Know exactly why your AI agent failed

AgentScope is an AI agent observability platform that helps you trace, debug, and optimize multi-agent workflows in real time.

Debug Your First AgentView Live Trace

Works with OpenAI, LangChain, and custom multi-agent systems.

Used by developers building production AI agents

AI Agents Fail - And Logs Don't Tell You Why

In production, AI agents break in ways that are hard to debug:

  • Prompts behave unpredictably
  • Tools fail silently
  • Context drifts across steps
  • Multi-agent workflows become opaque

Logs show events. They don't explain decisions.

From Logs -> Full Observability

AgentScope gives you complete visibility into your AI system:

  • Trace every step of every agent
  • Inspect prompts, outputs, and tool calls
  • Detect where things go wrong
  • Understand why failures happen

Observe -> Trace -> Debug -> Fix

  1. 1. Capture every agent interaction
  2. 2. Visualize full execution traces
  3. 3. Identify failure points instantly
  4. 4. Optimize prompts and workflows

See What Your Agent Actually Did

TimelineStep Details47.3s total

Track the exact execution path, timing, and model decisions for every run.

Execution Timeline
llm_call - 6936.6ms
llm_call - 6503.1ms
llm_call - 4133.7ms
llm_call - 6899.7ms
Step Details
llm_call
Statussuccess (system)
Duration4134 ms
Tokens463
Cost$0.0002
PROMPT: structured view
RAW JSON payload
RESPONSE preview
  • Step-by-step execution timeline
  • Prompt + response inspection
  • Tool usage tracking

Find the Root Cause Faster

Pinpoint why runs degrade with ranked insights and concrete fix guidance.

Performance Slow Span

MEDIUM

Latency is elevated (avg 6525 ms, p95 8154 ms).

Cause

Critical LLM spans are bottlenecking overall run completion time.

Fix

Profile slow spans and reduce model/tool work on critical paths.

Missing Instructions

MEDIUM

No instruction files or runtime instruction overrides were captured.

Cause

Instruction context is missing from telemetry and execution snapshots.

Fix

Load instruction files and include explicit runtime system prompts.

  • Failure detection
  • Drift analysis
  • Hallucination + schema optimization
  • Suggested fixes

Why Logs Are Not Enough

Traditional LogsAgentScope
Raw outputsStructured traces
Hard to followVisual workflows
No root causeFailure insights
FragmentedUnified system view

Built for Real AI Systems

  • Debug AI agents in production
  • Monitor multi-agent workflows
  • Analyze LLM failures
  • Optimize prompt performance

AI Agent Debugging & LLM Observability

AgentScope helps teams solve:

  • AI agent debugging
  • LLM observability
  • Multi-agent workflow monitoring
  • AI system failure analysis

If your AI agent is failing and you don't know why - AgentScope helps you find the answer.

Stop Guessing. Start Debugging.

Understand your AI agents at every step.

Debug Your First AgentView Live Demo