Lesson 7 - Capstone: Build, Validate, and Ship

Apply everything you've learned to deliver a production-grade skill. Validate it with tooling, run a cold test, and publish it for your team or the community.

Duration: 2.5-3 hours

Learning Objectives

By the end of this lesson, you will be able to:

  • Build a complete skill with instructions, references, and scripts that aligns to your Lesson 1 charter.
  • Validate structure using the skills-ref CLI and behavioral quality using smoke tests.
  • Conduct a cold test where another person or AI tool uses the skill without coaching.
  • Ship the skill via git and establish a maintenance plan.

Videos

Choosing and Scoping Your Capstone

Select a compelling workflow, scope it realistically, and set clear success criteria for the session.

Duration: 6 minutes

Video coming soon

The End-to-End Build Cycle

Walk through the complete build process with checkpoints, demonstrating the finished deploy-checklist as reference.

Duration: 12 minutes

Video coming soon

Maintenance, Composition, and What's Next

Position the capstone as the beginning — cover maintenance, composing skills, and growing a skill library.

Duration: 6 minutes

Video coming soon

Key Concepts

Capstone Project Options

Choose one of these projects or bring your own: ### Option 1: Code Review Skill **Problem:** Reviews are inconsistent — different reviewers check different things. **What to build:** Automated review against your team's specific conventions. **Include:** `references/style-guide.md` with conventions, output format as a checklist. **Good for:** Developers, tech leads, anyone who reviews PRs. ### Option 2: Documentation Skill **Problem:** Docs don't match your project's style or structure. **What to build:** Generate docs following your project's format and voice. **Include:** `references/doc-template.md`, `references/example-doc.md`. **Good for:** Technical writers, product managers, anyone who writes docs. ### Option 3: Deploy Checklist Skill **Problem:** Deployments miss steps — someone forgets migrations or env var checks. **What to build:** Pre-deploy validation that catches issues before shipping. **Include:** `scripts/pre-deploy-check.sh`, `assets/required-env-vars.json`. **Good for:** DevOps, backend engineers, anyone who ships code. ### Option 4: Content Skill **Problem:** Content doesn't match your brand voice or format. **What to build:** Content creation following your brand's tone and structure. **Include:** `references/brand-voice.md`, `references/content-template.md`. **Good for:** Marketers, content creators, product managers. ### Option 5: Your Own **Problem:** The workflow from your Lesson 1 charter. **What to build:** Whatever saves you the most time. **Include:** Whatever supporting files make sense.

Build Checklist

Track your progress through the 8-step build cycle: **Define (Lesson 1)** - [ ] Problem statement: What pain does this skill solve? - [ ] Target user: Who will use this skill? - [ ] Success metric: How will you know it's working? **Structure (Lesson 2)** - [ ] Folder created with correct kebab-case naming - [ ] SKILL.md has valid frontmatter (name matches folder, description is scenario-specific) **Write (Lesson 3)** - [ ] Trigger section with specific activation conditions - [ ] Workflow with 4+ numbered steps, each starting with a verb - [ ] Constraints with at least 2 things NOT to do - [ ] Output section with concrete example **Enhance (Lessons 4-6)** - [ ] references/ added if needed (templates, examples) - [ ] scripts/ added if needed (validation, automation) - [ ] assets/ added if needed (data, configs) - [ ] Platform features added if applicable ($ARGUMENTS, paths) - [ ] Supporting Files table documented in SKILL.md **Test & Ship (Lesson 7)** - [ ] Tested 3+ times with different inputs - [ ] Deviations logged and instructions fixed - [ ] skills-ref validate passes (or manual validation checklist completed) - [ ] Cold test: someone else used it without coaching - [ ] Committed to git and shared (PR, repo, or community)

Capstone Quality Rubric

Score your capstone on each dimension (aim for 4-5 on all): | Dimension | 1-2 (Needs Work) | 3 (Acceptable) | 4-5 (Excellent) | |-----------|-------------------|-----------------|------------------| | **Problem Clarity** | Vague or too broad | Partially scoped | Crisp trigger + success metric | | **Instruction Quality** | Missing sections | Basic structure, some gaps | All 4 parts with examples + quality gates | | **Supporting Files** | None when needed | One directory used | References + scripts/assets, all documented | | **Testing** | Untested | One manual pass | 3+ logged tests, deviations fixed | | **Sharing** | Local only | In repo, no docs | PR + README + compatibility notes | Use this rubric for self-assessment and peer review.

