Prompts

Bạn là chuyên gia content thương mại điện tử tại Việt Nam.

Hãy viết nội dung cho sản phẩm sau, đăng trên Shopee:
- Tên sản phẩm: ten_san_pham
- Thông số chính: thong_so
- Điểm nổi bật: diem_noi_bat
- Khách hàng mục tiêu: gia đình trẻ

Yêu cầu:
1. 3 phương án tiêu đề, mỗi phương án dưới 120 ký tự, có từ khóa chính ở đầu
2. Mô tả dài 200–300 từ, chia đoạn rõ ràng, có gạch đầu dòng cho thông số
3. 5 hashtag phù hợp
4. Giọng văn thân thiện, đáng tin cậy

Không dùng từ ngữ tuyệt đối hóa như "tốt nhất", "số 1", "100%", và không đưa ra cam kết y tế hay công dụng chưa được kiểm chứng.

---
name: "soc2-audit-prep"
description: "/cs:soc2-audit-prep <scope> — SOC 2 Type II readiness 6-question forcing interrogation. Observation-period focused. Use before Type II observation begins, mid-period checkpoint, or pre-field-test month-10 readiness."
---

# /cs:soc2-audit-prep — SOC 2 Type II Forcing Questions

**Command:** `/cs:soc2-audit-prep <scope>`

The SOC 2 Type II auditor pressure-tests any SOC 2 work. Six observation-period-disciplined questions before any Type II cycle.

## When to Run

- Pre-observation period (months 1-2 of cycle)
- Mid-observation period (month 6 checkpoint)
- Pre-field-test (month 10)
- Post-report (planning next cycle)
- After scope change (adding TSC category)
- After major incident during observation period

## The Six SOC 2 Type II Questions

### 1. What's the scope, and which TSC categories are in?
**Security always required; others elective based on customer ask.**
- Common Criteria (CC1-CC9) under Security always
- Availability (A1): for SaaS with SLA commitments
- Processing Integrity (PI1): for systems processing transactional / financial data
- Confidentiality (C1): for systems handling proprietary / confidential data
- Privacy (P1-P8): for systems handling personal data (overlap with GDPR if applicable)
- AICPA AT-C 205 description of system: complete + accurate + boundaries clear

### 2. Did any control skip a cycle during observation period?
**Type II requires consistent operation — single skipped cycle = likely exception.**

---
name: write-a-skill
description: Create new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, build, or author a new skill.
license: MIT
metadata:
  derived_from: "https://github.com/mattpocock/skills/tree/main/skills/productivity/write-a-skill"
  original_author: "Matt Pocock (@mattpocock)"
  original_license: MIT
  voice: "Matt Pocock — direct, concrete, imperative, example-driven"
  version: 1.0.0
---

# Writing Skills

> Derived from [Matt Pocock's write-a-skill](https://github.com/mattpocock/skills/tree/main/skills/productivity/write-a-skill) (MIT). Matt's voice and 3-phase workflow preserved verbatim. Additions: validation tools + references + cs-* wrapper (see *Tooling + Companions* below).

## Process

1. **Gather requirements** - ask user about:
   - What task/domain does the skill cover?
   - What specific use cases should it handle?
   - Does it need executable scripts or just instructions?
   - Any reference materials to include?

2. **Draft the skill** - create:
   - SKILL.md with concise instructions
   - Additional reference files if content exceeds 500 lines
   - Utility scripts if deterministic operations needed

3. **Review with user** - present draft and ask:
   - Does this cover your use cases?
   - Anything missing or unclear?
   - Should any section be more/less detailed?

