Claude-skill-registry elevate-code

Elevate projects to production quality using proven patterns. Use when starting a project, reviewing architecture, auditing code, or when user mentions "elevate-code", "production ready", "patterns", "make it production grade".

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/elevate-code" ~/.claude/skills/majiayu000-claude-skill-registry-elevate-code && rm -rf "$T"
manifest: skills/data/elevate-code/SKILL.md
source content

Elevate Code

Transform any project into production-quality software using proven patterns.

The Problem: Most projects fail in predictable ways—users can't set them up, accidents cause data loss, crashes waste hours of progress, code becomes unmaintainable, errors are cryptic. These aren't bugs; they're missing patterns.

The Solution: Elevate systematically applies 12 battle-tested patterns that distinguish amateur code from production software.


Quick Start

ModeWhen to UseWhat Happens
New ProjectStarting from scratchDetect type → Generate scaffold with all patterns
AuditReviewing existing codeDetect type → Scan → Gap report
TransformElevating existing projectAudit + Propose + Generate missing pieces

The 12 Patterns

The Foundation: The Triad (Patterns 1-3)

Three non-negotiable properties. If your project lacks any of these, fix them first.

Setup should verify. Mistakes should undo. Crashes should resume.

#PatternLitmus Test
1Health (Doctor)Can a new user run
tool doctor
and know what's missing?
2Safety (Safety Net)Can a mistake be undone in under 60 seconds?
3Resilience (Statekeeper)Can interrupted work resume without losing progress?

The Complete Set (Patterns 4-12)

#PatternProblem It Solves
4Architecture"The code is a tangled mess"
5Data Models"What shape is this data?"
6Code Organization"Where does this code go?"
7Error Handling"It failed but I don't know why"
8Testing"I'm afraid to change anything"
9Build & Deploy"How do I ship this?"
10CLI UX"This tool is confusing"
11Documentation"How does this work?"
12State Persistence"Where did my data go?"

Elevation Workflow

Step 1: Detect Project Type

Scan for file markers to identify project type and load the appropriate checklist:

File MarkersProject TypeChecklist
pyproject.toml
+
[project.scripts]
Python CLIpython-cli.md
package.json
+
"bin"
field
Node.js CLInode-cli.md
manifest.json
+
"background"
Browser Extensionbrowser-extension.md
pyproject.toml
+
fastapi
in deps
REST API (Python)rest-api.md
package.json
+
express
/
hono
/
fastify
REST API (Node)rest-api.md
mcp.json
OR
@modelcontextprotocol
imports
MCP Servermcp-server.md
action.yml
or
action.yaml
GitHub Actiongithub-action.md

Step 2: Scan for Existing Patterns

For each of the 12 patterns, grep for indicators and score as Present, Partial, or Missing:

# Triad
grep -rE "(doctor|check|verify|preflight)" .         # Health
grep -rE "(undo|restore|trash|dry-run)" .            # Safety
grep -rE "(checkpoint|resume|state\.json)" .         # Resilience

# Structure
grep -rE "(@dataclass|interface |TypedDict)" .       # Data Models
grep -rE "(pytest|vitest|conftest|\.test\.)" .       # Testing

# Quality
grep -rE "(retry|backoff|graceful)" .                # Error Handling

Step 3: Generate Gap Report

## Gap Analysis: <project-name>

**Project Type**: <detected-type>
**Patterns Detected**: X/12

### Present
- [x] Pattern Name - evidence found

### Partial
- [~] Pattern Name - what exists, what's missing

### Missing
- [ ] Pattern Name - why it matters

Step 4: Propose Transformations

For each gap, propose specific changes. Prioritize by impact:

  1. Triad first (Doctor, Safety, Statekeeper)
  2. Data Models (foundation for everything else)
  3. Error Handling (user experience)
  4. Testing (confidence to change)
  5. Everything else

Step 5: Generate Scaffold

For missing patterns, generate files from

templates/<project-type>/
:

  • Customize with project name
  • Show diff preview before writing

Success Criteria

A fully elevated project passes:

  • Triad: doctor ✓, undo ✓, resume ✓
  • Type Safety: All data structures typed (dataclass/interface)
  • Module Separation: One module = one responsibility
  • Error Messages: Include what + why + fix
  • Tests: Mocked external deps, >80% coverage on core
  • Build Config: Standard tooling (pyproject.toml / package.json)
  • AI Collaboration: CLAUDE.md with architecture
  • Output Modes: Human +
    --json
    +
    --quiet

Elevate: Because production-quality isn't about perfection—it's about patterns.