A sophisticated multi-jurisdiction content policy enforcer that acts as the final line of defense for AI-generated output compliance.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install sharpagent-content-safety
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install sharpagent-content-safety using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is SharpAgent Content Safety Engine?
The SharpAgent Content Safety Engine is a robust, independent Layer 3 component of the SharpAgent four-layer architecture. It is designed to evaluate AI outputs not just on their factual accuracy, but on their legal and ethical compliance across various global regions. By separating credibility (Layer 1) from compliance (Layer 3), this skill ensures that information quality is never contaminated by the shifting requirements of regional regulations.
Built as a pluggable rule engine, it allows developers using Openclaw Skills to implement strict safety buffers that can block, flag, or pass content based on concurrent jurisdictions. Whether you are navigating China Internet regulations, US export controls, or EU GDPR requirements, this engine provides a unified interface for safety interception.
SharpAgent Content Safety Engine Use Cases
- Enforcing regional regulatory compliance for AI responses in the US, EU, and China.
- Automating the detection and removal of Personally Identifiable Information (PII) like emails and addresses.
- Shielding applications from hate speech and discriminatory content through global safety sets.
- Flagging sensitive technical data subject to export control for human review.
- Implementing corporate-specific content policies alongside standard legal requirements.
How SharpAgent Content Safety Engine Works
- Pre-Flight Validation: The engine first validates that content is present and chunks any text exceeding 4096 characters to ensure efficient processing.
- Policy Loading: It initializes active jurisdictions (e.g., global, cn, us) and stacks the corresponding YAML-based rule sets.
- Rule Matching: The engine scans each content chunk against regex patterns, keywords, and defined exemptions within the active rule sets.
- Conflict Resolution: If multiple rules apply, the engine applies a 'strictest wins' logic where block actions override flags, and flags override passes.
- Verdict Execution: A final verdict of pass, flag, or block is issued. Blocks trigger an automatic replacement message explaining the safety violation.
- Audit Logging: Every check is recorded with a timestamp, matched rules, and severity levels for legal compliance and memory archiving.
SharpAgent Content Safety Engine Setup
To integrate this engine into your environment, follow these steps:
- Load the Skill: Ensure the Openclaw Skills environment can access the
sharpagent-content-safetypackage. - Configure Jurisdictions: Initialize the engine within your runtime:
safety_engine.load_policies(jurisdictions=["global", "eu", "us"])
- Add Custom Rules: Place any company-specific policies in the
rules/custom/directory using the standard YAML schema.
SharpAgent Content Safety Engine Data Schema & Taxonomy
The engine organizes safety data through a structured hierarchy of YAML files and standardized log outputs:
| Data Component | Description | Format |
|---|---|---|
| Rule Sets | Regional safety definitions (e.g., rules/cn.yaml) |
YAML |
| Rule Object | Individual check with ID, jurisdiction, severity, and patterns | YAML |
| Safety Verdict | The outcome of an analysis (pass, flag, block) | String |
| Audit Log | Full JSON trace of matched rules and timestamps | JSON |
| Exemptions | Contextual conditions where rules are ignored | List |
SharpAgent Content Safety Engine Advanced Features
- Multi-Jurisdiction Stacking: Simultaneously enforce rules from different regions with automatic conflict resolution.
- Overlapping Chunk Scanning: Scans +/- 200 characters across chunk boundaries to prevent sensitive phrases from being missed at split points.
- Calibration Integration: Maps the safety engine directly to Layer 2 output adaptation for seamless 'warm' or 'professional' content filtering.
- Self-Evolving Feedback Loop: High-confidence false positives can trigger reflection cycles to propose rule improvements.
- Exemption Engine: Support for complex exemption logic, such as allowing sensitive terms in educational or news reporting contexts.
SKILL.md
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