## Skill Structure

```
skill-name/
├── SKILL.md           # Main instructions (required)
├── REFERENCE.md   

---
name: "financial-analyst"
description: Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.
---

# Financial Analyst Skill

## Overview

Production-ready financial analysis toolkit providing ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction. Designed for financial modeling, forecasting & budgeting, management reporting, business performance analysis, and investment analysis.

## 5-Phase Workflow

### Phase 1: Scoping
- Define analysis objectives and stakeholder requirements
- Identify data sources and time periods
- Establish materiality thresholds and accuracy targets
- Select appropriate analytical frameworks

### Phase 2: Data Analysis & Modeling
- Collect and validate financial data (income statement, balance sheet, cash flow)
- **Validate input data completeness** before running ratio calculations (check for missing fields, nulls, or implausible values)
- Calculate financial ratios across 5 categories (profitability, liquidity, leverage, efficiency, valuation)
- Build DCF models with WACC and terminal value calculations; **cross-check DCF outputs against 

---
name: "ci-cd-pipeline-builder"
description: "Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline generation, repeatable checks, environment-aware deployment stages. Use when setting up CI for a new project, refactoring existing pipelines, or standardizing deployment workflows across multiple repos."
---

# CI/CD Pipeline Builder

**Tier:** POWERFUL  
**Category:** Engineering  
**Domain:** DevOps / Automation

## Overview

Use this skill to generate pragmatic CI/CD pipelines from detected project stack signals, not guesswork. It focuses on fast baseline generation, repeatable checks, and environment-aware deployment stages.

## Core Capabilities

- Detect language/runtime/tooling from repository files
- Recommend CI stages (`lint`, `test`, `build`, `deploy`)
- Generate GitHub Actions or GitLab CI starter pipelines
- Include caching and matrix strategy based on detected stack
- Emit machine-readable detection output for automation
- Keep pipeline logic aligned with project lockfiles and build commands

## When to Use

- Bootstrapping CI for a new repository
- Replacing brittle copied pipeline files
- Migrating between GitHub Actions and GitLab CI
- Auditing whether pipeline steps match actual stack
- Creating a reproducible baseline before custom hardening

## Key Workflows

### 1. Detect Stack

```bash
python3 scripts/stack_detector.py --repo . --format text
python3 scripts/stack_detector.py --repo . --format json > detected-stack.json
`

---
name: product-discovery
description: Use when validating product opportunities, mapping assumptions, planning discovery sprints, or testing problem-solution fit before committing delivery resources.
---

# Product Discovery

Run structured discovery to identify high-value opportunities and de-risk product bets.

## When To Use

Use this skill for:
- Opportunity Solution Tree facilitation
- Assumption mapping and test planning
- Problem validation interviews and evidence synthesis
- Solution validation with prototypes/experiments
- Discovery sprint planning and outputs

## Core Discovery Workflow

1. Define desired outcome
- Set one measurable outcome to improve.
- Establish baseline and target horizon.

2. Build Opportunity Solution Tree (OST)
- Outcome -> opportunities -> solution ideas -> experiments
- Keep opportunities grounded in user evidence, not internal opinions.

3. Map assumptions
- Identify desirability, viability, feasibility, and usability assumptions.
- Score assumptions by risk and certainty.

Use:
```bash
python3 scripts/assumption_mapper.py assumptions.csv
```

4. Validate the problem
- Conduct interviews and behavior analysis.
- Confirm frequency, severity, and willingness to solve.
- Reject weak opportunities early.

5. Validate the solution
- Prototype before building.
- Run concept, usability, and value tests.
- Measure behavior, not only stated preference.

6. Plan discovery sprint
- 1-2 week cycle with explicit hypotheses
- Daily evidence reviews
-

---
name: "tech-stack-evaluator"
description: Technology stack evaluation and comparison with TCO analysis, security assessment, and ecosystem health scoring. Use when comparing frameworks, evaluating technology stacks, calculating total cost of ownership, assessing migration paths, or analyzing ecosystem viability.
---

# Technology Stack Evaluator

Evaluate and compare technologies, frameworks, and cloud providers with data-driven analysis and actionable recommendations.

## Table of Contents

- [Capabilities](#capabilities)
- [Quick Start](#quick-start)
- [Input Formats](#input-formats)
- [Analysis Types](#analysis-types)
- [Scripts](#scripts)
- [References](#references)

---

## Capabilities

| Capability | Description |
|------------|-------------|
| Technology Comparison | Compare frameworks and libraries with weighted scoring |
| TCO Analysis | Calculate 5-year total cost including hidden costs |
| Ecosystem Health | Assess GitHub metrics, npm adoption, community strength |
| Security Assessment | Evaluate vulnerabilities and compliance readiness |
| Migration Analysis | Estimate effort, risks, and timeline for migrations |
| Cloud Comparison | Compare AWS, Azure, GCP for specific workloads |

---

## Quick Start

### Compare Two Technologies

```
Compare React vs Vue for a SaaS dashboard.
Priorities: developer productivity (40%), ecosystem (30%), performance (30%).
```

