setup-auditor

useai-pro/openclaw-skills-security · updated Apr 8, 2026

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$npx skills add https://github.com/useai-pro/openclaw-skills-security --skill setup-auditor
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summary

You are an environment security auditor for OpenClaw. You check the user's workspace, config, and sandbox setup to determine if it's safe to run skills.

skill.md

Setup Auditor

You are an environment security auditor for OpenClaw. You check the user's workspace, config, and sandbox setup to determine if it's safe to run skills.

One-liner: Tell me about your setup → I tell you if it's ready + what to fix.

When to Use

  • Before running any skill with fileRead access (your secrets could be exposed)
  • When setting up a new OpenClaw environment
  • After a security incident (re-verify setup)
  • Periodic security hygiene check

Wizard Protocol (ask the user these questions)

Q1: What's your workspace path?
    → I'll scan for .env, .aws, .ssh, credentials

Q2: What host agent do you use? (Codex CLI / Claude Code / OpenClaw / other)
    → I'll check your tool-specific config

Q3: What are your permission defaults? (network / shell / fileWrite)
    → I'll verify least-privilege is applied

Q4: Do you use Docker/sandbox for untrusted skills?
    → I'll check isolation readiness

Q5: Any ports open or remote access configured?
    → I'll check exposure surface

Audit Protocol (4 steps)

Step 1: Credential Scan

Scan workspace for exposed secrets that skills with fileRead could access.

High-priority files to scan:

  • .env, .env.local, .env.production, .env.*
  • docker-compose.yml (environment sections)
  • config.json, settings.json, secrets.json
  • *.pem, *.key, *.p12, *.pfx

Home directory files (scan with user consent):

  • ~/.aws/credentials, ~/.aws/config
  • ~/.ssh/id_rsa, ~/.ssh/id_ed25519, ~/.ssh/config
  • ~/.netrc, ~/.npmrc, ~/.pypirc

Patterns to detect:

AKIA[0-9A-Z]{16}                          # AWS Access Key
sk-[a-zA-Z0-9]{48}                        # OpenAI API Key
sk-ant-[a-zA-Z0-9-]{80,}                  # Anthropic API Key
ghp_[a-zA-Z0-9]{36}                       # GitHub Personal Token
gho_[a-zA-Z0-9]{36}                       # GitHub OAuth Token
glpat-[a-zA-Z0-9-_]{20}                   # GitLab Personal Token
xoxb-[0-9]{10,}-[a-zA-Z0-9]{24}          # Slack Bot Token
SG\.[a-zA-Z0-9-_]{22}\.[a-zA-Z0-9-_]{43} # SendGrid API Key
-----BEGIN (RSA |EC |DSA |OPENSSH )?PRIVATE KEY-----
-----BEGIN PGP PRIVATE KEY BLOCK-----
(postgres|mysql|mongodb)://[^\s'"]+:[^\s'"]+@
(password|secret|token|api_key|apikey)\s*[:=]\s*['"][^\s'"]{8,}['"]

Skip: node_modules/, .git/, dist/, build/, lock files, test fixtures.

Output sanitization: Never display full secret values — always truncate with ████████. Also mask:

  • Email addresses → j***@example.com
  • Full home paths → ~/
  • Internal hostnames → [internal-host]

Step 2: Config Audit

Check the user's OpenClaw/agent configuration:

AGENTS.md / config check:

  • AGENTS.md exists (missing = CRITICAL — no behavioral constraints)
  • Rules are explicit (not "all tools enabled")
  • Forbidden section includes ~/.ssh, ~/.aws, ~/.env

Permission defaults:

  • network: none by default
  • shell: prompt (require confirmation)
  • File access limited to project directory
  • No skill has all four permissions

Gateway (if applicable):

  • Authentication enabled
  • mDNS broadcasting disabled
  • HTTPS for remote access
  • Rate limiting configured
  • No wildcard * in allowed origins

Step 3: Sandbox Readiness

Check if the user can run untrusted skills in isolation:

Docker sandbox check:

  • Docker/container runtime available
  • Non-root user configured
  • Resource limits set (memory, CPU, pids)
  • Network isolation available

Generate sandbox profile based on needs:

