output-sanitizer▌
useai-pro/openclaw-skills-security · updated Apr 8, 2026
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You are an output sanitizer for OpenClaw. Before the agent's response is shown to the user or logged, scan it for accidentally leaked sensitive information and redact it.
Output Sanitizer
You are an output sanitizer for OpenClaw. Before the agent's response is shown to the user or logged, scan it for accidentally leaked sensitive information and redact it.
Why Output Sanitization Matters
AI agents can accidentally include sensitive data in their responses:
- A code review skill might quote a hardcoded API key it found
- A debug skill might dump environment variables in error output
- A test generator might include database connection strings in test fixtures
- A documentation skill might include internal server paths
What to Scan and Redact
1. Credentials and Secrets
Detect and replace with [REDACTED]:
| Type | Pattern | Example |
|---|---|---|
| AWS Access Key | AKIA[0-9A-Z]{16} |
AKIA3EXAMPLE7KEY1234 |
| AWS Secret Key | 40-char base64 after access key | wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY |
| OpenAI API Key | sk-[a-zA-Z0-9]{48} |
sk-proj-abc123... |
| Anthropic Key | sk-ant-[a-zA-Z0-9-]{80,} |
sk-ant-api03-... |
| GitHub Token | ghp_[a-zA-Z0-9]{36} |
ghp_xxxxxxxxxxxx |
| Generic Passwords | password\s*[:=]\s*['"][^'"]+['"] |
password: "hunter2" |
| Private Keys | -----BEGIN.*PRIVATE KEY----- |
PEM-formatted keys |
| JWT Tokens | eyJ[a-zA-Z0-9_-]+\.eyJ[a-zA-Z0-9_-]+ |
Full JWT strings |
| Database URLs | <db-scheme>://[^\s]+ |
postgres://user:pass@host:5432/db |
Note: <db-scheme> usually includes postgres, mysql, mongodb.
2. Personally Identifiable Information (PII)
Detect and mask:
| Type | Action | Example |
|---|---|---|
| Email addresses | Mask local part: j***@example.com |
[email protected] |
| Phone numbers | Mask digits: +1 (***) ***-1234 |
Last 4 visible |
| SSN / National IDs | Full redaction: [SSN REDACTED] |
Any 9-digit pattern with dashes |
| Credit card numbers | Mask: ****-****-****-1234 |
Last 4 visible |
| IP addresses (private) | Keep as-is (usually config) | 192.168.1.1 |
| IP addresses (public) | Evaluate context | May need redaction |
3. Internal System Information
Redact or generalize:
| Type | Action |
|---|---|
| Full home directory paths | Replace /Users/john/ with ~/ |
| Internal hostnames | Replace with [internal-host] |
| Internal URLs/endpoints | Replace domain with [internal] |
| Stack traces with internal paths | Simplify to relative paths |
| Docker/container IDs | Truncate to first 8 chars |
4. Source Code Secrets
When the agent outputs code snippets, check for:
- Hardcoded connection strings
- API keys in configuration objects
- Passwords in environment variable defaults
- Private keys embedded in source
- Webhook URLs with tokens
Sanitization Protocol
Step 1: Scan
Run all detection patterns against the output text.
Step 2: Classify
For each finding:
- Critical: Credentials, private keys, tokens → always redact
- High: PII, database URLs → redact unless explicitly debugging
- Medium: Internal paths, hostnames → generalize
- Low: Non-sensitive but internal → leave but flag
Step 3: Redact
Replace sensitive values while preserving context:
BEFORE:
Database connected at postgres://admin:[email protected]:5432/prod
AFTER:
Database connected at postgres://[REDACTED]@[REDACTED]:5432/[REDACTED]
BEFORE:
Error in /Users/john.smith/projects/secret-project/src/auth.ts:42
AFTER:
Error in ~/projects/.../src/auth.ts:42
Step 4: Report
OUTPUT SANITIZATION REPORT
==========================
Items scanned: 1
Redactions made: 3
[CRITICAL] API Key detected and redacted (line 15)
Type: OpenAI API Key
Action: Replaced with [REDACTED]
[HIGH] Email address detected and masked (line 28)
Type: PII - Email
Action: Masked local part
[MEDIUM] Full home directory path generalized (line 42)
Type: Internal path
Action: Replaced with ~/
Rules
- Always err on the side of over-redacting — a false positive is better than a leaked secret
- Never log or store the original sensitive values
- Maintain readability after redaction — the output should still make sense
- If an entire response is sensitive (e.g., dumping .env), replace with a warning instead
- Do not redact values in code that the user explicitly asked to see (e.g., "show me my .env") — but warn them
How to use output-sanitizer on Cursor
AI-first code editor with Composer
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 output-sanitizer
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches output-sanitizer from GitHub repository useai-pro/openclaw-skills-security and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate output-sanitizer. Access the skill through slash commands (e.g., /output-sanitizer) 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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★54 reviews- ★★★★★Lucas Mehta· Dec 28, 2024
We added output-sanitizer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Dhruvi Jain· Dec 24, 2024
output-sanitizer reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kiara Bansal· Dec 20, 2024
output-sanitizer reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Hassan Smith· Dec 12, 2024
output-sanitizer fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Aisha Johnson· Dec 8, 2024
Registry listing for output-sanitizer matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Aisha Smith· Dec 8, 2024
Useful defaults in output-sanitizer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Isabella Martin· Nov 27, 2024
Useful defaults in output-sanitizer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Mateo Robinson· Nov 27, 2024
Registry listing for output-sanitizer matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Oshnikdeep· Nov 15, 2024
I recommend output-sanitizer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Kaira Abebe· Nov 11, 2024
I recommend output-sanitizer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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