safe-agent-cli 0.4.0

An AI coding agent you can actually trust - with built-in impact preview

🛡️ Safe Agent

Guardrails for AI code agents.

Safe Agent previews every file edit with impact-preview so AI helpers can’t quietly ship risky changes. Drop it into CI or run locally and require approvals before writes.

pip install safe-agent-cli
safe-agent "add error handling to api.py" --dry-run

✨ New in v0.4.0

• 🧭 Policy-as-code enforcement - Deterministic allow/deny/require-approval decisions before execution
• 🎛️ Policy presets - --policy-preset startup|fintech|games plus --list-policy-presets
• 🕵️ Prompt injection scan surfaced - Preview shows scanner severity + reason IDs

Project Map

• impact-preview (Agent Polis): the guardrail layer that previews and scores risky actions.
• safe-agent-cli (this repo): a reference coding agent that uses impact-preview for approvals.
• Roadmap: staged execution plan in ROADMAP.md.
• Compatibility Matrix: version contract in docs/compatibility-matrix.md.
• Monday Packet: current assignment bundle in docs/monday-assignment-packet.md.

The Problem

AI coding agents are powerful but dangerous:

• Replit Agent deleted a production database
• Cursor YOLO mode deleted an entire system
• You can't see what's about to happen until it's too late

The Solution

Safe Agent previews every change before execution:

$ safe-agent "update database config to use production"

📋 Task: update database config to use production

📝 Planned Changes
┌────────┬─────────────────┬─────────────────────────┐
│ Action │ File            │ Description             │
├────────┼─────────────────┼─────────────────────────┤
│ MODIFY │ config/db.yaml  │ Update database URL     │
└────────┴─────────────────┴─────────────────────────┘

Step 1/1

╭─────────────── Impact Preview ───────────────╮
│ Update database URL                          │
│                                              │
│ **File:** `config/db.yaml`                   │
│ **Action:** MODIFY                           │
│ **Risk:** 🔴 CRITICAL                        │
│ **Policy:** REQUIRE_APPROVAL [builtin]       │
│ **Scanner:** LOW                             │
╰──────────────────────────────────────────────╯

Risk Factors:
  ⚠️  Production pattern detected: production
  ⚠️  Database configuration change

Diff:
- url: postgresql://localhost:5432/dev
+ url: postgresql://prod-server:5432/production

⚠️  CRITICAL RISK - Please review carefully!
Apply this change? [y/N]: 

Installation

pip install safe-agent-cli

Set your Anthropic API key:

export ANTHROPIC_API_KEY=your-key-here

Usage

Basic Usage

# Run a coding task
safe-agent "add input validation to user registration"

# Preview only (no execution)
safe-agent "refactor auth module" --dry-run

# Auto-approve low-risk changes
safe-agent "add docstrings" --auto-approve-low

CI / Non-interactive mode

Use --non-interactive to avoid prompts (auto-approves when policy allows; skips anything requiring approval). Combine with --fail-on-risk to fail the process if risky changes are proposed:

safe-agent "scan repository for risky config changes" --dry-run --non-interactive --fail-on-risk high

Policy (allow/deny/require approval)

By default Safe Agent enforces a built-in policy that:

• denies obvious secret/key targets (e.g. .env, .ssh, .pem)
• allows LOW/MEDIUM risk actions
• requires approval for HIGH/CRITICAL risk actions

Override with a bundled preset:

safe-agent --list-policy-presets
safe-agent "update auth flow" --policy-preset fintech

Or load a policy file (JSON/YAML):

safe-agent "update auth flow" --policy ./policy.json

Interactive Mode

safe-agent --interactive

From File

safe-agent --file task.md

How It Works

1. Plan - Claude analyzes your task and plans file changes
2. Preview - Each change runs through impact-preview for risk analysis
3. Approve - You see the diff and risk level before anything executes
4. Execute - Only approved changes are applied

Enterprise & Compliance Features

Safe Agent now includes features for insurance partnerships, regulatory compliance, and enterprise deployments.

Audit Export for Insurance

Export complete audit trails for insurance underwriting and claims:

safe-agent "update production config" --audit-export audit.json

The audit export includes:

• Complete task history with timestamps
• Risk assessments for all operations
• Approval/rejection records (human oversight)
• Change execution status
• Compliance flags for regulatory requirements

Perfect for working with AI liability insurance carriers like AIUC, Armilla AI, and Beazley.

See docs/insurance-integration.md for details on insurance partnerships and premium rate factors.

