of expertise
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- Community flywheel: solve → share → improve
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```mermaid +render +width:100%
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graph LR
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E["👩💻 Expert writes skill"] --> P["📦 Published to ClawHub"]
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P --> U["🤖 Agents everywhere use it"]
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U --> F["🔄 Community improves it"]
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F --> P
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style E fill:#ff6b6b,stroke:#333,color:#fff
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style P fill:#4a9eff,stroke:#333,color:#fff
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style U fill:#51cf66,stroke:#333,color:#fff
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style F fill:#ffd93d,stroke:#333,color:#000
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```
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<!-- speaker_note: This is the strategic argument. Skills aren't just operational convenience — they're knowledge management that actually works. -->
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Skills = Efficiency + Reliability
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Load expertise on demand. Follow SOPs, not guesswork.
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Capture knowledge. Scale it. Share it.
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🎯
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<!-- speaker_note: Closing. The question isn't whether your agents need skills — it's what expertise you'd encode first. -->
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