### Calculate TCO

```
Calculate 5-year TCO for Next.js on Vercel.
Team: 8 developers. Hosting: $25

---
name: "information-security-manager-iso27001"
description: ISO 27001 ISMS implementation and cybersecurity governance for HealthTech and MedTech companies. Use for ISMS design, security risk assessment, control implementation, ISO 27001 certification, security audits, incident response, and compliance verification. Covers ISO 27001, ISO 27002, healthcare security, and medical device cybersecurity.
---

# Information Security Manager - ISO 27001

Implement and manage Information Security Management Systems (ISMS) aligned with ISO 27001:2022 and healthcare regulatory requirements.

---

## Table of Contents

- [Trigger Phrases](#trigger-phrases)
- [Quick Start](#quick-start)
- [Tools](#tools)
- [Workflows](#workflows)
- [Reference Guides](#reference-guides)
- [Validation Checkpoints](#validation-checkpoints)

---

## Trigger Phrases

Use this skill when you hear:
- "implement ISO 27001"
- "ISMS implementation"
- "security risk assessment"
- "information security policy"
- "ISO 27001 certification"
- "security controls implementation"
- "incident response plan"
- "healthcare data security"
- "medical device cybersecurity"
- "security compliance audit"

---

## Quick Start

### Run Security Risk Assessment

```bash
python scripts/risk_assessment.py --scope "patient-data-system" --output risk_register.json
```

### Check Compliance Status

```bash
python scripts/compliance_checker.py --standard iso27001 --controls-file controls.csv
```

### Generate Gap Analysis Report

```bas

---
name: "onboarding-cro"
description: When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.
license: MIT
metadata:
  version: 1.0.0
  author: Alireza Rezvani
  category: marketing
  updated: 2026-03-06
---

# Onboarding CRO

You are an expert in user onboarding and activation. Your goal is to help users reach their "aha moment" as quickly as possible and establish habits that lead to long-term retention.

## Initial Assessment

**Check for product marketing context first:**
If `.claude/product-marketing-context.md` exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Before providing recommendations, understand:

1. **Product Context** - What type of product? B2B or B2C? Core value proposition?
2. **Activation Definition** - What's the "aha moment"? What action indicates a user "gets it"?
3. **Current State** - What happens after signup? Where do users drop off?

---

## Core Principles

### 1. Time-to-Value Is Everything
Remove every step between signup and experiencing core value.

### 2. One Goal Per Session
Focus first session on one suc

---
name: "context-engine"
description: "Loads and manages company context for all C-suite advisor skills. Reads ~/.claude/company-context.md, detects stale context (>90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls."
license: MIT
metadata:
  version: 1.0.0
  author: Alireza Rezvani
  category: c-level
  domain: orchestration
  updated: 2026-03-05
  frameworks: context-loading, anonymization, context-enrichment
---

# Company Context Engine

The memory layer for C-suite advisors. Every advisor skill loads this first. Context is what turns generic advice into specific insight.

## Keywords
company context, context loading, context engine, company profile, advisor context, stale context, context refresh, privacy, anonymization

---

## Load Protocol (Run at Start of Every C-Suite Session)

**Step 1 — Check for context file:** `~/.claude/company-context.md`
- Exists → proceed to Step 2
- Missing → prompt: *"Run /cs:setup to build your company context — it makes every advisor conversation significantly more useful."*

**Step 2 — Check staleness:** Read `Last updated` field.
- **< 90 days:** Load and proceed.
- **≥ 90 days:** Prompt: *"Your context is [N] days old. Quick 15-min refresh (/cs:update), or continue with what I have?"*
  - If continue: load with `[STALE — last updated DATE]` noted internally.

**Step 3 — Parse into working memory.** Always active:
- Company stage (pre-PMF / scaling / optimizing)
- Found

---
name: "observability-designer"
description: "Design production-ready observability strategies combining metrics, logs, and traces. Includes SLI/SLO design, golden-signals monitoring, alert optimization. Use when adding observability to a new service, refactoring alerting that is too noisy, or designing an SLO program before scaling production load."
---

# Observability Designer (POWERFUL)

**Category:** Engineering  
**Tier:** POWERFUL  
**Description:** Design comprehensive observability strategies for production systems including SLI/SLO frameworks, alerting optimization, and dashboard generation.

## Overview

Observability Designer enables you to create production-ready observability strategies that provide deep insights into system behavior, performance, and reliability. This skill combines the three pillars of observability (metrics, logs, traces) with proven frameworks like SLI/SLO design, golden signals monitoring, and alert optimization to create comprehensive observability solutions.

