- Refactor main CLAUDE.md from 491 to 164 lines (66% reduction) - Create 9 domain-specific CLAUDE.md files for focused guidance: * agents/CLAUDE.md (347 lines) - Agent development guide * marketing-skill/CLAUDE.md (253 lines) - Marketing tools * product-team/CLAUDE.md (268 lines) - Product management tools * engineering-team/CLAUDE.md (291 lines) - Engineering tools * standards/CLAUDE.md (176 lines) - Standards usage * c-level-advisor/CLAUDE.md (143 lines) - Strategic advisory * project-management/CLAUDE.md (139 lines) - Atlassian integration * ra-qm-team/CLAUDE.md (153 lines) - RA/QM compliance * templates/CLAUDE.md (77 lines) - Template system - Add navigation map in main CLAUDE.md for easy domain access - Create PROGRESS.md for real-time sprint tracking - Implement auto-documentation system for sprint progress Benefits: - Main CLAUDE.md now concise and navigable - Domain-specific guidance easier to find - No duplicate content across files - Better organization for 42 skills across 6 domains Total: 2,011 lines across 10 organized files vs 491 lines in 1 monolithic file Sprint: sprint-11-05-2025 Issue: Part of documentation refactoring milestone
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CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Purpose
This is a comprehensive skills library for Claude AI - reusable, production-ready skill packages that bundle domain expertise, best practices, analysis tools, and strategic frameworks. The repository provides modular skills that teams can download and use directly in their workflows.
Current Scope: 42 production-ready skills across 6 domains with 97 Python automation tools.
Key Distinction: This is NOT a traditional application. It's a library of skill packages meant to be extracted and deployed by users into their own Claude workflows.
Navigation Map
This repository uses modular documentation. For domain-specific guidance, see:
| Domain | CLAUDE.md Location | Focus |
|---|---|---|
| Agent Development | agents/CLAUDE.md | cs-* agent creation, YAML frontmatter, relative paths |
| Marketing Skills | marketing-skill/CLAUDE.md | Content creation, SEO, demand gen Python tools |
| Product Team | product-team/CLAUDE.md | RICE, OKRs, user stories, UX research tools |
| Engineering | engineering-team/CLAUDE.md | Scaffolding, fullstack, AI/ML, data tools |
| C-Level Advisory | c-level-advisor/CLAUDE.md | CEO/CTO strategic decision-making |
| Project Management | project-management/CLAUDE.md | Atlassian MCP, Jira/Confluence integration |
| RA/QM Compliance | ra-qm-team/CLAUDE.md | ISO 13485, MDR, FDA compliance workflows |
| Standards Library | standards/CLAUDE.md | Communication, quality, git, security standards |
| Templates | templates/CLAUDE.md | Template system usage |
Current Sprint: See documentation/delivery/sprint-11-05-2025/ for active sprint context and progress.
Architecture Overview
Repository Structure
claude-code-skills/
├── agents/ # cs-* prefixed agents (in development)
├── marketing-skill/ # 3 marketing skills + Python tools
├── product-team/ # 5 product skills + Python tools
├── engineering-team/ # 14 engineering skills + Python tools
├── c-level-advisor/ # 2 C-level skills
├── project-management/ # 6 PM skills + Atlassian MCP
├── ra-qm-team/ # 12 RA/QM compliance skills
├── standards/ # 5 standards library files
├── templates/ # Reusable templates
└── documentation/ # Implementation plans, sprints, delivery
Skill Package Pattern
Each skill follows this structure:
skill-name/
├── SKILL.md # Master documentation
├── scripts/ # Python CLI tools (no ML/LLM calls)
├── references/ # Expert knowledge bases
└── assets/ # User templates
Design Philosophy: Skills are self-contained packages. Each includes executable tools (Python scripts), knowledge bases (markdown references), and user-facing templates. Teams can extract a skill folder and use it immediately.
Key Pattern: Knowledge flows from references/ → into SKILL.md workflows → executed via scripts/ → applied using assets/ templates.
Git Workflow
Follow conventional commits and semantic versioning:
# Feature branches by domain
git checkout -b feature/marketing/seo-optimizer
git checkout -b feature/agents/content-creator
# Conventional commit format
feat(agents): implement cs-content-creator agent
fix(seo-optimizer): correct keyword density calculation
docs(README): update agent catalog section
# Semantic versioning by skill
git tag v1.0-content-creator
git tag v1.0-product-manager-toolkit
Branch Strategy: Domain-based branches, squash merge to main, semantic tags per skill release.
See standards/git/git-workflow-standards.md for complete workflow details.
Development Environment
No build system or test frameworks - intentional design choice for portability.
Python Scripts:
- Use standard library only (minimal dependencies)
- CLI-first design for easy automation
- Support both JSON and human-readable output
- No ML/LLM calls (keeps skills portable and fast)
If adding dependencies:
- Keep scripts runnable with minimal setup (
pip install packageat most) - Document all dependencies in SKILL.md
- Prefer standard library implementations
Current Sprint
Active Sprint: sprint-11-05-2025 (Nov 5-19, 2025) Goal: Skill-Agent Integration Phase 1-2 Status: Day 1 complete (foundation), Day 2 ready (marketing agents)
Progress Tracking:
- Sprint Plan - Day-by-day execution plan
- Sprint Context - Goals, scope, risks
- Sprint Progress - Real-time auto-updating tracker
Roadmap
Phase 1 Complete: 42 production-ready skills deployed
- Marketing (3), C-Level (2), Product (5), PM (6), Engineering (14), RA/QM (12)
- 97 Python automation tools, 90+ reference guides
- Complete enterprise coverage from marketing through regulatory compliance
Next Priorities:
- Phase 2 (Q1 2026): Marketing expansion - SEO optimizer, social media manager, campaign analytics
- Phase 3 (Q2 2026): Business & growth - Sales engineer, customer success, growth marketer
- Phase 4 (Q3 2026): Specialized domains - Mobile, blockchain, web3, finance
Target: 50+ skills by Q3 2026
See domain-specific roadmaps in each skill folder's README.md or roadmap files.
Key Principles
- Skills are products - Each skill deployable as standalone package
- Documentation-driven - Success depends on clear, actionable docs
- Algorithm over AI - Use deterministic analysis (code) vs LLM calls
- Template-heavy - Provide ready-to-use templates users customize
- Platform-specific - Specific best practices > generic advice
Anti-Patterns to Avoid
- Creating dependencies between skills (keep each self-contained)
- Adding complex build systems or test frameworks (maintain simplicity)
- Generic advice (focus on specific, actionable frameworks)
- LLM calls in scripts (defeats portability and speed)
- Over-documenting file structure (skills are simple by design)
Working with This Repository
Creating New Skills: Follow the appropriate domain's roadmap and CLAUDE.md guide (see Navigation Map above).
Editing Existing Skills: Maintain consistency across markdown files. Use the same voice, formatting, and structure patterns.
Quality Standard: Each skill should save users 40%+ time while improving consistency/quality by 30%+.
Additional Resources
- .gitignore: Excludes .vscode/, .DS_Store, AGENTS.md, PROMPTS.md, .env*
- Standards Library: standards/ - Communication, quality, git, documentation, security
- Implementation Plans: documentation/implementation/
- Sprint Delivery: documentation/delivery/
Last Updated: November 5, 2025 Current Sprint: sprint-11-05-2025 (Skill-Agent Integration Phase 1-2) Status: 42 skills deployed, agent system in development