EU AI Act Compliance Mode

Enable strict compliance mode for EU AI Act requirements:

safe-agent "modify user data" --compliance-mode --audit-export audit.json

Compliance mode:

• Disables all auto-approve features (Article 14: Human Oversight)
• Requires explicit approval for every operation
• Records all compliance flags in audit exports
• Supports Article 12 (Record-Keeping) requirements

Ready for the August 2, 2026 enforcement deadline.

See docs/eu-ai-act-compliance.md for complete compliance guide and requirements mapping.

Incident Documentation

We maintain a comprehensive database of AI agent incidents to raise awareness and demonstrate prevention mechanisms:

• Replit SaaStr Database Deletion - Production database deleted during demo
• Cursor YOLO Mode Bypass - Security controls circumvented

Submit an incident report to help the community.

Options

Flag	Description
--dry-run	Preview changes without executing
--auto-approve-low	Auto-approve low-risk changes
--non-interactive	Run without prompts (CI-friendly)
--fail-on-risk	Exit non-zero if any change meets/exceeds risk level
--policy	Path to a policy file (JSON/YAML) for deterministic allow/deny/approval
--policy-preset	Use a bundled policy preset (startup, fintech, games)
--list-policy-presets	List available policy presets and exit
--interactive, -i	Interactive mode
--file, -f	Read task from file
--model	Claude model to use (default: claude-sonnet-4-20250514)
--audit-export	Export audit trail to JSON file (insurance/compliance)
--compliance-mode	Enable strict compliance mode (disables auto-approve)

MCP Server (For Other AI Agents)

Safe Agent can be used as an MCP server, letting other AI agents delegate coding tasks safely.

# Start the MCP server
safe-agent-mcp

Claude Desktop Integration

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "safe-agent": {
      "command": "safe-agent-mcp"
    }
  }
}

Available MCP Tools

Tool	Description	Safety
run_coding_task	Execute a coding task with preview	🔴 Destructive
preview_coding_task	Preview changes without executing	🟢 Read-only
get_agent_status	Check agent status and capabilities	🟢 Read-only

Moltbook Integration

Safe Agent is available as a Moltbook skill for AI agent networks.

See moltbook-skill.json for the skill definition.

Demo Producer

Set up a canned risky-edit scenario and print recording commands:

safe-agent-demo prepare  # creates a demo repo with config/db.yaml
cd /tmp/safe-agent-demo-*  # or your chosen path
safe-agent-demo record     # shows asciinema + GIF commands

By default the demo runs safe-agent --dry-run "switch database config to production" against the prepared repo.

For AI Agents

If you're an AI agent wanting to use Safe Agent programmatically:

from safe_agent import SafeAgent

agent = SafeAgent(
    auto_approve_low_risk=True,      # Skip approval for low-risk changes
    dry_run=False,                   # Set True to preview only
    audit_export_path="audit.json",  # Export audit trail for compliance
    compliance_mode=False,           # Enable for EU AI Act compliance
)

result = await agent.run("add error handling to api.py")

For insurance and compliance use cases:

# EU AI Act compliant configuration
agent = SafeAgent(
    compliance_mode=True,              # Strict compliance mode
    audit_export_path="audit.json",    # Required for Article 12
    non_interactive=False,             # Human oversight required
)

Powered By

• impact-preview - Impact analysis and diff generation
• Claude - AI planning and code generation
• Rich - Beautiful terminal output
• MCP - Model Context Protocol for agent interoperability

Known Incidents

AI coding agents without proper safeguards have caused real damage. We document these incidents to raise awareness and demonstrate why preview-before-execute architecture matters.

Recent Incidents

• Replit SaaStr Database Deletion (July 2025) - Production database deleted, 1,200+ executives affected
• Cursor YOLO Mode Bypass (July 2025) - Security controls bypassed, arbitrary command execution possible

Submit an Incident

Experienced an AI agent incident? Help the community by submitting an incident report.

Browse all documented incidents in docs/incident-reports/.

Marketing Helpers

A lightweight CLI to generate headline variants, channel-specific copy (HN, Twitter/X, LinkedIn), and README hero blocks:

safe-agent-marketing generate --audience "Teams running AI code agents in CI" \
  --hypothesis "Guardrail that blocks risky edits" --update-readme

This writes JSON/Markdown bundles to marketing/ and (optionally) refreshes the README hero block. Queue posts with:

safe-agent-marketing queue --slot 2026-02-05T15:00:00Z --slot 2026-02-05T20:00:00Z

Log traction daily:

safe-agent-marketing analytics --repo agent-polis/safe-agent --log experiments/experiments.csv

License

MIT License - see LICENSE for details.

---

Built by developers who want AI agents they can actually trust.