git:20260921.571f9e8 to git:20261007.6533a59

3 added, 3 removed. Audit A to A.

# AI Skills Library — Agent Instructions

## What This Repository Is

- This is the **universal AI skills library** — **339 production-ready skill packages across 17 professional domains** with **787 Python automation tools**, 76 agents (incl. 8 cross-domain personas), 27 slash commands, and 8 CI/CD workflows. It works with every major AI coding assistant: Claude Code, Cursor, Copilot, Codex / ChatGPT, Gemini CLI, Windsurf, Cline, Aider, Goose, and more.

+ This is the **universal AI skills library** — **339 production-ready skill packages across 17 professional domains** with **787 Python automation tools**, 77 agents (incl. 8 cross-domain personas), 27 slash commands, and 8 CI/CD workflows. It works with every major AI coding assistant: Claude Code, Cursor, Copilot, Codex / ChatGPT, Gemini CLI, Windsurf, Cline, Aider, Goose, and more.

**This is NOT a traditional application.** It's a library of self-contained skill packages meant to be extracted and deployed by users into their own workflows.

## Supported Platforms

| Platform | Config File | Status |

|----------|------------|--------|

| Claude Code | `CLAUDE.md` + `.claude-plugin/marketplace.json` | Primary |

| OpenAI Codex / ChatGPT | `AGENTS.md` (root + nested per-domain) | Full |

| Cursor | `.cursor/rules/*.mdc` (+ legacy `.cursorrules`) | Full |

| Gemini CLI | `GEMINI.md` + `.gemini/skills-index.json` | Full |

| GitHub Copilot | `.github/copilot-instructions.md` | Full |

| Windsurf | `.windsurfrules` | Full |

| Cline | `.clinerules` | Full |

| Goose | `.goosehints` | Full |

| Aider · Jules · RooCode / Kilo Code | `AGENTS.md` | Full |

> Codex and other AGENTS.md-aware agents also read **nested `AGENTS.md`/`CLAUDE.md` files** inside each

> domain folder for scoped guidance (e.g. `engineering/CLAUDE.md`, `project-management/CLAUDE.md`).

## Repository Structure (domain → skill count)

```

- ├── engineering/ # 82 skills — architecture, fullstack, DevOps, security, AI/ML, data, agent tooling

+ ├── engineering/ # 92 skills — architecture, fullstack, DevOps, security, AI/ML, data, agent tooling

├── project-management/ # 70 skills — discovery, delivery, career, strategy-frameworks/, gtm/, Jira/Linear/Notion

├── marketing/ # 41 skills — content, SEO/AEO, demand gen, brand, analytics

├── c-level-advisor/ # 31 skills — CEO/CTO/CFO/CMO/CRO/CPO/COO/CHRO/CISO + CAIO/CDO/CCO/GC/VPE

├── ra-qm-team/ # 27 skills — ISO 13485, MDR, FDA, SOC 2, GDPR, EU AI Act, NIS2, DORA, NIST CSF

├── business-growth/ # 20 skills — CRO, pricing, revenue ops, commercial

├── legal/ # 17 skills — EXPERIMENTAL: contracts, NDA, privacy, DPIA, breach response

├── product-team/ # 13 skills — RICE, OKRs, UX research, product analytics, Apple HIG

├── personal-productivity/ # 10 skills — resume, leads, meetings, invoices, email triage

├── vertical-advisors/ # 7 skills — fintech, healthtech, edtech, ecommerce, proptech, climate-tech, marketplace

├── data-analytics/ # 5 skills — analysis, BI, data science, ML ops

├── sales-success/ # 5 skills — account exec, sales ops, solutions architect

├── documents/ # 4 skills — docx, pdf, pptx, xlsx (stdlib OOXML)

├── hr-operations/ # 4 skills — talent, people analytics, HRBP

├── research/ # 4 skills — litreview, grants, patent, dossier

├── finance/ # 3 skills — financial analysis, DCF, forecasting

├── workflow/ # 2 skills — skill-router, handoff (meta-skills)

- ├── agents/ # 68 cs-* domain agents + 8 cross-domain personas

+ ├── agents/ # 69 cs-* domain agents + 8 cross-domain personas

├── scripts/ # Manifest builder (build_manifest.py) + skill installer

├── standards/ # Best-practices library

├── templates/ # Reusable templates + sample workflows

└── cli/skills.json # Machine-readable manifest (regenerated by build_manifest.py)

```

## Skill Package Pattern

Every skill follows the same structure:

```

skill-name/

├── SKILL.md # Master documentation with workflows (progressive disclosure: lean Tier-1 + on-demand references)

├── scripts/ # Python CLI tools (standard library, no ML/LLM calls)

├── references/ # Expert knowledge bases

└── assets/ # User-facing templates

```

Knowledge flows: `references/` → `SKILL.md` workflows → `scripts/` execution → `assets/` templates.

## Quick Install

```bash

# Browse available skills

python scripts/skill-installer.py list

# Install a skill

python scripts/skill-installer.py install senior-fullstack --agent claude

python scripts/skill-installer.py install content-creator --agent cursor

python scripts/skill-installer.py install ceo-advisor --agent codex

# Keep skills up to date

python scripts/skill-installer.py update

```

After adding/removing/renaming any skill, regenerate the manifest so every platform surface stays in sync:

```bash

python scripts/build_manifest.py # rewrites cli/skills.json + registry.json

```

## Code Style

- **Python scripts:** Standard library only, CLI-first with argparse, JSON + human-readable output

- **Markdown:** YAML frontmatter on all SKILL.md files, descriptions ≤ ~60 tokens, consistent formatting

- **Commits:** Conventional commits — `feat(domain):`, `fix(tool):`, `docs(skill):`

## Key Principles

1. **Skills are products** — Each skill is deployable as a standalone package

2. **Documentation-driven** — Clear, actionable docs over generic advice

3. **Algorithm over AI** — Deterministic analysis (Python scripts) over LLM calls

4. **Template-heavy** — Ready-to-use templates users customize

5. **Self-contained** — No dependencies between skills

## Anti-Patterns

- Creating dependencies between skills

- Adding complex build systems or test frameworks

- Generic advice instead of specific, actionable frameworks

- LLM/ML calls in scripts (defeats portability)

- Over-documenting file structure