Production Release Engineering: Shipping v4.5.0 with 739 Skills and Zero Downtime

Posted on Jan 3, 2025

The Challenge

I needed to ship v4.5.0 of the Claude Code Plugins marketplace after 8 days of intensive development. The release included:

38 commits across multiple feature areas
500 new standalone skills (739 total)
ZCF Integration (5 phases complete)
External Plugin Sync infrastructure
MCP Registry manifests for 7 servers
5,385 files changed (+197K lines, -8K lines)

The requirement: Zero manual errors, complete audit trail, automated quality gates, and the ability to roll back at any failure point.

Why This Matters

Most teams ship releases manually:

Someone updates version numbers in 3-4 files
Another person writes changelog entries
A third verifies tests pass
Someone tags the commit
Another creates the GitHub release

The problems:

Version conflicts between files
Changelog drift from actual changes
Manual processes = human errors
No rollback automation
Poor audit trails

I wanted to prove you can automate ALL of it with intelligent analysis and safety gates.

The Journey: Building Universal Release Engineering

First Attempt: Manual Release Process

Initially, I’d run releases like everyone else:

# Update package.json manually
vim package.json  # Change 4.4.0 → 4.5.0

# Update README manually
vim README.md     # Update badges

# Write changelog manually
vim CHANGELOG.md  # Summarize 38 commits from memory

# Create release
git add -A
git commit -m "chore: release v4.5.0"
git tag v4.5.0
git push origin main --tags

The problem I hit: After shipping v4.3.0, I realized:

README said v4.3.0
package.json said v4.2.9
CHANGELOG was missing 12 commits

Version conflicts everywhere. No single source of truth.

Second Attempt: Config-Driven Release Automation

I built a /release skill that would:

Detect version scheme (semver vs padded)
Find ALL version files automatically
Analyze commits to determine bump level
Generate changelog from git history
Update all files atomically
Create tag and GitHub release

The architecture:

Preflight Checks → Analysis → Decision → Plan → Apply → Verify
     ↓                ↓          ↓         ↓       ↓       ↓
  Working tree    Git log   Bump level  File     Commit  GitHub
  is clean?       parsing   (semver)    updates  + tag   release

Each phase is a gate - if it fails, the entire workflow stops.

Technical Implementation

Phase 1: Preflight Checks

Before ANY changes, verify the environment:

# Working tree must be clean
git status --porcelain | head -20

# On correct branch
git branch --show-current  # Must be 'main'

# Last tag exists
git describe --tags --abbrev=0  # v4.4.0

# Version file exists
cat package.json | grep '"version"'  # 4.4.0

Safety gate: If any check fails → STOP. No partial updates.

Phase 2: Commit Analysis

Parse git history to categorize changes:

# Get commits since last release
git log v4.4.0..HEAD --pretty=format:"%s"

# Categorize by type
git log v4.4.0..HEAD --format="%s" | \
  grep -iE "^(feat|fix|perf|security|BREAKING)"

The output:

20 features (→ MINOR bump)
11 fixes
0 breaking changes (would force MAJOR)

Phase 3: Intelligent Version Bump

Decision logic:

BREAKING changes → MAJOR (4.4.0 → 5.0.0)
Features only → MINOR (4.4.0 → 4.5.0)
Fixes only → PATCH (4.4.0 → 4.4.1)
No changes → SKIP (don't release)

My release:

20 features + 11 fixes → MINOR bump to 4.5.0

Phase 4: Atomic File Updates

Update ALL version references in one transaction:

# 1. package.json version
sed -i 's/"version": "4.4.0"/"version": "4.5.0"/' package.json

# 2. README badges
sed -i 's/version-4\.4\.0/version-4.5.0/g' README.md

# 3. Prepend CHANGELOG entry
# (Edit tool with full commit analysis)

# 4. Sync marketplace catalog
pnpm run sync-marketplace

Key insight: All updates happen BEFORE any commit. Either everything succeeds or nothing changes.

Phase 5: Generate Changelog from Commits

Instead of manual summaries, parse git history:

## [4.5.0] - 2025-01-03

### 50-Vendor SaaS Skill Packs (500 Skills)
- Skill Databases: 105 vendor databases
- Flagship Packs: Supabase, Vercel, OpenRouter, Kling AI
- Template System: 30 Jinja2 slot templates

### ZCF Integration (Issue #184)
- MCP Registry manifests for 7 servers
- ZCF preset configuration
- BMAD workflows
- Tool routing documentation

### Statistics
| Metric | v4.4.0 | v4.5.0 | Change |
|--------|--------|--------|--------|
| Skills | 244 | 739 | +495 |
| Plugins | 258 | 260 | +2 |

Auto-generated from git commits, not written by hand.

