uv tool install mirdan                  # Install mirdan
mirdan llm setup                        # Auto-installs backend, downloads model, configures
mirdan init --claude-code               # or --cursor
# Done. Quality enforcement + local intelligence is now automatic.

mirdan llm setup              # Detects hardware, installs backend, downloads model, configures
mirdan init --claude-code     # or --cursor
mirdan llm status             # Verify it's working

API_KEY = "sk-proj-abc123456789"           # SEC001: hardcoded API key
def get_users(user_id):
    query = f"SELECT * FROM users WHERE id={user_id}"  # SEC005 + AI008: SQL injection
    result = eval(user_input)              # PY001: code injection via eval()
    data = requests.get(url, verify=False) # SEC007: SSL verification disabled
    try:
        process(data)
    except:                                # PY003: bare except
        pass

uv tool install mirdan                   # Install mirdan
mirdan llm setup                         # Auto-installs LLM backend + downloads model

# Optional extras:
uv tool install 'mirdan[ast]'            # + tree-sitter for TS/JS AST analysis
uv tool install 'mirdan[enterprise]'     # + truststore for corporate SSL inspection

# Upgrade:
uv tool upgrade mirdan

# Or with pip:
pip install mirdan

mirdan init --claude-code    # Claude Code: hooks, rules, skills, agents
mirdan init --cursor         # Cursor: hooks, rules, AGENTS.md, BUGBOT.md
mirdan init --all            # Both IDEs

mirdan validate --file src/auth.py     # Validate a file
mirdan validate --staged               # Validate git staged changes
mirdan fix --file src/auth.py          # Auto-fix violations (pattern-based)
mirdan check --smart                   # Run lint + typecheck + test with LLM analysis
mirdan check --smart --fix src/        # Run checks AND auto-fix with local LLM
mirdan gate                            # CI/CD quality gate (exit 0 or 1)
mirdan scan --dependencies             # Check deps for known CVEs
mirdan scan --directory src/           # Discover codebase conventions
mirdan llm setup                       # Configure local LLM
mirdan llm status                      # Show LLM health, model, hardware
mirdan llm metrics                     # Token savings dashboard

┌──────────────────────────────────────────────────┐
│  Your AI Assistant (Claude Code / Cursor / etc)  │
│                                                  │
│  1. You type a coding task                       │
│  2. Hook triages task via local LLM ────┐        │
│  3. AI generates code with guidance     │        │
│  4. Hook runs lint/typecheck/test ◄─────┘        │
│  5. AI fixes only complex issues                 │
│  6. Quality gate passes → task complete          │
└──────────────────────────────────────────────────┘
         │                        ▲
         ▼                        │
┌──────────────────────────────────────────────────┐
│  Mirdan MCP Server + Local Intelligence Layer    │
│                                                  │
│  MCP Tools (unchanged):                          │
│  enhance_prompt         → Quality requirements   │
│  validate_code_quality  → 64 rules + LLM enrich │
│  validate_quick         → Fast security checks   │
│  get_quality_standards  → Language/framework ref  │
│  get_quality_trends     → Historical analysis    │
│  scan_dependencies      → CVE detection (OSV)    │
│  scan_conventions       → Convention discovery   │
│                                                  │
│  Local LLM (Gemma 4, runs on your machine):      │
│  Triage          → Classify tasks, save tokens   │
│  Check Runner    → Run ruff/mypy/pytest locally  │
│  Smart Validator → FP filtering, root causes     │
│  Auto-Fix        → Search/replace code fixes     │
│  HTTP Sidecar    → <5ms hook integration         │
└──────────────────────────────────────────────────┘

mirdan init --quality-profile enterprise
mirdan profile apply fintech          # Change later
mirdan profile suggest                # Let mirdan recommend one

mirdan init --claude-code

mirdan init --cursor

{
  "mcpServers": {
    "mirdan": {
      "command": "uvx",
      "args": ["mirdan"]
    }
  }
}

{
  "mcpServers": {
    "mirdan": {
      "command": "uvx",
      "args": ["mirdan"],
      "env": {
        "MIRDAN_HF_ENDPOINT": "https://artifactory.corp.com/hf",
        "MIRDAN_HF_TOKEN": "your-artifactory-token",
        "MIRDAN_SSL_CERT_FILE": "/path/to/corporate-ca-bundle.crt"
      }
    }
  }
}

{
  "mcpServers": {
    "mirdan": {
      "command": "uvx",
      "args": ["mirdan"]
    }
  }
}

name: Mirdan Quality Gate
on: [pull_request]

jobs:
  quality:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: astral-sh/setup-uv@v4
      - run: uv tool install mirdan
      - run: mirdan gate

- run: mirdan export --format sarif > results.sarif
- uses: github/codeql-action/upload-sarif@v3
  with:
    sarif_file: results.sarif

# .pre-commit-config.yaml
repos:
  - repo: local
    hooks:
      - id: mirdan
        name: mirdan quality gate
        entry: mirdan validate --staged --quick
        language: system
        types: [python]

mirdan export --format badge > .mirdan/badge.json

version: "1.0"

project:
  name: "MyApp"
  primary_language: "python"
  frameworks: ["fastapi", "react"]

# Quality enforcement levels
quality:
  security: "strict"           # strict|moderate|permissive
  architecture: "moderate"
  documentation: "moderate"
  testing: "strict"

# Or use a named profile (overrides quality section)
quality_profile: "default"

# Semantic validation and dependency scanning
semantic:
  enabled: true
  analysis_protocol: "security"  # none|security|comprehensive

dependencies:
  enabled: true
  osv_cache_ttl: 86400           # 24 hours
  scan_on_gate: true
  fail_on_severity: "high"       # critical|high|medium|low|none

# Score thresholds
thresholds:
  severity_error_weight: 0.25
  severity_warning_weight: 0.08
  arch_max_function_length: 30
  arch_max_file_length: 300
  # Per-file threshold overrides (glob patterns)
  file_overrides:
    - pattern: "tests/**"
      arch_max_function_length: 60
    - pattern: "scripts/**"
      arch_max_file_length: 500

# Hook behavior
hooks:
  enabled_events: ["PreToolUse", "PostToolUse", "Stop"]
  quick_validate_timeout: 5000
  auto_fix_suggestions: true

llm:
  enabled: true
  backend: llamacpp                # llamacpp (default) or ollama
  model_keep_alive: 5m             # Unload model after idle (saves RAM)