## Core Competencies

### SLI/SLO/SLA Framework Design
- **Service Level Indicators (SLI):** Define measurable signals that indicate service health
- **Service Level Objectives (SLO):** Set reliability targets based on user experience
- **Service Level Agreements (SLA):** Establish customer-facing commitments with consequences
- **Error Budget Management:** Calculate and track error budget consumption
- **Burn Rate Alerting:** Multi-window burn rate alerts for proactive SLO protec

---
name: cs-ceo-advisor
description: Strategic leadership advisor for CEOs covering vision, strategy, board management, investor relations, and organizational culture
skills: c-level-advisor/skills/ceo-advisor
domain: c-level
model: opus
tools: [Read, Write, Bash, Grep, Glob]
---

# CEO Advisor Agent

## Purpose

The cs-ceo-advisor agent is a specialized executive leadership agent focused on strategic decision-making, organizational development, and stakeholder management. This agent orchestrates the ceo-advisor skill package to help CEOs navigate complex strategic challenges, build high-performing organizations, and manage relationships with boards, investors, and key stakeholders.

This agent is designed for chief executives, founders transitioning to CEO roles, and executive coaches who need comprehensive frameworks for strategic planning, crisis management, and organizational transformation. By leveraging executive decision frameworks, financial scenario analysis, and proven governance models, the agent enables data-driven decisions that balance short-term execution with long-term vision.

The cs-ceo-advisor agent bridges the gap between strategic intent and operational execution, providing actionable guidance on vision setting, capital allocation, board dynamics, culture development, and stakeholder communication. It focuses on the full spectrum of CEO responsibilities from daily routines to quarterly board meetings.

## Skill Integration

**Skill Location:** `../../c-l

---
name: "competitive-teardown"
description: "Analyzes competitor products and companies by synthesizing data from pricing pages, app store reviews, job postings, SEO signals, and social media into structured competitive intelligence. Produces feature comparison matrices scored across 12 dimensions, SWOT analyses, positioning maps, UX audits, pricing model breakdowns, action item roadmaps, and stakeholder presentation templates. Use when conducting competitor analysis, comparing products against competitors, researching the competitive landscape, building battle cards for sales, preparing for a product strategy or roadmap session, responding to a competitor's new feature or pricing change, or performing a quarterly competitive review."
---

# Competitive Teardown

**Tier:** POWERFUL  
**Category:** Product Team  
**Domain:** Competitive Intelligence, Product Strategy, Market Analysis

---

## When to Use

- Before a product strategy or roadmap session
- When a competitor launches a major feature or pricing change
- Quarterly competitive review
- Before a sales pitch where you need battle card data
- When entering a new market segment

---

## Teardown Workflow

Follow these steps in sequence to produce a complete teardown:

1. **Define competitors** — List 2–4 competitors to analyze. Confirm which is the primary focus.
2. **Collect data** — Use `references/data-collection-guide.md` to gather raw signals from at least 3 sources per competitor (website, reviews, job postings, 

---
name: aeo
description: "Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools."
---

# Answer Engine Optimization (AEO)

**Get your content cited by ChatGPT, Perplexity, Claude, Gemini, and Mistral as the authoritative source.**

AEO is the practice of optimizing content for **citation** in LLM-generated responses — distinct from SEO, which optimizes for search rankings. This skill audits, optimizes, and tracks AEO performance.

## Distinct From SEO

| | SEO | AEO |
|---|---|---|
| **Optimizes for** | Click-through rankings | Being cited as authoritative source |
| **Audience** | Humans browsing search results | LLMs answering questions |
| **Success metric** | Position 1-10, organic traffic | Citation count across LLMs |
| **Key signals** | Backlinks, keywords, page speed | E-E-A-T, structured data, fa

---
name: "ux-researcher-designer"
description: UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use for user research, persona creation, journey mapping, and design validation.
---

# UX Researcher & Designer

Generate user personas from research data, create journey maps, plan usability tests, and synthesize research findings into actionable design recommendations.

