I'll fetch the README file from the Vuln-Z-Claw repository and translate it to English for you.I can see the README is actually in Chinese (Simplified), not Japanese. Let me translate it to English for you:

AI-powered penetration testing CLI tool — speak plainly, find vulnerabilities.

This project is a standalone AI penetration testing Agent.

Built on LLM Agent + MCP toolchain + penetration skill orchestration, compatible with OpenAI / MiniMax / DeepSeek and other compatible models. Accepts natural language input → automatically completes the entire "information gathering → vulnerability discovery → exploitation → report generation" workflow.

Input natural language, and AI automatically executes the full penetration testing workflow:

User Input: Perform penetration testing on http://target.example.com

VulnClaw automatically executes:
  Round 1:  Information Gathering → Fingerprinting, port scanning, directory enumeration
  Round 2:  Vulnerability Discovery → Injection point detection, known CVEs, config flaws
  Round 3:  Exploitation → PoC verification, privilege escalation
  Round 4:  Report Generation → Structured report + Python PoC script

Suitable for authorized penetration testing, CTF competitions, security education, red team exercises, etc.

• Goal-driven solver engine (default) — Abandons fixed-round workflows, uses "goal achieved / frontier exploration exhausted / safety budget" as termination conditions, auto-converges
• Blackboard graph state space search — Models penetration as search from origin to goal: Fact (confirmed facts) + Intent (exploration directions), structurally prevents "spinning in place"
• Evidence-level hallucination gate — Claims of flags/conclusions must appear verbatim in real tool output to be trusted; prevents fabricated flag victories
• Natural language driven — Describe penetration intent in plain language, automatically identify phases and tools
• 13 LLM Providers — OpenAI / MiniMax / DeepSeek / Zhipu / Moonshot / Qwen / SiliconFlow / Doubao / Baichuan / Stepfun / SenseTime / Yi, one-click switch
• MCP toolchain — 4 MCP services: fetch / memory work out-of-the-box locally, chrome-devtools / burp integrate external MCP services for browser automation and HTTP sniffing/replay
• AI Agent core — OpenAI-compatible protocol + Tool Calling + autonomous penetration loop
• Structured reasoning + adaptive reflection — Known facts/constraints/attack chains structured and injected into prompts; failures auto-classified with L0-L4 progressive payload bypass strategies
• Vulnerability detection plugin system — Low-coupling plugin runtime + built-in read-only Web plugins, results auto-merged into report pipeline (vulnclaw plugins)
• 21 penetration skills — 7 core + 14 specialized skills (including CTF Web/Crypto/Misc, OSINT recon, security knowledge), with 180 reference documents
• Encode/decode & encryption tools — 29 operations (Base64/Hex/URL/AES/JWT/Morse etc.), LLM can precisely invoke without guessing
• Python code execution — Built-in python_execute tool for payload construction and response parsing
• Persistent penetration testing — Cycle loops (default 100 rounds/cycle × 10 cycles = 1000 rounds), auto-generate reports per cycle until manual stop
• Reasoning process display control — think on/off toggle to show/hide LLM thinking process, default off, clean output shows conclusions only
• Sandbox mode prompts — Unlock AI security testing capabilities, CTF/authorized penetration scenarios only
• Auto-report & PoC — Generate structured Markdown reports and runnable Python PoC scripts
• Web UI mode — vulnclaw web launches local Web interface, browser-based full penetration testing workflow, default 127.0.0.1:7788
• Security knowledge base — Pre-built knowledge base module with seed data, CLI-maintainable

The old autonomous penetration was fixed-round loops (run N rounds then stop), easily falling into "repeatedly requesting same page, claiming to test injection but not sending packets" dead loops on weak models. The new version reconstructs penetration as directed search from origin (target) to goal (get flag / shell / confirm critical vulnerability) using two primitives:

Loop structure:

REASON (read full graph) → Goal achieved? / Propose new exploration direction / No proposal
        │
EXPLORE (take one Intent) → Actually execute with tools → Write confirmed conclusion back as Fact
        │
Terminate: Goal achieved / Exploration frontier exhausted / Safety budget exceeded

Why it structurally prevents spinning: Once "homepage is login form" becomes a Fact, Reason won't propose "go view homepage" again, but rather "test SQL injection"; each Intent is taken once, concluded once, preventing repetition.

Weak models often fabricate flags from thin air. The new engine records all real tool output (HTTP response bodies, python_execute output) as the only trusted evidence:

• Conclusion gate: Flags claimed in Explore conclusions must appear verbatim in real tool output → marked as [unverified] if not
• Completion gate: When Reason declares "goal achieved", if the goal requires flag but real output contains none → reject completion, continue exploring
• Instant convergence: Once evidence-verified flag obtained, complete immediately, no more verification rounds

# Install from PyPI (recommended)
pip install vulnclaw

# Install from source
git clone https://github.com/Unclecheng-li/VulnClaw.git
cd VulnClaw
pip install -e .

# 1. Choose provider (auto-fills Base URL and model name)
vulnclaw config provider minimax   (or openai/deepseek/zhipu/moonshot/qwen/siliconflow)

# 1.2 (optional) Customize Base URL or model name
vulnclaw config set llm.base_url https://your-own-api.example.com/v1 
vulnclaw config set llm.model your-model-name

# 2. Set API Key
vulnclaw config set llm.api_key sk-your-key-here

# 3. Default: open original CLI / REPL
vulnclaw

# 4. Optional: open TUI workbench
vulnclaw tui

vulnclaw doctor

vulnclaw --help    # View all commands

Commands:
    run           🚀 One-command full workflow penetration testing
    persistent    🔄 Continuous penetration testing (100 rounds/cycle)
    recon         🔍 Information gathering phase only
    scan          🔎 Execute vulnerability scanning phase
    exploit       💥 Execute exploitation phase
    report        📝 Generate report from session records
    repl          💬 Launch classic REPL interaction interface
    config        ⚙️  Manage configuration (set/get/list/provider)
    init          🔧 Initialize configuration
    doctor        🏥  Check runtime environment
    tui           🖥️  Open terminal GUI workbench
    web           🌐 Launch local Web UI

VulnClaw supports all OpenAI-compatible APIs, with 8 built-in provider presets:

vulnclaw config provider --list    # View all providers
vulnclaw config provider minimax   # One-click switch

VulnClaw is for authorized security testing only. Before using this tool, ensure:

1. You have explicit authorization to test the target system
2. Testing scope has been confirmed in writing with the target owner
3. You comply with local laws and regulations

Unauthorized penetration testing is illegal. The tool author is not responsible for misuse.

MIT License

This is an AI-powered penetration testing framework that leverages LLMs + MCP toolchain to automate security assessments. It's designed for authorized testing professionals and CTF competitors, supporting multiple LLM providers and featuring advanced anti-hallucination mechanisms to ensure reliable vulnerability detection.