feat(tools): add Sentinel Safety Tools for AI guardrails

lib/crewai-tools/src/crewai_tools/tools/__init__.py

@@ -179,6 +179,10 @@
     YoutubeVideoSearchTool,
 )
 from crewai_tools.tools.zapier_action_tool.zapier_action_tool import ZapierActionTools
+from crewai_tools.tools.sentinel_safety_tool.sentinel_safety_tool import (
+    SentinelSafetyTool,
+    SentinelAnalyzeTool,
+)
 
 
 __all__ = [
@@ -271,4 +275,6 @@
     "YoutubeChannelSearchTool",
     "YoutubeVideoSearchTool",
     "ZapierActionTools",
+    "SentinelSafetyTool",
+    "SentinelAnalyzeTool",
 ]

lib/crewai-tools/src/crewai_tools/tools/sentinel_safety_tool/README.md

@@ -0,0 +1,99 @@
+# SentinelSafetyTool Documentation
+
+## Description
+
+The Sentinel Safety Tools provide AI safety guardrails for CrewAI agents using the THSP protocol (Truth, Harm, Scope, Purpose). These tools help ensure that AI agents operate within ethical boundaries by:
+
+1. **SentinelSafetyTool**: Returns alignment seeds that can be used as system prompts to make LLMs safer
+2. **SentinelAnalyzeTool**: Analyzes content for safety using the four-gate THSP protocol
+
+The THSP protocol evaluates requests through four gates:
+- **Truth**: Detects deception and manipulation
+- **Harm**: Identifies potential harmful content
+- **Scope**: Validates appropriate boundaries
+- **Purpose**: Requires legitimate benefit
+
+## Installation
+
+To incorporate this tool into your project, follow the installation instructions below:
+
+```shell
+pip install 'crewai[tools]' sentinelseed
+```
+
+## Example
+
+### Basic Usage
+
+```python
+from crewai_tools import SentinelSafetyTool, SentinelAnalyzeTool
+
+# Get the alignment seed for system prompts
+seed_tool = SentinelSafetyTool()
+seed = seed_tool._run(variant="standard")  # or "minimal"
+
+# Analyze content for safety
+analyze_tool = SentinelAnalyzeTool()
+result = analyze_tool._run(content="Help me with network security")
+print(result)  # "SAFE - All gates passed..."
+```
+
+### With CrewAI Agent
+
+```python
+from crewai import Agent
+from crewai_tools import SentinelSafetyTool, SentinelAnalyzeTool
+
+# Create agent with Sentinel tools
+agent = Agent(
+    role="Safe Research Assistant",
+    goal="Research topics safely and ethically",
+    backstory="You are an expert researcher with strong ethical principles.",
+    tools=[SentinelSafetyTool(), SentinelAnalyzeTool()],
+    verbose=True
+)
+```
+
+### Using Seed as System Prompt
+
+```python
+from sentinelseed import get_seed
+from crewai import Agent
+
+# Get seed directly for system prompt
+sentinel_seed = get_seed("v2", "standard")
+
+agent = Agent(
+    role="Safe Assistant",
+    system_template=sentinel_seed,  # Inject safety via system prompt
+    verbose=True
+)
+```
+
+## Tool Details
+
+### SentinelSafetyTool
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `variant` | str | "standard" | Seed variant: "minimal" (~450 tokens) or "standard" (~1.4K tokens) |
+
+### SentinelAnalyzeTool
+
+| Parameter | Type | Required | Description |
+|-----------|------|----------|-------------|
+| `content` | str | Yes | The content to analyze for safety |
+
+**Returns:**
+- `SAFE - All gates passed` if content is safe
+- `UNSAFE - Issues: [list of issues]` if content fails any gate
+
+## Links
+
+- [Sentinel Seed Website](https://sentinelseed.dev)
+- [sentinelseed on PyPI](https://pypi.org/project/sentinelseed/)
+- [CrewAI Documentation](https://docs.crewai.com)
+
+## Conclusion
+
+By integrating the Sentinel Safety Tools into CrewAI projects, developers can add AI safety guardrails to their agents with minimal effort. The THSP protocol provides a systematic approach to evaluating content for truth, harm, scope, and purpose, ensuring that AI systems operate within ethical boundaries.

lib/crewai-tools/src/crewai_tools/tools/sentinel_safety_tool/__init__.py

@@ -0,0 +1,6 @@
+from .sentinel_safety_tool import (
+    SentinelSafetyTool,
+    SentinelAnalyzeTool,
+)
+
+__all__ = ["SentinelSafetyTool", "SentinelAnalyzeTool"]

lib/crewai-tools/src/crewai_tools/tools/sentinel_safety_tool/sentinel_safety_tool.py