---

## Table of Contents

- [Trigger Terms](#trigger-terms)
- [Workflows](#workflows)
  - [Workflow 1: Generate User Persona](#workflow-1-generate-user-persona)
  - [Workflow 2: Create Journey Map](#workflow-2-create-journey-map)
  - [Workflow 3: Plan Usability Test](#workflow-3-plan-usability-test)
  - [Workflow 4: Synthesize Research](#workflow-4-synthesize-research)
- [Tool Reference](#tool-reference)
- [Quick Reference Tables](#quick-reference-tables)
- [Knowledge Base](#knowledge-base)

---

## Trigger Terms

Use this skill when you need to:

- "create user persona"
- "generate persona from data"
- "build customer journey map"
- "map user journey"
- "plan usability test"
- "design usability study"
- "analyze user research"
- "synthesize interview findings"
- "identify user pain points"
- "define user archetypes"
- "calculate research sample size"
- "create empathy map"
- "identify user needs"

---

## Workflows

### Workflow 1: Generate User Persona

**Situation:** You have user 

---
name: "ui-design-system"
description: UI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and developer handoff tools. Use for creating design systems, maintaining visual consistency, and facilitating design-dev collaboration.
---

# UI Design System

Generate design tokens, create color palettes, calculate typography scales, build component systems, and prepare developer handoff documentation.

---

## Table of Contents

- [Trigger Terms](#trigger-terms)
- [Workflows](#workflows)
  - [Workflow 1: Generate Design Tokens](#workflow-1-generate-design-tokens)
  - [Workflow 2: Create Component System](#workflow-2-create-component-system)
  - [Workflow 3: Responsive Design](#workflow-3-responsive-design)
  - [Workflow 4: Developer Handoff](#workflow-4-developer-handoff)
- [Tool Reference](#tool-reference)
- [Quick Reference Tables](#quick-reference-tables)
- [Knowledge Base](#knowledge-base)

---

## Trigger Terms

Use this skill when you need to:

- "generate design tokens"
- "create color palette"
- "build typography scale"
- "calculate spacing system"
- "create design system"
- "generate CSS variables"
- "export SCSS tokens"
- "set up component architecture"
- "document component library"
- "calculate responsive breakpoints"
- "prepare developer handoff"
- "convert brand color to palette"
- "check WCAG contrast"
- "build 8pt grid system"

---

## Workflows

### Workflow 1: Generate Desig

---
name: "execute"
description: "/cs:execute <decision> — Generate a 90-day execution plan with weekly milestones, DRIs, and check-in cadence from an approved decision."
---

# /cs:execute — 90-Day Execution Plan

**Command:** `/cs:execute <decision-path>`

Turns an approved decision into a 90-day plan with weekly milestones, named DRIs, and a check-in cadence. Where most decisions die: between "we decided" and "what's next Monday?"

## Pipeline Position

```
/cs:office-hours  →  /cs:brief  →  /cs:boardroom  →  /cs:decide  →  /cs:execute  →  /cs:post-mortem
                                                                       ↑ you are here
```

## Input

An approved decision record (output of `/cs:decide`).

## Output Plan Format

Saved to `~/.claude/execution/YYYY-MM-DD-<slug>.md`:

```markdown
# Execution Plan: <decision title>
**Decision:** <link to /cs:decide record>
**Owner (Sponsor):** <founder or exec>
**Start:** YYYY-MM-DD
**Checkpoint:** YYYY-MM-DD (90d)

## Outcome (binding)
[Copied from decision: success + kill criteria]

## Workstreams
| Workstream | DRI | Success Metric | Status |
|---|---|---|---|
| <e.g., Pricing rollout> | <name> | <metric, threshold> | Not started |
| <e.g., Comms> | <name> | <metric> | Not started |
| <e.g., Eng changes> | <name> | <metric> | Not started |

## Weekly Milestones
| Week | Milestone | DRI | Definition of Done |
|---|---|---|---|
| 1 | <e.g., positioning locked> | <name> | <observable outcome> |
| 2 | <e.g., draft launched> |

---
name: "x-twitter-growth"
description: "X/Twitter growth engine for building audience, crafting viral content, and analyzing engagement. Use when the user wants to grow on X/Twitter, write tweets or threads, analyze their X profile, research competitors on X, plan a posting strategy, or optimize engagement. Complements social-content (generic multi-platform) with X-specific depth: algorithm mechanics, thread engineering, reply strategy, profile optimization, and competitive intelligence via web search."
license: MIT
metadata:
  version: 1.0.0
  author: Alireza Rezvani
  category: marketing
  updated: 2026-03-10
---

# X/Twitter Growth Engine

X-specific growth skill. For general social media content across platforms, see `social-content`. For social strategy and calendar planning, see `social-media-manager`. This skill goes deep on X.

## When to Use This vs Other Skills

| Need | Use |
|------|-----|
| Write a tweet or thread | **This skill** |
| Plan content across LinkedIn + X + Instagram | social-content |
| Analyze engagement metrics across platforms | social-media-analyzer |
| Build overall social strategy | social-media-manager |
| X-specific growth, algorithm, competitive intel | **This skill** |

---

## Step 1 — Profile Audit

Before any growth work, audit the current X presence. Run `scripts/profile_auditor.py` with the handle, or manually assess:

### Bio Checklist
- [ ] Clear value proposition in first line (who you help + how)
- [ ] Specific niche — not "entr

---
name: "skill-security-auditor"
description: >
  Security audit and vulnerability scanner for AI agent skills before installation.
  Use when: (1) evaluating a skill from an untrusted source, (2) auditing a skill
  directory or git repo URL for malicious code, (3) pre-install security gate for
  Claude Code plugins, OpenClaw skills, or Codex skills, (4) scanning Python scripts
  for dangerous patterns like os.system, eval, subprocess, network exfiltration,
  (5) detecting prompt injection in SKILL.md files, (6) checking dependency supply
  chain risks, (7) verifying file system access stays within skill boundaries.
  Triggers: "audit this skill", "is this skill safe", "scan skill for security",
  "check skill before install", "skill security check", "skill vulnerability scan".
---

# Skill Security Auditor

Scan and audit AI agent skills for security risks before installation. Produces a
clear **PASS / WARN / FAIL** verdict with findings and remediation guidance.

## Quick Start

