Can I trace multi-agent coordination with this skill?

Yes, it includes specialized methods for tracing routing decisions, allowing you to see how tasks are distributed between different specialized agents.

Does this skill support quality evaluation?

Yes, it provides a framework for scoring decisions after they occur, comparing them against ground truth or final task outcomes to measure accuracy.

How does this help with debugging autonomous agents?

By snapshotting context at the moment of a decision, it allows developers to replay specific steps with modified context to identify where an agent's logic went wrong.

What is the primary purpose of the decision-tracing skill?

It captures the 'why' behind agent actions, documenting the options considered, the context used, and the reasoning chains to help debug and optimize AI logic.

Decision Tracing for AI Agents

Name: Decision Tracing for AI Agents
Author: nexus-labs-automation

bynexus-labs-automation

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분석 및 모니터링

Monitors and records AI agent decision-making processes, tool selections, and reasoning chains for enhanced observability.

The Decision Tracing skill provides deep visibility into the logic behind AI agent actions by capturing the options considered, the specific tool choices made, and the context that influenced those decisions. It enables developers to move beyond logging outcomes by documenting the 'why' of every action, making it easier to debug complex multi-step workflows, evaluate agent routing, and optimize reasoning chains. With support for quality scoring and decision replay, it is an essential tool for building reliable, production-grade autonomous systems.

주요 기능

01Reasoning chain extraction and Chain of Thought (CoT) logging

02Detailed tool selection tracing with available alternatives and confidence scores

03Decision replay and context snapshotting for precise debugging

04Multi-agent routing decision analysis and scoring metrics

050 GitHub stars

06Quality evaluation patterns to score decisions against outcomes

사용 사례

01Optimizing agent efficiency by analyzing unnecessary tool calls and backtracking

02Debugging why an agent selected the wrong tool or failed to route a task correctly

03Evaluating the quality of agent reasoning chains across different model versions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nexus-labs-automation/agent-observability decision-tracing

For use in Claude.ai and ChatGPT

Download Skill