Phase 6: Release Execution

Commit, tag, and push in one atomic operation:

# Single commit with all changes
git add -A
git commit -m "chore(release): v4.5.0 - SaaS Skill Packs + ZCF Integration"

# Annotated tag with metadata
git tag -a v4.5.0 -m "Release v4.5.0: 50-Vendor SaaS Skill Packs..."

# Push both atomically
git push origin main && git push origin v4.5.0

Rollback safety:

# If push fails, everything rolls back:
git tag -d v4.5.0
git reset --hard HEAD~1

Phase 7: GitHub Release Automation

Create GitHub release with rich metadata:

gh release create v4.5.0 \
  --title "v4.5.0 - 50-Vendor SaaS Skill Packs + ZCF Integration" \
  --notes "## Release Highlights
- 50-Vendor SaaS Skill Packs (500 skills)
- ZCF Integration (5 phases)
- External Plugin Sync
..."

Result: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/releases/tag/v4.5.0

What I Learned

1. Atomic Operations Are Critical

Before: Update files one-by-one → partial failures left repo in broken state

After: All updates happen before commit → either everything succeeds or nothing changes

2. Git History Is Your Source of Truth

Before: Manually write changelog from memory → miss commits, misrepresent changes

After: Parse git log for features/fixes → accurate, complete, automated

3. Safety Gates Prevent Disasters

Before: No validation → pushed broken releases multiple times

After: Each phase validates before proceeding:

Working tree clean?
Tests pass?
Version conflicts resolved?
Changelog generated?

4. Rollback Plans Are Mandatory

Before: If something failed mid-release → manual recovery, downtime

After: Each phase has explicit rollback:

# Tag failed to push?
git tag -d v4.5.0
git reset --hard HEAD~1

# GitHub release failed?
gh release delete v4.5.0 --yes
git push origin --delete v4.5.0

5. Semver Automation Scales

The pattern:

Parse commits for feat:, fix:, BREAKING:
Calculate bump level automatically
No human decision needed

Works for:

10 commits or 1,000 commits
Solo developer or 50-person team
Any language, any project

Results

Release v4.5.0 Shipped Successfully

Metric	Value
Time to Ship	18 minutes (from `/release` to live)
Files Updated	3 (package.json, README, changelog)
Manual Steps	1 (approve the release)
Errors	0
Rollbacks Needed	0

What Got Shipped

Skills: 244 → 739 (+495 skills)
Plugins: 258 → 260
MCP Servers: 5 → 7
Skill Databases: 0 → 105

Automated Quality Gates

Working tree clean
All tests pass
Version files synced
Changelog generated
Tag created
GitHub release published

The Real Value

This isn’t just about shipping v4.5.0 faster. It’s about:

Consistency - Every release follows the same workflow
Auditability - Complete trail from commits → changelog → tag → release
Safety - Gates prevent broken releases
Scalability - Works for 10 commits or 1,000
Knowledge Transfer - Anyone can run /release, no tribal knowledge

Try It Yourself

The /release skill is part of the Claude Code Plugins marketplace:

/plugin marketplace add jeremylongshore/claude-code-plugins
/plugin install release@claude-code-plugins-plus

Run a release:

/release

It will:

Analyze your commits
Suggest a version bump
Generate a changelog
Show you the plan
Wait for your approval
Execute atomically
Roll back on any failure

GitHub Release Workflow: When Yesterday’s Updates Aren’t Public (And How We Fixed It) - Our first attempt at release automation
Building External Plugin Sync: How We Keep 258 Community Plugins Fresh - Part of what shipped in v4.5.0
Debugging a Critical Marketplace Schema Validation Failure - Why release validation matters

What’s Next

I’m working on:

Config-driven releases - .release.yml for team customization
Multi-repo releases - Coordinated releases across 3+ repos
Deployment automation - Auto-deploy after GitHub release
Smoke tests - Verify live deployment before announcing

Production release engineering isn’t glamorous, but it’s the difference between shipping with confidence and hoping nothing breaks.

Want to see the actual release? https://github.com/jeremylongshore/claude-code-plugins-plus-skills/releases/tag/v4.5.0