skills-ws
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87 agent skills for AI coding assistants — marketing, growth, web3, dev, design & operations. Built for OpenClaw, Claude Code, Cursor, and Codex.
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## Contents
- 3. Understanding the Pipeline
- 4-Phase Architecture
- What Each Phase Does
## 3. Understanding the Pipeline
### 4-Phase Architecture
```
Phase 1: RECONNAISSANCE
├── Pre-Recon (source code analysis with configured LLM)
│ └── Outputs: code_analysis_deliverable.md
└── Recon (attack surface mapping with Playwright + Nmap)
└── Outputs: recon_deliverable.md
Phase 2: VULNERABILITY ANALYSIS (5 parallel agents)
├── Injection Analysis → injection_analysis.md + exploitation_queue.json
├── XSS Analysis → xss_analysis.md + exploitation_queue.json
├── Auth Analysis → auth_analysis.md + exploitation_queue.json
├── SSRF Analysis → ssrf_analysis.md + exploitation_queue.json
└── AuthZ Analysis → authz_analysis.md + exploitation_queue.json
Phase 3: EXPLOITATION (5 parallel agents, conditional)
├── Injection Exploit → injection_exploitation_evidence.md
├── XSS Exploit → xss_exploitation_evidence.md
├── Auth Exploit → auth_exploitation_evidence.md
├── SSRF Exploit → ssrf_exploitation_evidence.md
└── AuthZ Exploit → authz_exploitation_evidence.md
Phase 4: REPORTING
└── Security-Assessment-Report.md
```
### What Each Phase Does
**Pre-Recon** reads source code to understand the application architecture, identify entry points, map data flows, and find potential vulnerability patterns before any network interaction.
**Recon** maps the live attack surface: crawls the app with a headless browser, enumerates API endpoints, identifies technologies, scans for open ports.
**Vulnerability Analysis** agents work in parallel, each specializing in one category. They combine source code knowledge with recon data to hypothesize specific vulnerabilities and create exploitation queues.
**Exploitation** agents receive the queues and attempt real attacks using browser automation (Playwright) and HTTP requests. Only proven exploits are included in the final report.