ReskPoints
The AI Agent Logger
Track Every Action Your Agents Take
ReskPoints is a Python library that logs every action performed by AI agents -- function calls, tool executions, LLM completions -- with full context: probability, parameters, results, and timestamps. Ship logs to Datadog, Prometheus, OpenTelemetry, webhooks, or local files. Built for observability in production AI agent deployments.
Project Stats
Key Features
Multi-Destination Logging
Send agent logs to any observability backend without changing your code.
- Datadog: Ship logs as Datadog events with custom attributes
- Prometheus: Expose metrics for agent activity, latency, error rates
- OpenTelemetry: Trace agent executions across distributed systems
- Webhooks: HTTP callbacks for real-time agent monitoring
- File: Local JSON or CSV logging for debugging
Rich Agent Context
Every log entry captures the full context of the agent action.
- Function name and parameters
- Token probabilities at decision points
- Execution duration and timestamps
- Success/failure status with error details
- Session and trace identifiers for correlation
Minimal Performance Overhead
Designed for production use with asynchronous, non-blocking log shipping.
- Async batch processing of log entries
- Configurable buffer size and flush interval
- Automatic retry on network failures
- Zero-dependency logging core
Framework Agnostic
Works with any agent framework -- LangChain, CrewAI, AutoGen, or custom implementations.
- Decorator-based instrumentation
- Context manager for manual scoping
- Middleware for framework-specific integrations
- OpenTelemetry-compatible spans
Quick Install
pip install reskpoints
Usage Example
Basic Logging
from reskpoints import AgentLogger
logger = AgentLogger(
destination="datadog",
api_key="your-datadog-key",
)
@logger.track("send_email")
def send_email(to: str, subject: str, body: str):
# Your agent action here
return {"status": "sent", "to": to}
send_email(to="user@example.com", subject="Hello")
Multi-Destination
from reskpoints import AgentLogger
logger = AgentLogger(
destinations=["datadog", "prometheus", "file"],
config={
"datadog": {"api_key": "...", "site": "datadoghq.eu"},
"prometheus": {"port": 8000, "namespace": "my_agent"},
"file": {"path": "./agent_logs.json", "format": "json"},
}
)
Get Started with ReskPoints
Add observability to your AI agent deployments.
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For technical inquiries and integration support:
contact[@]resk.fr
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