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claude-skills

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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: 53 production-ready skills across 8 domains with 87+ 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.

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We split this CLAUDE.md into the rules it gives an agent

7 rules. About 0 are common, 5 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use standard library only (minimal dependencies)

    line 110
  2. Distinctive:

    No ML/LLM calls (keeps skills portable and fast)

    line 113
  3. Very specific:

    Keep scripts runnable with minimal setup (pip install package at most)

    line 116
  4. Very specific:

    Document all dependencies in SKILL.md

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  5. Distinctive:

    Prefer standard library implementations

    line 118
  6. Distinctive:

    Algorithm over AI: - Use deterministic analysis (code) vs LLM calls

    line 156
  7. Distinctive:

    Creating New Skills: Follow the appropriate domain's roadmap and CLAUDE.md guide (see Navigation Map above).

    line 170

≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
CLAUDE.md

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: 53 production-ready skills across 8 domains with 87+ 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:

DomainCLAUDE.md LocationFocus
Agent Developmentagents/CLAUDE.mdcs-* agent creation, YAML frontmatter, relative paths
Marketing Skillsmarketing-skill/CLAUDE.mdContent creation, SEO, demand gen, campaign analytics Python tools
Product Teamproduct-team/CLAUDE.mdRICE, OKRs, user stories, UX research tools
Engineeringengineering-team/CLAUDE.mdScaffolding, fullstack, AI/ML, data tools
C-Level Advisoryc-level-advisor/CLAUDE.mdCEO/CTO strategic decision-making
Project Managementproject-management/CLAUDE.mdAtlassian MCP, Jira/Confluence integration
RA/QM Compliancera-qm-team/CLAUDE.mdISO 13485, MDR, FDA compliance workflows
Business & Growthbusiness-growth/CLAUDE.mdCustomer success, sales engineering, revenue operations
Financefinance/CLAUDE.mdFinancial analysis, DCF valuation, budgeting, forecasting
Standards Librarystandards/CLAUDE.mdCommunication, quality, git, security standards
Templatestemplates/CLAUDE.mdTemplate 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/           # 6 marketing skills + Python tools
├── product-team/              # 5 product skills + Python tools
├── engineering-team/          # 18 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
├── business-growth/           # 3 business & growth skills + Python tools
├── finance/                   # 1 finance skill + Python tools
├── 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

Branch Strategy: feature → dev → main (PR only)

Branch Protection Active: Main branch requires PR approval. Direct pushes blocked.

Quick Start

# 1. Always start from dev
git checkout dev
git pull origin dev

# 2. Create feature branch
git checkout -b feature/agents-{name}

# 3. Work and commit (conventional commits)
feat(agents): implement cs-{agent-name}
fix(tool): correct calculation logic
docs(workflow): update branch strategy

# 4. Push and create PR to dev
git push origin feature/agents-{name}
gh pr create --base dev --head feature/agents-{name}

# 5. After approval, PR merges to dev
# 6. Periodically, dev merges to main via PR

Branch Protection Rules:

  • ✅ Main: Requires PR approval, no direct push
  • ✅ Dev: Unprotected, but PRs recommended
  • ✅ All: Conventional commits enforced

See documentation/WORKFLOW.md for complete workflow guide. See standards/git/git-workflow-standards.md for commit standards.

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 package at 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: ✅ COMPLETE - All 6 days finished, 5 agents deployed

Deliverables:

  • 5 production agents: cs-content-creator, cs-demand-gen-specialist, cs-ceo-advisor, cs-cto-advisor, cs-product-manager
  • 1 agent template for future development
  • Modular documentation structure (main + 9 domain CLAUDE.md files)
  • Branch protection and workflow documentation

Progress Tracking:

  • Sprint Plan - Day-by-day execution plan
  • Sprint Context - Goals, scope, risks
  • Sprint Progress - Real-time auto-updating tracker

Roadmap

Phase 1-2 Complete: 53 production-ready skills deployed

  • Marketing (6), C-Level (2), Product (5), PM (6), Engineering (18), RA/QM (12), Business & Growth (3), Finance (1)
  • 87+ Python automation tools, 104+ reference guides
  • Complete enterprise coverage from marketing through regulatory compliance, sales, customer success, and finance

Next Priorities:

  • Phase 3 (Q2 2026): Marketing expansion - SEO optimizer, social media manager, growth marketer
  • Phase 4 (Q3 2026): Specialized domains - Mobile, blockchain, web3, advanced analytics

Target: 60+ skills by Q3 2026

See domain-specific roadmaps in each skill folder's README.md or roadmap files.

Key Principles

  1. Skills are products - Each skill deployable as standalone package
  2. Documentation-driven - Success depends on clear, actionable docs
  3. Algorithm over AI - Use deterministic analysis (code) vs LLM calls
  4. Template-heavy - Provide ready-to-use templates users customize
  5. 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: February 2026 Current Sprint: sprint-11-05-2025 (Skill-Agent Integration Phase 1-2) Status: 53 skills deployed, agent system in development

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