nist-compliance

LLM Software Development Standards Start any project right in 30 seconds. Battle-tested standards from real production systems.

インストール
CLI
npx skills add https://github.com/williamzujkowski/standards --skill nist-compliance

CLI を使用してこのスキルをインストールし、ワークスペースで SKILL.md ワークフローの使用を開始します。

最終更新日: 5/6/2026

🚀 Software Development Standards

Anthropic Skills

Start any project right in 30 seconds. Based on industry best practices and NIST guidelines.

Why This Repository?

You're starting a new project. You need to make dozens of decisions: project structure, testing approach, security patterns, CI/CD setup, documentation format. Each wrong choice costs days or weeks to fix later.

This repository gives you those answers immediately - comprehensive, production-tested standards that work together as a complete system. No more arguing about code style. No more wondering about test coverage. No more security reviews finding basic issues.

Just copy, implement, and ship.


🆕 Skills System (NEW!)

Last Updated: 2025-10-24 21:45:00 EDT (UTC-04:00)

Load only what you need. Progressive loading reduces token usage by 91-99.6% depending on scenario:

  • Repository metadata: 127K → 500 tokens (99.6% reduction)
  • Typical usage: 8.9K → 573 tokens (93.6% reduction)
  • Single skill Level 1: ~300-600 tokens

Evidence: 61 active skills with progressive disclosure (Level 1: metadata, Level 2: instructions, Level 3: resources)

What Are Skills?

Instead of loading massive 50,000+ token documents, use progressive skills that deliver the right information at the right time:

Note: The @load directive is planned for v2.0. Current implementation uses the skill-loader script.

Current (v1.x):

# Load Level 1: Quick Start (5 minutes, ~336 tokens)
python3 scripts/skill-loader.py load skill:coding-standards

# Load by product type (auto-selects relevant skills)
python3 scripts/skill-loader.py load product:api --language python
# Loads: coding-standards, security-practices, testing, nist-compliance

# Total: ~1,755 tokens compared to loading all standards documents (~150K tokens) (98.8% reduction)

Planned (v2.0):

@load skill:coding-standards
@load product:api --language python

Quick Skills Tutorial (2 minutes)

Current (v1.x):

# 1. Get skill recommendations for your project
python3 scripts/skill-loader.py recommend ./

# 2. Load recommended skills
python3 scripts/skill-loader.py load product:api

# 3. See the difference!
# Before: ~150,000 tokens (full standards)
# After: ~1,755 tokens (Level 1)

Planned (v2.0):

# 2. Load recommended skills
@load product:api

Available Skills (61 Total)

Skill Count Verified: 2025-10-24 19:21:55 EDT (UTC-04:00)

Core Skills (examples with estimated Level 1 token counts):

  • coding-standards: Code quality patterns (~300-400 tokens L1)
  • security-practices: Modern security (~400-500 tokens L1)
  • testing: TDD & testing strategies (~400-500 tokens L1)
  • nist-compliance: NIST 800-53r5 controls (~500-600 tokens L1)

Note: Token counts are estimates. Actual counts vary based on skill complexity. See skills/ directory for complete catalog.

View Full Catalog → | Quick Start Guide → | Skills Directory →


⚡ Quick Start for New Projects

Copy these templates to your new repository and let AI do the rest:

# 1. Copy the kickstart template to your new repo
curl -o KICKSTART.md https://raw.githubusercontent.com/williamzujkowski/standards/master/templates/KICKSTART_REPO.md

# 2. Fill in basic project details (or let AI auto-detect)

# 3. Provide KICKSTART.md to any AI assistant (Claude, ChatGPT, Gemini)
# AI will auto-detect your tech stack and generate:
# - Complete project structure
# - Standards-aligned code
# - Configuration files
# - CI/CD pipelines
# - Testing setup
# - Security implementation

Option 2: Use LLM Prompt Directly

  1. Copy this prompt: KICKSTART_PROMPT.md
  2. Paste into any LLM (ChatGPT, Claude, Gemini, etc.) with your project description
  3. Get instant analysis:
    • Complete project structure
    • Relevant standards selection
    • Implementation roadmap
    • Tool configurations
    • First PR ready to go

Example:

You: [Paste kickstart prompt] + "I'm building a Python API with FastAPI and PostgreSQL"

AI: Here's your complete setup:
- Project structure with /src, /tests, /docs
- FastAPI best practices from CODING_STANDARDS.md
- pytest configuration from TESTING_STANDARDS.md
- PostgreSQL patterns from DATA_ENGINEERING_STANDARDS.md
- Docker setup from CLOUD_NATIVE_STANDARDS.md
- GitHub Actions from .github/workflows/
[... complete implementation plan ...]

What You Get

The AI assistant will generate a complete PROJECT_PLAN.md including:

  • Auto-detected tech stack from your repository
  • Standards recommendations using @load directives (v2.0 - planned) or skill-loader script (v1.x - current)
  • Project structure with full directory tree
  • Configuration files (pyproject.toml, package.json, etc.)
  • CI/CD pipelines with quality gates
  • Security implementation with NIST controls
  • Testing strategy with 80%+ coverage targets
  • 8-week implementation timeline with phases

Common Scenarios

Note: The @load directive examples below are planned for v2.0. Current implementation uses skill-loader script.

