Guardrails

guardrails - Interactive Security Guardrails Configuration

Helps users configure comprehensive security guardrails for their OpenClaw workspace through an interactive interview process.

Commands

guardrails setup

Interactive setup mode - Guides user through creating their GUARDRAILS.md file.

Workflow: 1. Run environment discovery: bash scripts/discover.sh 2. Classify risks: bash scripts/discover.sh | python3 scripts/classify-risks.py 3. Generate tailored questions: bash scripts/discover.sh | python3 scripts/classify-risks.py | python3 scripts/generate_questions.py 4. Conduct interactive interview with the user: - Ask questions from the generated question bank (tailored to discovered environment) - Present suggestions for each question - Allow custom answers - Follow up when appropriate 5. Generate GUARDRAILS.md: echo '' | python3 scripts/generate_guardrails_md.py /path/to/guardrails-config.json - Stdin JSON format: {"discovery": {...}, "classification": {...}, "answers": {...}} 6. Present the generated GUARDRAILS.md for review 7. Ask for confirmation before writing to workspace 8. Write GUARDRAILS.md to workspace root 9. Save guardrails-config.json to workspace root

Important:

Be conversational and friendly during the interview

Explain why each question matters

Provide context about discovered risks

Highlight high-risk skills/integrations

Allow users to skip or customize any answer

Review the final output with the user before writing

guardrails review

Review mode - Check existing configuration against current environment.

Workflow: 1. Run discovery and classification 2. Load existing guardrails-config.json 3. Compare discovered skills/integrations against config 4. Identify gaps (new skills not covered, removed skills still in config) 5. Ask user about gaps only - don't re-interview everything 6. Update config and GUARDRAILS.md if changes needed

guardrails monitor

Monitor mode - Detect changes and potential violations.

Workflow: 1. Run: bash scripts/monitor.sh 2. Parse the JSON report 3. If status is "ok": silent or brief acknowledgment 4. If status is "needs-attention": notify user with details 5. If status is "review-recommended": suggest running guardrails review

Can be run manually or via cron/heartbeat.

Files Generated

GUARDRAILS.md - The main guardrails document (workspace root)

guardrails-config.json - Machine-readable config for monitoring (workspace root)

Notes

This skill only helps *create* guardrails - enforcement is up to the agent

Discovery (discover.sh) uses bash + jq; classification (classify-risks.py) uses Python standard library only

Question generation and GUARDRAILS.md generation require an LLM — set OPENAI_API_KEY or ANTHROPIC_API_KEY

Python scripts require the requests library (pip install requests)

Discovery and classification are read-only operations

Only setup and review modes write files, and only with user confirmation

This skill only helps *create* guardrails - enforcement is up to the agent

Discovery (discover.sh) uses bash + jq; classification (classify-risks.py) uses Python standard library only

Question generation and GUARDRAILS.md generation require an LLM — set OPENAI_API_KEY or ANTHROPIC_API_KEY

Python scripts require the requests library (pip install requests)

Discovery and classification are read-only operations

Only setup and review modes write files, and only with user confirmation