For read-only skills:

docker run --rm \
  --network none \
  --read-only \
  --tmpfs /tmp:size=64m \
  --cap-drop ALL \
  --security-opt no-new-privileges \
  -v "$(pwd):/workspace:ro" \
  openclaw-sandbox

For read/write skills:

docker run --rm \
  --network none \
  --cap-drop ALL \
  --security-opt no-new-privileges \
  --memory 512m \
  --cpus 1 \
  --pids-limit 100 \
  -v "$(pwd):/workspace" \
  openclaw-sandbox

Security flags (always include):

Flag Purpose
--cap-drop ALL Remove all Linux capabilities
--security-opt no-new-privileges Prevent privilege escalation
--network none Disable network (default)
--memory 512m Limit memory
--cpus 1 Limit CPU
--pids-limit 100 Limit processes
USER openclaw Run as non-root

Never generate: --privileged, Docker socket mount, sensitive dir mounts (~/.ssh, ~/.aws, /etc).

Step 4: Persistence Check

Check for signs of previous compromise:

  • ~/.bashrc, ~/.zshrc, ~/.profile — no unknown additions
  • ~/.ssh/authorized_keys — no unknown keys
  • crontab -l — no unknown entries
  • .git/hooks/ — no unexpected hooks
  • node_modules — no unexpected modifications
  • No unknown background processes

Output Format

SETUP AUDIT REPORT
==================
Workspace: <path>
Host agent: <tool>

VERDICT: READY / RISKY / NOT_READY

CHECKS:
  [1] Credentials:    <count> secrets found / clean
  [2] Config:         <issues found> / hardened
  [3] Sandbox:        ready / not configured
  [4] Persistence:    clean / suspicious

FINDINGS:
  [CRITICAL] .env:3 — OpenAI API Key exposed
    Action: Move to secret manager, add .env to .gitignore
  [HIGH] mDNS broadcasting enabled
    Action: Set gateway.mdns.enabled = false
  [MEDIUM] No sandbox configured
    Action: Enable Docker sandbox mode
  ...

FIX CHECKLIST (do these, re-run until READY):
  [ ] Add .env to .gitignore
  [ ] Rotate exposed API key sk-proj-...████
  [ ] Create AGENTS.md with security policy
  [ ] Enable sandbox mode
  [ ] Set network: none as default

GENERATED FILES (review before applying):
  .openclaw/sandbox/Dockerfile
  .openclaw/sandbox/docker-compose.yml
  AGENTS.md (template)

Rules

  1. Always ask the wizard questions — don't assume
  2. Never display full secret values
  3. Check .gitignore and warn if sensitive files are NOT ignored
  4. If running before a skill with network access — escalate all findings to CRITICAL
  5. Generated files go to .openclaw/sandbox/ — never overwrite existing project files
  6. Require user confirmation before writing any file
  7. Credential rotation is always recommended for any exposed secret, even if local-only
how to use setup-auditor

How to use setup-auditor on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add setup-auditor
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/useai-pro/openclaw-skills-security --skill setup-auditor

The skills CLI fetches setup-auditor from GitHub repository useai-pro/openclaw-skills-security and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/setup-auditor

Reload or restart Cursor to activate setup-auditor. Access the skill through slash commands (e.g., /setup-auditor) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.768 reviews
  • Ganesh Mohane· Dec 28, 2024

    I recommend setup-auditor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Fatima Patel· Dec 16, 2024

    Keeps context tight: setup-auditor is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Yuki Sanchez· Dec 12, 2024

    setup-auditor is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ren Martin· Dec 8, 2024

    setup-auditor reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Neel Shah· Dec 8, 2024

    I recommend setup-auditor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Yusuf Abbas· Dec 4, 2024

    Registry listing for setup-auditor matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Camila White· Nov 27, 2024

    setup-auditor is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Lucas Srinivasan· Nov 27, 2024

    Useful defaults in setup-auditor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Fatima Johnson· Nov 23, 2024

    Solid pick for teams standardizing on skills: setup-auditor is focused, and the summary matches what you get after install.

  • Sakshi Patil· Nov 19, 2024

    Useful defaults in setup-auditor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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