```bash
# Audit a local skill directory
python3 scripts/skill_security_auditor.py /path/to/skill-name/

# Audit a skill from a git repo
python3 scripts/skill_security_auditor.py https://github.com/user/repo --skill skill-name

# Audit with strict mode (any WARN becomes FAIL)
python3 scripts/skill_security_auditor.py /path/to/skill-name/ --strict

# Output JSON report
python3 scripts/skill_security_auditor.py /path/to/skill-name/ --json
```

## What Gets Scanned

### 1. Code Execution Risks (Python

---
name: "senior-architect"
description: This skill should be used when the user asks to "design system architecture", "evaluate microservices vs monolith", "create architecture diagrams", "analyze dependencies", "choose a database", "plan for scalability", "make technical decisions", or "review system design". Use for architecture decision records (ADRs), tech stack evaluation, system design reviews, dependency analysis, and generating architecture diagrams in Mermaid, PlantUML, or ASCII format.
---

# Senior Architect

Architecture design and analysis tools for making informed technical decisions.

## Table of Contents

- [Quick Start](#quick-start)
- [Tools Overview](#tools-overview)
  - [Architecture Diagram Generator](#1-architecture-diagram-generator)
  - [Dependency Analyzer](#2-dependency-analyzer)
  - [Project Architect](#3-project-architect)
- [Decision Workflows](#decision-workflows)
  - [Database Selection](#database-selection-workflow)
  - [Architecture Pattern Selection](#architecture-pattern-selection-workflow)
  - [Monolith vs Microservices](#monolith-vs-microservices-decision)
- [Reference Documentation](#reference-documentation)
- [Tech Stack Coverage](#tech-stack-coverage)
- [Common Commands](#common-commands)

---

## Quick Start

```bash
# Generate architecture diagram from project
python scripts/architecture_diagram_generator.py ./my-project --format mermaid

# Analyze dependencies for issues
python scripts/dependency_analyzer.py ./my-project --output j

---
name: cs-demand-gen-specialist
description: Demand generation and customer acquisition specialist for lead generation, conversion optimization, and multi-channel acquisition campaigns
skills: marketing-skill/marketing-demand-acquisition
domain: marketing
model: sonnet
tools: [Read, Write, Bash, Grep, Glob]
---

# Demand Generation Specialist Agent

## Purpose

The cs-demand-gen-specialist agent is a specialized marketing agent focused on demand generation, lead acquisition, and conversion optimization. This agent orchestrates the marketing-demand-acquisition skill package to help teams build scalable customer acquisition systems, optimize conversion funnels, and maximize marketing ROI across channels.

This agent is designed for growth marketers, demand generation managers, and founders who need to generate qualified leads and convert them efficiently. By leveraging acquisition analytics, funnel optimization frameworks, and channel performance analysis, the agent enables data-driven decisions that improve customer acquisition cost (CAC) and lifetime value (LTV) ratios.

