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CORE_WORKSHOP_v1.0
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BLOCK 1 · FOUNDATIONS 9:45 – 10:30 · 45 min · 25L / 20HO

TOPIC 1.3 / 3 · MENTAL MODEL

Skills, Plugins, Agents

AI coding tools, the Claude Code loop, and the load-bearing skill / plugin / agent decision framework that Block 2 builds on.

1.3.1

CLI-first vs IDE-chat

5 min Lecture
Slide 1 / 3 · Two shapes

Where does the model live?

ShapeExamplesWhy it matters
IDE chatCursor, Copilot Chat, JetBrains AITight loop, lower engineering ceiling
CLI agentClaude Code, Codex CLI, Gemini CLIComposable, scriptable, higher ceiling
Slide 2 / 3 · Why CLI

CLI = composability

  • Pipes to other tools (grep, jq, gh)
  • Triggers from CI, hooks, cron, MCP servers
  • Versionable config — settings, skills, plugins on disk
  • Multi-CLI verification (run Codex + Claude on the same task)
  • This is why Sam's block lives at the CLI altitude
Slide 3 / 3 · Convergent shape

The shape is convergent

  • Prompt → plan → tool use → diff → confirm
  • Most CLIs implement some variation of this loop
  • Differences are surface, not deep
  • We'll demo with Claude Code; portability is the point
1.3.2

Claude Code core flow

5 min Lecture
Slide 1 / 3 · The loop

Claude Code core flow

PROMPT  →  PLAN  →  TOOL USE  →  DIFF  →  CONFIRM
                                      ↑                 ↓
                                      └──── iterate ←───┘
Slide 2 / 3 · One turn

Anatomy of one turn

  • Prompt — you describe the goal
  • Plan — model proposes steps (you can edit)
  • Tool use — model edits files, runs commands, reads diagnostics
  • Diff — every write is staged as a diff
  • Confirm — you accept, reject, or redirect
Slide 3 / 3 · Plugins extend the loop

Plugins extend the loop

  • A plugin can inject skills (extra knowledge)
  • A plugin can inject slash commands (new entry points)
  • A plugin can ship its own subagents
  • The skill-creator plugin we'll use next: all three
1.3.3

★ Skill vs plugin vs agent decision framework

10 min Lecture LOAD-BEARING — DO NOT CUT

Block 2 depends on this mental model. Without it, attendees don't know why they're promoting a prompt to a skill.

Slide 1 / 4 · Four surfaces

Four ways to package AI behavior

SurfaceWhat it isWhen to reach for it
PromptPlain text, one-offSingle use, exploratory, you don't need it again
SkillSKILL.md with frontmatter + body + referencesRepeatable workflow with specific triggers; you'll want this again next week
PluginFolder bundling skills + commands + MCP serversShipping a capability to a team; needs versioning + distribution + multiple skills bundled
AgentSpecialized subagent dispatched for a taskIsolated context, parallel work, narrow capability — when you want a fresh model, not a fresh prompt
Slide 2 / 4 · Hierarchy

The packaging hierarchy

PLUGIN
  ├── SKILL  (1..N)
  │     └── prompt body + references
  ├── slash commands
  ├── MCP servers
  └── subagents (AGENTS)

Skill is the atom. Plugin is the package. Agent is the dispatcher.

Slide 3 / 4 · Decision flow

Decision questions, in order

  1. Will I use this again? No → prompt. Yes → keep going.
  2. Does it need its own context window? Yes → agent.
  3. Will I ship it to others? Yes → plugin. No → skill.
  4. Does it bundle commands + MCP + multiple skills? Yes → plugin.
Slide 4 / 4 · Five examples

Where does each example land?

