Is this compatible with existing agent frameworks?

Yes, it includes specific integration examples and code snippets for popular frameworks like LangGraph and CrewAI.

Does this skill support asynchronous workflows?

Yes, it includes built-in patterns and attributes for both synchronous blocking requests and asynchronous callback-based approval workflows.

How does this help improve agent autonomy?

By tracking escalation rates and approval outcomes over time, you can identify repetitive patterns where the agent can be safely granted more autonomy through fine-tuning or prompt adjustments.

What types of human interventions can I track?

You can track a variety of intervention types including manual approvals, clarification requests, error escalations, and general quality feedback loops.

Can I measure human response latency?

Absolutely. The skill provides specific attributes for tracking wait times, time-to-first-view, and monitoring performance against SLA targets.

Human-in-the-Loop Observability

Name: Human-in-the-Loop Observability
Author: nexus-labs-automation

bynexus-labs-automation

分析与监控

Instruments human intervention points to monitor approval workflows, feedback loops, and agent escalations within AI systems.

关于

This skill provides a standardized framework for tracking interactions between AI agents and human operators, ensuring complete observability into hybrid decision-making processes. It enables developers to monitor when and why agents request help, measure human response times against SLAs, and analyze the impact of human feedback on agent performance. By instrumenting approvals, clarifications, and escalations, teams can identify bottlenecks in hybrid workflows, audit manual overrides, and improve the long-term autonomy and reliability of their AI systems.

主要功能

0 GitHub stars
Standardized instrumentation for approval, clarification, and feedback requests
Support for both synchronous blocking and asynchronous workflow patterns
Seamless integration templates for LangGraph, CrewAI, and OpenTelemetry spans
Comprehensive SLA tracking for human-agent interaction latency and wait times
Detailed metadata capture for human decisions, modifications, and risk assessments

使用场景

Monitoring high-risk agent actions that require manual sign-off before execution
Measuring and optimizing human response times in critical customer-facing AI workflows
Analyzing the frequency and root causes of agent escalations to human operators

关于

主要功能

0 GitHub stars
Standardized instrumentation for approval, clarification, and feedback requests
Support for both synchronous blocking and asynchronous workflow patterns
Seamless integration templates for LangGraph, CrewAI, and OpenTelemetry spans
Comprehensive SLA tracking for human-agent interaction latency and wait times
Detailed metadata capture for human decisions, modifications, and risk assessments

使用场景

Monitoring high-risk agent actions that require manual sign-off before execution
Measuring and optimizing human response times in critical customer-facing AI workflows
Analyzing the frequency and root causes of agent escalations to human operators