Validation Pipeline

Run these checks before sharing: **Automated:** ```bash # Validate structure (if skills-ref is installed) skills-ref validate ./my-skill # Alternative: manual validation # 1. Folder name matches 'name' field? ✓ # 2. Frontmatter valid YAML between --- markers? ✓ # 3. Name is lowercase with hyphens? ✓ # 4. Description under 1024 chars and scenario-specific? ✓ # 5. All file references use relative paths? ✓ # 6. Scripts are executable (chmod +x)? ✓ ``` **Manual:** - [ ] Skill tested 3+ times with different inputs - [ ] Cold test completed (another person or AI tool used it successfully) - [ ] Supporting Files table is complete and accurate - [ ] No hardcoded paths, secrets, or machine-specific references

Course Summary: Your Journey

Here's what you've learned across 7 lessons: | Lesson | Key Takeaway | What You Built | |--------|-------------|----------------| | 1. Why Skills Matter | Skills = reusable expertise, open standard across 30+ tools | Scorecard + charter | | 2. Designing a Skill | SKILL.md + optional directories, progressive disclosure | Folder skeleton + frontmatter | | 3. Crafting Instructions | Trigger → Workflow → Constraints → Output framework | Complete instruction body | | 4. Deploying & Sharing | Personal → project → enterprise, shared via git | Promoted skill to project repo | | 5. Power Features | references/, scripts/, assets/ for richer skills | Template + validation script | | 6. Platform Enhancements | Standard first, platform features second | Cross-platform compatibility | | 7. Build & Ship | Full cycle: define, build, test, iterate, validate, share | Production-grade capstone skill | **You now have the ability to:** - Capture your expertise as reusable, testable skills - Share skills with your team via git - Write skills that work across 30+ AI tools - Build, test, iterate, and ship skills independently Welcome to the skill-building community. The skill you built today is just the beginning.

Common Mistakes & Pitfalls

Skipping the charter and jumping straight to building

Without a clear problem statement and success metric, you'll build something that 'works' but doesn't solve a real pain. Five minutes on the charter saves hours of unfocused work.

Testing with toy inputs instead of real scenarios

A skill that works with 'Hello World' may fail with real data. Use actual tasks from your workflow — that's where the edge cases live.

Testing only once

One test doesn't catch inconsistencies. Three tests with different inputs reveals whether the skill is truly reliable.

Skipping the cold test

If the skill only works because YOU know the missing context, it's not ready to share. Have someone else use it without any coaching.

Overbuilding before shipping

Ship version 1 when it works, not when it's perfect. Real feedback from real usage is more valuable than hypothetical improvements.

Not establishing a maintenance plan

Skills drift as your workflow evolves. Set a reminder to review your skill quarterly. Update it or retire it — stale skills erode trust.

Exercises

Exercise 1: Build Your Capstone Skill

60 minutes

Use the build checklist to create a complete skill from scratch (or finish the one you've been building). Follow the 8-step cycle.

Expected Output:

A complete skill directory with SKILL.md, supporting files, and validated structure.

Success Criteria:

  • SKILL.md has valid frontmatter and all four instruction sections populated.
  • At least one supporting file (reference, script, or asset) included and documented.
  • skills-ref validate passes (or manual validation checklist completed).
  • Supporting Files table present in SKILL.md.

Exercise 2: The Cold Test

30 minutes

Hand your skill to another person (or a different AI tool) with NO explanation. Can they use it successfully from SKILL.md alone?

Expected Output:

Feedback from the tester: what worked, what was confusing, and suggestions.

Success Criteria:

  • Tester completed the core workflow without verbal coaching from you.
  • Collected specific feedback on at least one confusing or missing element.
  • Applied at least one instruction improvement based on feedback.
  • Re-tested after the improvement to confirm the fix works.

Exercise 3: Ship It

15 minutes

Commit your skill to a git repository, open a PR or publish it, and write a short announcement describing the skill.

Expected Output:

Your skill live in a repository, accessible to at least one other person.

Success Criteria:

  • Skill committed to git with a descriptive commit message.
  • PR description (or README) includes: problem solved, how to invoke, test evidence.
  • Compatibility field documents tested platforms.
  • Shared with at least one other person (teammate, community, or public repo).

Lesson Reflection

Take a moment to reflect on what you've learned:

  • 1. Compare your Lesson 1 scorecard to your capstone result. How much time does the skill save per week?
  • 2. What was the most surprising thing you learned about writing instructions for AI?
  • 3. During the cold test, what did the tester struggle with? What does that tell you about your instructions?
  • 4. What's the next skill you'll build after this capstone?
  • 5. If your entire team adopted skill-based workflows, what would change about how you work together?