Python API (v2.0 - planned):

@load [product:api + CS:python + TS:pytest + SEC:* + DE:database]

Python API (v1.x - current):

python3 scripts/skill-loader.py load product:api --language python

React Web App (v2.0 - planned):

@load [product:frontend-web + FE:react + SEC:auth + DOP:ci-cd]

React Web App (v1.x - current):

python3 scripts/skill-loader.py load product:frontend-web --framework react

Mobile App (v2.0 - planned):

@load [product:mobile + CS:swift + TS:xctest + SEC:mobile-auth]

Mobile App (v1.x - current):

python3 scripts/skill-loader.py load product:mobile

Data Pipeline (v2.0 - planned):

@load [product:data-pipeline + CS:python + DE:* + OBS:monitoring]

Data Pipeline (v1.x - current):

python3 scripts/skill-loader.py load product:data-pipeline --language python

📋 Available Templates

Core Templates

Template Purpose Usage
KICKSTART_REPO.md LLM-optimized repo kickstart Copy to new repo, fill details, provide to AI
PROJECT_PLAN_TEMPLATE.md Systematic project planning AI generates this from kickstart

Example Projects

Example Tech Stack Located In
Python API FastAPI + PostgreSQL examples/project-templates/python-api/
React SPA React + TypeScript examples/project-templates/react-spa/
NIST-compliant Service Security controls examples/nist-templates/

🔄 For Existing Projects

# Quick assessment
curl -O https://raw.githubusercontent.com/williamzujkowski/standards/master/scripts/setup-project.sh
chmod +x setup-project.sh
./setup-project.sh --assess my-project

# Or manually:
1. Review UNIFIED_STANDARDS.md for gaps
2. Copy relevant templates from examples/
3. Run validation: python scripts/generate-audit-reports.py

📚 What You Get

Complete Standards Library (25 Documents)

Core Development

Specialized Domains

  • Frontend, Mobile, Backend, Data Engineering
  • Cloud Native, DevOps, Observability
  • AI/ML, Event-Driven, Microservices
  • Cost Optimization, Legal Compliance

Ready-to-Use Templates

examples/
├── project-templates/     # Python, JS/TS, Go starter projects
├── nist-templates/        # Security components with compliance tags
├── docker/                # Container configurations
└── ci-cd/                 # GitHub Actions workflows

Automation & Tools

  • Setup Scripts: Auto-configure new projects
  • Validation Tools: Check standards compliance
  • NIST Tagging: Security control annotations
  • VS Code Extension: Real-time compliance hints
  • Pre-commit Hooks: Enforce standards automatically

🎯 For Different Roles

Developers

  • Copy working code patterns
  • Skip bikeshedding discussions
  • Focus on building features
  • Pass code reviews easily

Tech Leads

  • Onboard team members faster
  • Maintain consistency across projects
  • Reduce technical debt
  • Implement best practices systematically

Architects

  • Reference architecture patterns
  • Security-by-default designs
  • Scalability guidelines
  • Integration strategies

Compliance Teams

  • NIST 800-53r5 control templates
  • Audit-ready documentation
  • Automated compliance checking
  • Evidence collection tools

🔥 Real Examples

Start a Python API

Planned (v2.0):

@load [product:api + CS:python + TS:pytest + SEC:auth]
# Gets you: FastAPI structure, pytest config, JWT auth, Docker, CI/CD

Current (v1.x):

python3 scripts/skill-loader.py load product:api --language python
# Gets you: FastAPI structure, pytest config, JWT auth, Docker, CI/CD

Build a React App

Planned (v2.0):

@load [product:frontend-web + FE:react + SEC:*]
# Gets you: React patterns, testing, all security standards, deployment

Current (v1.x):

python3 scripts/skill-loader.py load product:frontend-web --framework react
# Gets you: React patterns, testing, all security standards, deployment

Data Pipeline

Planned (v2.0):

@load [product:data-pipeline + DE:* + OBS:monitoring]
# Gets you: ETL patterns, data quality, monitoring, orchestration

Current (v1.x):

python3 scripts/skill-loader.py load product:data-pipeline
# Gets you: ETL patterns, data quality, monitoring, orchestration

📁 Repository Structure

standards/
├── docs/
│   ├── standards/          # 24 comprehensive standards
│   ├── guides/             # Implementation guides
│   └── nist/               # NIST compliance docs
├── examples/               # Copy-paste templates
├── scripts/                # Automation tools
├── config/                 # Configuration files
├── .github/workflows/      # CI/CD templates
└── CLAUDE.md               # LLM interface & routing

MIT License - Free for commercial use. Standards provided "as-is" without warranty. Legal compliance documents are templates, not legal advice. Always consult professionals for your specific needs.


🤝 Contributing

We actively welcome contributions! The standards evolve with real-world usage.

  • Report issues you encounter
  • Submit PRs with improvements
  • Share templates that work
  • Add examples from your projects

See CREATING_STANDARDS_GUIDE.md for guidelines.

📖 Documentation (MkDocs)

This repository uses MkDocs with the Material theme for documentation.

Local Development:

# Install dependencies
pip install -r requirements.txt

# Serve documentation locally (with live reload)
mkdocs serve
# Visit http://127.0.0.1:8000

# Build static site
mkdocs build

# Build with strict mode (fails on warnings)
mkdocs build --strict

Features:

  • Material theme with light/dark mode
  • Enhanced search functionality
  • Mobile-responsive navigation
  • Automatic deployment via GitHub Actions

Documentation automatically deploys to GitHub Pages when changes are pushed to the master branch.


🤖 Claude Code Integration

Make all standards skills and agents globally available in Claude Code via auto-discovery.

Quick Install

# Run from standards repo root
./scripts/sync-to-claude.sh

# Verify installation
ls ~/.claude/skills/std-* | head -5
ls ~/.claude/agents/std-*.md | head -5

What Gets Installed

  • 61 Skills: Symlinked to ~/.claude/skills/std-*
  • 60 Agents: Symlinked to ~/.claude/agents/std-*.md

All items prefixed with std- for easy identification and to avoid conflicts.

Uninstall

./scripts/sync-to-claude.sh --uninstall

Get Started

Skills (NEW!)

Resources

Support


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