ExampleSurfaceWhy
One-off PR description for a single PRPromptSingle use
Generating PR descriptions for all PRs going forwardSkillRepeatable trigger
Running 5 different code reviewers in parallel on one PRAgent(s)Isolated contexts, parallel work
Standardized incident-response toolkit for a teamPluginBundles skills + commands + RBAC
Reading a single file to answer a questionPromptSingle use, exploratory
1.3.4

Plugin marketplace tour

3 min Lecture
Slide 1 / 2 · Marketplace

The Anthropic plugin marketplace

  • Discovery layer for plugins
  • Already includes: skill-creator, frontend-design, superpowers, context7, more
  • Installed via /plugin inside the Claude Code REPL
  • An ecosystem maturity signal — plugins are how the platform is shipping fast
Slide 2 / 2 · Today's plugin

skill-creator — our Block 2 spine

  • Plugin we'll use in Block 2 (the next ~75 min)
  • Should already be installed (Prerequisites)
  • We'll verify in Beat 1.3.5 hands-on
  • The plugin marketplace itself is worth a tour after the workshop
1.3.5

HO Beat A — Boot Claude Code + verify skill-creator

5 min Hands-on
Slide 1 / 2 · Two commands

Boot + verify

  • Open a terminal in the workshop repo
  • Run the verify one-liner below

Verify command:

grep -q '"skill-creator@' ~/.claude/plugins/installed_plugins.json \
  && echo "✓ skill-creator installed" \
  || echo "✗ NOT installed"
Slide 2 / 2 · Red X path

If you get the red X

  1. claude (launch the REPL)
  2. /plugin (interactive picker)
  3. Search "skill-creator" → install
  4. Re-run the verify command above

Don't try claude /plugin list/plugin is an interactive REPL command, not a CLI subcommand.

1.3.6

HO Beat B — Tour the skill-creator on disk

5 min Hands-on
Slide 1 / 3 · Where it lives

A plugin is a folder

~/.claude/plugins/marketplaces/
  claude-plugins-official/
    plugins/
      skill-creator/
Slide 2 / 3 · What's inside

The four things every plugin can ship

  • SKILL.md — the plugin's primary skill (the one Claude reads first)
  • scripts/ — Python/shell helpers the plugin invokes
  • references/ — long-form docs the skill links to (lazy-loaded)
  • agents/ — specialized subagents the plugin dispatches (e.g. grader, analyzer)
  • (skill-creator adds) eval-viewer/ — the HTML report we'll see in Block 2
Slide 3 / 3 · Why this matters

The plugin is just files

  • You can read every line of a plugin before it touches your machine
  • The grader subagent is agents/grader.md
  • The eval-viewer is a Python script you can run yourself
  • No magic. Just structured files.
1.3.7

HO Beat C — "Which is this?" classification

10 min Hands-on · discussion
Slide 1 / 6 · Setup

Which surface is this?

  • 5 scenarios on screen, one at a time
  • Vote: prompt / skill / plugin / agent
  • 1 min per scenario, then group discussion
  • No wrong answers — only better justifications
Slide 2 / 6 · Scenario 1

Scenario 1

"I want to generate a PR description for the PR I just opened. It's a one-line bugfix."

Vote: prompt / skill / plugin / agent

Slide 3 / 6 · Scenario 2

Scenario 2

"Every time anyone on my team opens a PR, they should get an auto-generated description following our team's format. I want this to be a hooked-in workflow."

Vote: prompt / skill / plugin / agent

Slide 4 / 6 · Scenario 3

Scenario 3

"I want to run a security reviewer, a performance reviewer, and a style reviewer on the same PR simultaneously, each in their own fresh context, then merge their findings."

Vote: prompt / skill / plugin / agent

Slide 5 / 6 · Scenario 4

Scenario 4

"My company has 15 internal AI-coding workflows: incident response, RFC scaffolding, code-review checklists, deploy verification, oncall handoffs. I want one install that gives every engineer all 15."

Vote: prompt / skill / plugin / agent

Slide 6 / 6 · Scenario 5

Scenario 5

"I want to ask the model what's in this single config file so I understand the timeout values."

Vote: prompt / skill / plugin / agent

1.3.8

Bridge to Block 2

2 min Lecture
Slide 1 / 2 · What you have

What you have now

  • A v5 prompt for Project Inspector (saved on disk)
  • The skill-creator plugin installed and verified
  • The decision framework for skill vs plugin vs agent
  • Working terminal, working CLI, working Claude Code session
Slide 2 / 2 · What's next

Block 2 — Build & Eval a Skill

  • We promote your v5 prompt to a working skill (Beat A — 5 min)
  • We run with-skill vs baseline in parallel (Beat C — 8 min)
  • The plugin tells you which of your tests doesn't test anything (Beat F)
  • You leave with a benchmarked, optimized, eval-tested skill on disk

Coffee first. Back at 10:45.