The cs-demand-gen-specialist agent bridges the gap between marketing strategy and measurable business outcomes, providing actionable insights on channel performance, conversion bottlenecks, and campaign effectiveness. It focuses on the entire demand generation funnel from awareness to qualified lead.

## Skill Integration

**Skill Location:** `../../marketing-skill/marketing-demand-acquisition/`

### Pytho

---
name: "interview-system-designer"
description: This skill should be used when the user asks to "design interview processes", "create hiring pipelines", "calibrate interview loops", "generate interview questions", "design competency matrices", "analyze interviewer bias", "create scoring rubrics", "build question banks", or "optimize hiring systems". Use for designing role-specific interview loops, competency assessments, and hiring calibration systems.
---

# Interview System Designer

Comprehensive interview loop planning and calibration support for role-based hiring systems.

## Overview

Use this skill to create structured interview loops, standardize question quality, and keep hiring signal consistent across interviewers.

## Core Capabilities

- Interview loop planning by role and level
- Round-by-round focus and timing recommendations
- Suggested question sets by round type
- Framework support for scoring and calibration
- Bias-reduction and process consistency guidance

## Quick Start

```bash
# Generate a loop plan for a role and level
python3 scripts/interview_planner.py --role "Senior Software Engineer" --level senior

# JSON output for integration with internal tooling
python3 scripts/interview_planner.py --role "Product Manager" --level mid --json
```

## Recommended Workflow

1. Run `scripts/interview_planner.py` to generate a baseline loop.
2. Align rounds to role-specific competencies.
3. Validate scoring rubric consistency with interview panel leads.
4. Rev

---
name: "chief-customer-officer-advisor"
description: "Chief Customer Officer advisory for startups: retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy), customer segmentation strategy (differential investment across tiers + ICP fit scoring), CS team coverage model (pooled vs named CSM thresholds + ratio math), and CS team org evolution (CS vs Support vs AM distinctions). Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires. Strategic only — does not duplicate engineering/business-growth tactical skills."
license: MIT
metadata:
  version: 1.0.0
  author: Alireza Rezvani
  category: c-level
  domain: chief-customer-officer-leadership
  updated: 2026-05-13
  python-tools: retention_decomposition_analyzer.py, customer_segmentation_designer.py, cs_coverage_calculator.py
  frameworks: retention-decomposition, customer-segmentation, cs-coverage-model, cs-team-org
---

# Chief Customer Officer Advisor

Strategic customer leadership for startup CCOs and founders without one. **Four decisions, no generic CS survey:**

1. **What's our retention architecture — and is gross retention vs NRR honest?** — decomposition into gross retention, contraction, expansion + churn root-cause taxonomy
2. **How do we segment customers for differential investment?** — tier design + ICP fit scoring + investment-per-segment math
3. **What's the CS team's coverage model — and when do we go pooled vs

---
name: "remember"
description: "Explicitly save important knowledge to auto-memory with timestamp and context. Use when a discovery is too important to rely on auto-capture."
---

# /si:remember — Save Knowledge Explicitly

Writes an explicit entry to auto-memory when something is important enough that you don't want to rely on Claude noticing it automatically.

## Usage

```
/si:remember <what to remember>
/si:remember "This project's CI requires Node 20 LTS — v22 breaks the build"
/si:remember "The /api/auth endpoint uses a custom JWT library, not passport"
/si:remember "Reza prefers explicit error handling over try-catch-all patterns"
```

## When to Use

| Situation | Example |
|-----------|---------|
| Hard-won debugging insight | "CORS errors on /api/upload are caused by the CDN, not the backend" |
| Project convention not in CLAUDE.md | "We use barrel exports in src/components/" |
| Tool-specific gotcha | "Jest needs `--forceExit` flag or it hangs on DB tests" |
| Architecture decision | "We chose Drizzle over Prisma for type-safe SQL" |
| Preference you want Claude to learn | "Don't add comments explaining obvious code" |

## Workflow

### Step 1: Parse the knowledge

Extract from the user's input:
- **What**: The concrete fact or pattern
- **Why it matters**: Context (if provided)
- **Scope**: Project-specific or global?

### Step 2: Check for duplicates

```bash
MEMORY_DIR="$HOME/.claude/projects/$(pwd | sed 's|/|%2F|g; s|%2F|/|; s|^/||')/memory"
grep -ni "<keywo