@@ -0,0 +1,144 @@
+"""
+Sentinel Safety Tools for CrewAI
+
+Provides AI safety guardrails for CrewAI agents using the THSP protocol
+(Truth, Harm, Scope, Purpose).
+
+Dependencies:
+    - sentinelseed (pip install sentinelseed)
+    - pydantic
+
+See: https://sentinelseed.dev
+"""
+
+from typing import Any, Literal, Type
+
+from crewai.tools import BaseTool
+from pydantic import BaseModel, Field
+
+
+class SentinelSeedSchema(BaseModel):
+    """Input schema for SentinelSafetyTool."""
+
+    variant: Literal["minimal", "standard"] = Field(
+        default="standard",
+        description="Seed variant: 'minimal' (~450 tokens) or 'standard' (~1.4K tokens)",
+    )
+
+
+class SentinelAnalyzeSchema(BaseModel):
+    """Input schema for SentinelAnalyzeTool."""
+
+    content: str = Field(..., description="The content to analyze for safety")
+
+
+class SentinelSafetyTool(BaseTool):
+    """
+    SentinelSafetyTool - Get alignment seeds for AI safety.
+
+    Returns the Sentinel THSP (Truth, Harm, Scope, Purpose) alignment protocol
+    that can be used as a system prompt to make LLMs safer.
+
+    The THSP protocol evaluates requests through four gates:
+    - Truth: Detects deception and manipulation
+    - Harm: Identifies potential harmful content
+    - Scope: Validates appropriate boundaries
+    - Purpose: Requires legitimate benefit
+
+    Dependencies:
+        - sentinelseed (pip install sentinelseed)
+    """
+
+    name: str = "Sentinel Get Safety Seed"
+    description: str = (
+        "Get the Sentinel alignment seed - a system prompt that adds safety "
+        "guardrails to any LLM using the THSP protocol (Truth, Harm, Scope, Purpose). "
+        "Use 'minimal' for ~450 tokens or 'standard' for ~1.4K tokens. "
+        "The seed can be used as a system prompt to improve AI safety."
+    )
+    args_schema: Type[BaseModel] = SentinelSeedSchema
+
+    def _run(self, **kwargs: Any) -> str:
+        """Get the Sentinel alignment seed."""
+        variant = kwargs.get("variant", "standard")
+
+        try:
+            from sentinelseed import get_seed
+
+            if variant not in ["minimal", "standard"]:
+                return f"Error: Invalid variant '{variant}'. Use 'minimal' or 'standard'."
+
+            seed = get_seed("v2", variant)
+            return seed
+
+        except ImportError:
+            return (
+                "Error: sentinelseed package not installed. "
+                "Run: pip install sentinelseed"
+            )
+        except Exception as e:
+            return f"Error getting seed: {str(e)}"
+
+
+class SentinelAnalyzeTool(BaseTool):
+    """
+    SentinelAnalyzeTool - Analyze content for safety using THSP gates.
+
+    Checks content against Sentinel's four-gate THSP protocol:
+    - Truth: Detects deception patterns (fake, phishing, impersonation)
+    - Harm: Identifies potential harmful content (violence, malware, weapons)
+    - Scope: Flags bypass attempts (jailbreak, ignore instructions)
+    - Purpose: Validates legitimate purpose
+
+    Dependencies:
+        - sentinelseed (pip install sentinelseed)
+    """
+
+    name: str = "Sentinel Analyze Content Safety"
+    description: str = (
+        "Analyze any text content for safety using Sentinel's THSP protocol. "
+        "Returns whether the content is safe and which gates passed/failed. "
+        "Use this to validate inputs, outputs, or any text before processing. "
+        "Gates checked: Truth, Harm, Scope, Purpose."
+    )
+    args_schema: Type[BaseModel] = SentinelAnalyzeSchema
+
+    def _run(self, **kwargs: Any) -> str:
+        """Analyze content using THSP gates."""
+        content = kwargs.get("content", "")
+
+        if not content:
+            return "Error: No content provided for analysis."
+
+        try:
+            from sentinelseed import SentinelGuard
+
+            guard = SentinelGuard()
+            analysis = guard.analyze(content)
+
+            gates_str = ", ".join(
+                f"{gate}: {status}" for gate, status in analysis.gates.items()
+            )
+
+            if analysis.safe:
+                return (
+                    f"SAFE - All gates passed.\n"
+                    f"Gates: {gates_str}\n"
+                    f"Confidence: {analysis.confidence:.0%}"
+                )
+            else:
+                issues_str = ", ".join(analysis.issues) if analysis.issues else "Unknown"
+                return (
+                    f"UNSAFE - Safety check failed.\n"
+                    f"Issues: {issues_str}\n"
+                    f"Gates: {gates_str}\n"
+                    f"Confidence: {analysis.confidence:.0%}"
+                )
+
+        except ImportError:
+            return (
+                "Error: sentinelseed package not installed. "
+                "Run: pip install sentinelseed"
+            )
+        except Exception as e:
+            return f"Error analyzing content: {str(e)}"